Added neural network trait prediction to genetic analyses.
This commit is contained in:
Simon Sarasova
parent
75331a22d3
commit
21082cfb0d
40 changed files with 3316 additions and 1666 deletions
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@ -6,6 +6,7 @@ Small and insignificant changes may not be included in this log.
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## Unversioned Changes
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* Added neural network trait prediction to genetic analyses. - *Simon Sarasova*
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* Improved the Create Genetic Models utility and neural network training code. Models are now able to predict traits with some accuracy. - *Simon Sarasova*
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* Improved ReadMe.md. - *Simon Sarasova*
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* Improved Seekia's slogan and Whitepaper.md. - *Simon Sarasova*
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@ -9,4 +9,4 @@ Many other people have written code for modules which are imported by Seekia. Th
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Name | Date Of First Commit | Number Of Commits
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--- | --- | ---
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Simon Sarasova | June 13, 2023 | 265
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Simon Sarasova | June 13, 2023 | 266
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@ -424,7 +424,7 @@ func setBuildMateProfilePage_Wealth(window fyne.Window, previousPage func()){
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}
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isLowerBoundHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
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setWealthOrIncomeIsLowerBoundExplainerPage(window, currentPage)
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setWealthIsLowerBoundExplainerPage(window, currentPage)
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})
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isLowerBoundCheckRow := container.NewHBox(layout.NewSpacer(), isLowerBoundCheck, isLowerBoundHelpButton, layout.NewSpacer())
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152
gui/helpGui.go
152
gui/helpGui.go
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@ -674,45 +674,95 @@ func setPolygenicDiseaseLocusRiskWeightProbabilityExplainerPage(window fyne.Wind
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}
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func setTraitOutcomeScoresExplainerPage(window fyne.Window, previousPage func()){
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func setDiscreteTraitNeuralNetworkPredictionExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Outcome Scores")
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title := getPageTitleCentered("Help - Neural Network Prediction")
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backButton := getBackButtonCentered(previousPage)
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subtitle := getPageSubtitleCentered("Trait Outcome Scores")
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subtitle := getPageSubtitleCentered("Discrete Trait Neural Network Prediction")
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description1 := getLabelCentered("Person genetic analyses contain trait analyses.")
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description2 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description3 := getLabelCentered("Points are added to an outcome to represent a higher probability.")
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description4 := getLabelCentered("Points are subtracted from an outcome to represent a lower probability.")
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description5 := getLabelCentered("The more rules that are tested, the higher the accuracy of the result will be.")
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description1 := getLabelCentered("Person genetic analyses contain discrete trait analyses.")
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description2 := getLabelCentered("There are 2 discrete trait analysis methods: Neural Networks and Rules.")
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description3 := getLabelCentered("Each trait can be analyzed by either rules or a neural network.")
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description4 := getLabelCentered("Neural network prediction is calculated by inputing a genome's loci into a neural network.")
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description5 := getLabelCentered("Each trait has multiple outcomes, and the neural network predicts a single outcome.")
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description6 := getLabelCentered("The higher the quantity of tested loci, the more accurate the result is.")
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description7 := getLabelCentered("The probability that a neural network's prediction is accurate is called its Confidence.")
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page := container.NewVBox(title, backButton, widget.NewSeparator(), subtitle, widget.NewSeparator(), description1, description2, description3, description4, description5)
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page := container.NewVBox(title, backButton, widget.NewSeparator(), subtitle, widget.NewSeparator(), description1, description2, description3, description4, description5, description6, description7)
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setPageContent(page, window)
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}
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func setOffspringTraitOutcomeScoresExplainerPage(window fyne.Window, previousPage func()){
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func setOffspringDiscreteTraitNeuralNetworkPredictionExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Outcome Scores")
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title := getPageTitleCentered("Help - Neural Network Prediction")
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backButton := getBackButtonCentered(previousPage)
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subtitle := getPageSubtitleCentered("Offspring Trait Outcome Scores")
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subtitle := getPageSubtitleCentered("Offspring Discrete Trait Neural Network Prediction")
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description1 := getLabelCentered("Couple genetic analyses contain trait analyses for the offspring.")
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description2 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description3 := getLabelCentered("Points are added to an outcome to represent a higher probability.")
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description4 := getLabelCentered("Points are subtracted from an outcome to represent a lower probability.")
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description5 := getLabelCentered("The more rules that are tested, the higher the accuracy of the result will be.")
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description1 := getLabelCentered("Couple genetic analyses contain discrete trait analyses.")
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description2 := getLabelCentered("There are 2 discrete trait analysis methods: Neural Networks and Rules.")
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description3 := getLabelCentered("Each trait can be analyzed by either rules or a neural network.")
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description4 := getLabelCentered("Neural network prediction is calculated by inputing a genome's loci into a neural network.")
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description5 := getLabelCentered("Each trait has multiple outcomes, and the neural network predicts the probability of each outcome.")
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description6 := getLabelCentered("The higher the quantity of known loci, the more accurate the result is.")
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description7 := getLabelCentered("The probability that a neural network's prediction is accurate is called its Confidence.")
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description8 := getLabelCentered("For couples, the Confidence is the average of the confidence of 100 prospective offspring predictions.")
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page := container.NewVBox(title, backButton, widget.NewSeparator(), subtitle, widget.NewSeparator(), description1, description2, description3, description4, description5)
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page := container.NewVBox(title, backButton, widget.NewSeparator(), subtitle, widget.NewSeparator(), description1, description2, description3, description4, description5, description6, description7, description8)
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setPageContent(page, window)
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}
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func setTraitRulesExplainerPage(window fyne.Window, previousPage func()){
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func setDiscreteTraitRulesPredictionExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Rules Prediction")
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backButton := getBackButtonCentered(previousPage)
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subtitle := getPageSubtitleCentered("Discrete Trait Rules Prediction")
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description1 := getLabelCentered("Person genetic analyses contain discrete trait analyses.")
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description2 := getLabelCentered("There are 2 discrete trait analysis methods: Neural Networks and Rules.")
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description3 := getLabelCentered("Each trait can be analyzed by either rules or a neural network.")
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description4 := getLabelCentered("Rule prediction is calculated by testing many predictive rules.")
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description5 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description6 := getLabelCentered("Points are added to an outcome to represent a higher probability.")
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description7 := getLabelCentered("Points are subtracted from an outcome to represent a lower probability.")
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description8 := getLabelCentered("The more rules that are tested, the higher the accuracy of the result will be.")
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page := container.NewVBox(title, backButton, widget.NewSeparator(), subtitle, widget.NewSeparator(), description1, description2, description3, description4, description5, description6, description7, description8)
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setPageContent(page, window)
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}
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func setOffspringDiscreteTraitRulesPredictionExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Rules Prediction")
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backButton := getBackButtonCentered(previousPage)
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subtitle := getPageSubtitleCentered("Offspring Discrete Trait Rules Prediction")
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description1 := getLabelCentered("Couple genetic analyses contain discrete trait analyses for the offspring.")
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description2 := getLabelCentered("There are 2 discrete trait analysis methods: Neural Networks and Rules.")
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description3 := getLabelCentered("Each trait can be analyzed by either rules or a neural network.")
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description4 := getLabelCentered("Rule prediction is calculated by testing many predictive rules.")
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description5 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description6 := getLabelCentered("Points are added to an outcome to represent a higher probability.")
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description7 := getLabelCentered("Points are subtracted from an outcome to represent a lower probability.")
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description8 := getLabelCentered("The more rules that are tested, the higher the accuracy of the result will be.")
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page := container.NewVBox(title, backButton, widget.NewSeparator(), subtitle, widget.NewSeparator(), description1, description2, description3, description4, description5, description6, description7, description8)
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setPageContent(page, window)
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}
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func setDiscreteTraitRulesExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Trait Rules")
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@ -720,8 +770,8 @@ func setTraitRulesExplainerPage(window fyne.Window, previousPage func()){
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subtitle := getPageSubtitleCentered("Trait Rules")
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description1 := getLabelCentered("Person genetic analyses contain trait analyses.")
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description2 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description1 := getLabelCentered("Person genetic analyses contain discrete trait analyses.")
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description2 := getLabelCentered("Discrete traits has multiple outcomes, and each outcome has an associated score.")
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description3 := getLabelCentered("A higher score represents a higher probability, and a lower score represents the opposite.")
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description4 := getLabelCentered("Each outcome's score is determined by trait rules.")
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description5 := getLabelCentered("A trait rule will add/subtract values to outcome(s).")
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@ -732,16 +782,16 @@ func setTraitRulesExplainerPage(window fyne.Window, previousPage func()){
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setPageContent(page, window)
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}
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func setOffspringTraitRulesExplainerPage(window fyne.Window, previousPage func()){
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func setOffspringDiscreteTraitRulesExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Trait Rules")
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backButton := getBackButtonCentered(previousPage)
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subtitle := getPageSubtitleCentered("Trait Rules")
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subtitle := getPageSubtitleCentered("Discrete Trait Rules")
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description1 := getLabelCentered("Offspring genetic analyses contain trait analyses for a couple's offspring.")
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description2 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description1 := getLabelCentered("Offspring genetic analyses contain discrete trait analyses for a couple's offspring.")
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description2 := getLabelCentered("Each discrete trait has multiple outcomes, and each outcome has an associated score.")
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description3 := getLabelCentered("A higher score represents a higher probability, and a lower score represents the opposite.")
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description4 := getLabelCentered("Each outcome's score is determined by trait rules.")
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description5 := getLabelCentered("A trait rule will add/subtract values to outcome(s).")
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@ -753,15 +803,15 @@ func setOffspringTraitRulesExplainerPage(window fyne.Window, previousPage func()
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setPageContent(page, window)
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}
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func setTraitNumberOfRulesTestedExplainerPage(window fyne.Window, previousPage func()){
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func setDiscreteTraitQuantityOfRulesTestedExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Number Of Rules Tested")
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title := getPageTitleCentered("Help - Quantity Of Rules Tested")
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backButton := getBackButtonCentered(previousPage)
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subtitle := getPageSubtitleCentered("Number Of Trait Rules Tested")
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subtitle := getPageSubtitleCentered("Quantity Of Trait Rules Tested")
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description1 := getLabelCentered("Person genetic analyses contain trait analyses.")
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description1 := getLabelCentered("Person genetic analyses contain discrete trait analyses.")
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description2 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description3 := getLabelCentered("A higher score represents a higher probability, and a lower score represent the opposite.")
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description4 := getLabelCentered("Each outcome's score is determined by trait rules.")
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@ -775,13 +825,13 @@ func setTraitNumberOfRulesTestedExplainerPage(window fyne.Window, previousPage f
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setPageContent(page, window)
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}
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func setOffspringTraitNumberOfRulesTestedExplainerPage(window fyne.Window, previousPage func()){
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func setOffspringDiscreteTraitQuantityOfRulesTestedExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Number Of Rules Tested")
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title := getPageTitleCentered("Help - Quantity Of Rules Tested")
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backButton := getBackButtonCentered(previousPage)
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subtitle := getPageSubtitleCentered("Offspring Trait Number Of Rules Tested")
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subtitle := getPageSubtitleCentered("Offspring Trait Quantity Of Rules Tested")
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description1 := getLabelCentered("Offspring genetic analyses contain trait analyses for a couple's offspring.")
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description2 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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@ -806,8 +856,8 @@ func setOffspringProbabilityOfPassingTraitRuleExplainerPage(window fyne.Window,
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subtitle := getPageSubtitleCentered("Offspring Probability Of Passing Trait Rule")
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description1 := getLabelCentered("Offspring genetic analyses contain trait analyses for a couple's offspring.")
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description2 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description1 := getLabelCentered("Offspring genetic analyses contain discrete trait analyses for a couple's offspring.")
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description2 := getLabelCentered("Each discrete trait has multiple outcomes, and each outcome has an associated score.")
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description3 := getLabelCentered("A higher score represents a higher probability, and a lower score represents the opposite.")
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description4 := getLabelCentered("Each outcome's score is determined by trait rules.")
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description5 := getLabelCentered("A trait rule will add/subtract values to outcome(s).")
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@ -821,8 +871,7 @@ func setOffspringProbabilityOfPassingTraitRuleExplainerPage(window fyne.Window,
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setPageContent(page, window)
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}
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func setPersonPassesTraitRuleExplainerPage(window fyne.Window, previousPage func()){
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func setPersonPassesDiscreteTraitRuleExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Trait Rules")
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@ -830,8 +879,8 @@ func setPersonPassesTraitRuleExplainerPage(window fyne.Window, previousPage func
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subtitle := getPageSubtitleCentered("Person Passes Trait Rule")
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description1 := getLabelCentered("Person genetic analyses contain trait analyses.")
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description2 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description1 := getLabelCentered("Person genetic analyses contain discrete trait analyses.")
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description2 := getLabelCentered("Each discrete trait has multiple outcomes, and each outcome has an associated score.")
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description3 := getLabelCentered("A higher score represents a higher probability, and a lower score represents the opposite.")
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description4 := getLabelCentered("Each outcome's score is determined by trait rules.")
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description5 := getLabelCentered("A trait rule will add/subtract values to outcome(s).")
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@ -842,7 +891,7 @@ func setPersonPassesTraitRuleExplainerPage(window fyne.Window, previousPage func
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setPageContent(page, window)
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}
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func setGenomePassesTraitRuleExplainerPage(window fyne.Window, previousPage func()){
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func setGenomePassesDiscreteTraitRuleExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Genome Passes Rule")
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@ -850,22 +899,23 @@ func setGenomePassesTraitRuleExplainerPage(window fyne.Window, previousPage func
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subtitle := getPageSubtitleCentered("Genome Passes Trait Rule")
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description1 := getLabelCentered("Person genetic analyses contain trait analyses.")
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description2 := getLabelCentered("Each trait has multiple outcomes, and each outcome has an associated score.")
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description3 := getLabelCentered("A higher score represents a higher probability, and a lower score represents the opposite.")
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description4 := getLabelCentered("Each outcome's score is determined by trait rules.")
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description5 := getLabelCentered("A trait rule will add/subtract values to outcome(s).")
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description6 := getLabelCentered("If a person passes a rule, its effects will be applied to their outcome(s).")
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description7 := getLabelCentered("If a person has imported multiple genomes, each genome may or may not pass the rule.")
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description8 := getLabelCentered("If one genome passes and another does not, it means that one genome has an invalid value.")
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description9 := getLabelCentered("This happens because genome sequencing technology is not perfectly accurate.")
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description1 := getLabelCentered("Person genetic analyses contain discrete trait analyses.")
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description2 := getLabelCentered("There are 2 discrete trait analysis methods: Rules and Neural Networks.")
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description3 := getLabelCentered("For rule-based analyses, each trait's outcome has an associated score.")
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description4 := getLabelCentered("A higher score represents a higher probability, and a lower score represents the opposite.")
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description5 := getLabelCentered("Each outcome's score is determined by trait rules.")
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description6 := getLabelCentered("A trait rule will add/subtract values to outcome(s).")
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description7 := getLabelCentered("If a person passes a rule, its effects will be applied to their outcome(s).")
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description8 := getLabelCentered("If a person has imported multiple genomes, each genome may or may not pass the rule.")
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description9 := getLabelCentered("If one genome passes and another does not, it means that one genome has an invalid value.")
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description10 := getLabelCentered("This happens because genome sequencing technology is not perfectly accurate.")
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page := container.NewVBox(title, backButton, widget.NewSeparator(), subtitle, widget.NewSeparator(), description1, description2, description3, description4, description5, description6, description7, description8, description9)
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page := container.NewVBox(title, backButton, widget.NewSeparator(), subtitle, widget.NewSeparator(), description1, description2, description3, description4, description5, description6, description7, description8, description9, description10)
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setPageContent(page, window)
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}
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func setTraitRuleOutcomeEffectsExplainerPage(window fyne.Window, previousPage func()){
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func setDiscreteTraitRuleOutcomeEffectsExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Outcome Effects")
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@ -885,7 +935,7 @@ func setTraitRuleOutcomeEffectsExplainerPage(window fyne.Window, previousPage fu
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}
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func setWealthOrIncomeIsLowerBoundExplainerPage(window fyne.Window, previousPage func()){
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func setWealthIsLowerBoundExplainerPage(window fyne.Window, previousPage func()){
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title := getPageTitleCentered("Help - Is Lower Bound")
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@ -10,6 +10,7 @@ import "fyne.io/fyne/v2/theme"
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import "fyne.io/fyne/v2/widget"
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import "fyne.io/fyne/v2/canvas"
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import "seekia/resources/geneticPredictionModels"
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import "seekia/resources/geneticReferences/monogenicDiseases"
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import "seekia/resources/geneticReferences/polygenicDiseases"
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import "seekia/resources/geneticReferences/traits"
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@ -48,7 +49,7 @@ func setViewCoupleGeneticAnalysisPage(window fyne.Window, person1Identifier stri
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return
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}
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if (person1Found == false){
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setErrorEncounteredPage(window, errors.New("Couple person A not found."), previousPage)
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setErrorEncounteredPage(window, errors.New("Couple person 1 not found."), previousPage)
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return
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}
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@ -58,7 +59,7 @@ func setViewCoupleGeneticAnalysisPage(window fyne.Window, person1Identifier stri
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return
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}
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if (person2Found == false){
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setErrorEncounteredPage(window, errors.New("Couple person B not found."), previousPage)
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setErrorEncounteredPage(window, errors.New("Couple person 2 not found."), previousPage)
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return
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}
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@ -88,11 +89,15 @@ func setViewCoupleGeneticAnalysisPage(window fyne.Window, person1Identifier stri
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polygenicDiseasesButton := widget.NewButton("Polygenic Diseases", func(){
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setViewCoupleGeneticAnalysisPolygenicDiseasesPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, currentPage)
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})
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traitsButton := widget.NewButton("Traits", func(){
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setViewCoupleGeneticAnalysisTraitsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, currentPage)
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discreteTraitsButton := widget.NewButton("Discrete Traits", func(){
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setViewCoupleGeneticAnalysisDiscreteTraitsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, currentPage)
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})
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numericTraitsButton := widget.NewButton("Numeric Traits", func(){
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//TODO
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showUnderConstructionDialog(window)
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})
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categoryButtonsGrid := getContainerCentered(container.NewGridWithColumns(1, generalButton, monogenicDiseasesButton, polygenicDiseasesButton, traitsButton))
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categoryButtonsGrid := getContainerCentered(container.NewGridWithColumns(1, generalButton, monogenicDiseasesButton, polygenicDiseasesButton, discreteTraitsButton, numericTraitsButton))
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page := container.NewVBox(title, backButton, widget.NewSeparator(), warningLabel1, warningLabel2, widget.NewSeparator(), coupleNameRow, widget.NewSeparator(), numberOfAnalyzedGenomesLabel, person1NumberOfAnalyzedGenomesRow, person2NumberOfAnalyzedGenomesRow, widget.NewSeparator(), categoryButtonsGrid)
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@ -1327,7 +1332,7 @@ func setViewCoupleGeneticAnalysisPolygenicDiseaseGenomePairDetailsPage(window fy
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|
||||
genomeNameLabel := getBoldLabelCentered(genomeName)
|
||||
|
||||
personRiskScoreKnown, _, personRiskScoreFormatted, _, numberOfLociTested, _, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject, diseaseName, personAnalysisGenomeIdentifier)
|
||||
personRiskScoreKnown, _, personRiskScoreFormatted, numberOfLociTested, _, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject, diseaseName, personAnalysisGenomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
|
||||
getPersonRiskScoreLabelText := func()string{
|
||||
|
|
@ -1860,120 +1865,206 @@ func setViewPolygenicDiseaseSampleOffspringRiskScoresChart(window fyne.Window, d
|
|||
}
|
||||
|
||||
|
||||
func setViewCoupleGeneticAnalysisTraitsPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, previousPage func()){
|
||||
func setViewCoupleGeneticAnalysisDiscreteTraitsPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, previousPage func()){
|
||||
|
||||
currentPage := func(){setViewCoupleGeneticAnalysisTraitsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, previousPage)}
|
||||
currentPage := func(){setViewCoupleGeneticAnalysisDiscreteTraitsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("Viewing Genetic Analysis - Traits")
|
||||
title := getPageTitleCentered("Viewing Genetic Analysis - Discrete Traits")
|
||||
|
||||
backButton := getBackButtonCentered(previousPage)
|
||||
|
||||
description := getLabelCentered("Below is an analysis of the average trait scores for the couple's offspring.")
|
||||
description := getLabelCentered("Below is an analysis of the average discrete trait outcomes for the couple's offspring.")
|
||||
|
||||
getTraitsGrid := func()(*fyne.Container, error){
|
||||
|
||||
pair1Person1GenomeIdentifier, pair1Person2GenomeIdentifier, secondGenomePairExists, _, _, _, _, _, _, _, _, err := readGeneticAnalysis.GetMetadataFromCoupleGeneticAnalysis(coupleAnalysisObject)
|
||||
if (err != nil){ return nil, err }
|
||||
|
||||
mainGenomePairIdentifier := helpers.JoinTwo16ByteArrays(pair1Person1GenomeIdentifier, pair1Person2GenomeIdentifier)
|
||||
|
||||
emptyLabel1 := widget.NewLabel("")
|
||||
traitNameLabel := getItalicLabelCentered("Trait Name")
|
||||
|
||||
offspringOutcomeScoresLabel := getItalicLabelCentered("Offspring Outcome Scores")
|
||||
emptyLabel2 := widget.NewLabel("")
|
||||
predictedProbabilitiesLabel := getItalicLabelCentered("Predicted Probabilities")
|
||||
|
||||
quantityOfLabel := getItalicLabelCentered("Quantity Of")
|
||||
lociKnownLabel := getItalicLabelCentered("Loci Known")
|
||||
|
||||
emptyLabel3 := widget.NewLabel("")
|
||||
conflictExistsLabel := getItalicLabelCentered("Conflict Exists?")
|
||||
|
||||
emptyLabel := widget.NewLabel("")
|
||||
emptyLabel4 := widget.NewLabel("")
|
||||
emptyLabel5 := widget.NewLabel("")
|
||||
|
||||
traitNameColumn := container.NewVBox(traitNameLabel, widget.NewSeparator())
|
||||
offspringOutcomeScoresColumn := container.NewVBox(offspringOutcomeScoresLabel, widget.NewSeparator())
|
||||
conflictExistsColumn := container.NewVBox(conflictExistsLabel, widget.NewSeparator())
|
||||
viewButtonsColumn := container.NewVBox(emptyLabel, widget.NewSeparator())
|
||||
traitNameColumn := container.NewVBox(emptyLabel1, traitNameLabel, widget.NewSeparator())
|
||||
predictedProbabilitiesColumn := container.NewVBox(emptyLabel2, predictedProbabilitiesLabel, widget.NewSeparator())
|
||||
quantityOfLociKnownColumn := container.NewVBox(quantityOfLabel, lociKnownLabel, widget.NewSeparator())
|
||||
conflictExistsColumn := container.NewVBox(emptyLabel3, conflictExistsLabel, widget.NewSeparator())
|
||||
viewDetailsButtonsColumn := container.NewVBox(emptyLabel4, emptyLabel5, widget.NewSeparator())
|
||||
|
||||
traitObjectsList, err := traits.GetTraitObjectsList()
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
for _, traitObject := range traitObjectsList{
|
||||
|
||||
traitName := traitObject.TraitName
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
if (traitIsDiscreteOrNumeric != "Discrete"){
|
||||
continue
|
||||
}
|
||||
|
||||
traitLociList := traitObject.LociList
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
if (len(traitRulesList) == 0){
|
||||
if (len(traitLociList) == 0 && len(traitRulesList) == 0){
|
||||
// This trait does not have any rules
|
||||
// We cannot analyze it yet
|
||||
// We will add neural network prediction so we can predict these traits
|
||||
continue
|
||||
}
|
||||
|
||||
mainGenomePairIdentifier := helpers.JoinTwo16ByteArrays(pair1Person1GenomeIdentifier, pair1Person2GenomeIdentifier)
|
||||
traitName := traitObject.TraitName
|
||||
|
||||
offspringOutcomeScoresKnown, offspringAverageOutcomeScoresMap, _, conflictExists, err := readGeneticAnalysis.GetOffspringTraitInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, mainGenomePairIdentifier)
|
||||
neuralNetworkExists, neuralNetworkAnalysisExists, offspringOutcomeProbabilitiesMap_NeuralNetwork, _, quantityOfLociKnown_NeuralNetwork, _, anyRulesExist, rulesAnalysisExists, offspringOutcomeProbabilitiesMap_Rules, _, _, quantityOfLociKnown_Rules, conflictExists, err := readGeneticAnalysis.GetOffspringDiscreteTraitInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, mainGenomePairIdentifier)
|
||||
if (err != nil) { return nil, err }
|
||||
if (neuralNetworkExists == false && anyRulesExist == false){
|
||||
// We cannot analyze this trait
|
||||
continue
|
||||
}
|
||||
|
||||
// We add all of the columns except for the trait outcomes column, which may be multiple rows high
|
||||
getQuantityOfLociKnown := func()int{
|
||||
if (neuralNetworkExists == true){
|
||||
return quantityOfLociKnown_NeuralNetwork
|
||||
}
|
||||
return quantityOfLociKnown_Rules
|
||||
}
|
||||
|
||||
traitNameText := getBoldLabelCentered(traitName)
|
||||
quantityOfLociKnown := getQuantityOfLociKnown()
|
||||
|
||||
getTotalQuantityOfLoci := func()int{
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
totalQuantityOfLoci := len(traitLociList)
|
||||
|
||||
return totalQuantityOfLoci
|
||||
}
|
||||
|
||||
traitLociList_Rules := traitObject.LociList_Rules
|
||||
|
||||
totalQuantityOfLoci := len(traitLociList_Rules)
|
||||
|
||||
return totalQuantityOfLoci
|
||||
}
|
||||
|
||||
totalQuantityOfLoci := getTotalQuantityOfLoci()
|
||||
|
||||
quantityOfLociKnownString := helpers.ConvertIntToString(quantityOfLociKnown)
|
||||
totalQuantityOfLociString := helpers.ConvertIntToString(totalQuantityOfLoci)
|
||||
|
||||
quantityOfLociKnownFormatted := quantityOfLociKnownString + "/" + totalQuantityOfLociString
|
||||
|
||||
quantityOfLociKnownLabel := getBoldLabelCentered(quantityOfLociKnownFormatted)
|
||||
|
||||
// We add each row except for the outcome rows
|
||||
// The outcome grid cell can be multiple rows tall
|
||||
|
||||
traitNameLabel := getBoldLabelCentered(traitName)
|
||||
|
||||
conflictExistsString := helpers.ConvertBoolToYesOrNoString(conflictExists)
|
||||
conflictExistsLabel := getBoldLabelCentered(conflictExistsString)
|
||||
|
||||
viewDetailsButton := getWidgetCentered(widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
setViewCoupleGeneticAnalysisTraitDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, currentPage)
|
||||
setViewCoupleGeneticAnalysisDiscreteTraitDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, currentPage)
|
||||
}))
|
||||
|
||||
traitNameColumn.Add(traitNameText)
|
||||
traitNameColumn.Add(traitNameLabel)
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownLabel)
|
||||
conflictExistsColumn.Add(conflictExistsLabel)
|
||||
viewButtonsColumn.Add(viewDetailsButton)
|
||||
viewDetailsButtonsColumn.Add(viewDetailsButton)
|
||||
|
||||
if (offspringOutcomeScoresKnown == false){
|
||||
// Outputs:
|
||||
// -bool: Outcome probabilities exist
|
||||
// -map[string]int: Outcome Name -> Probability of outcome (0-100)
|
||||
getOutcomeProbabilitiesMap := func()(bool, map[string]int){
|
||||
|
||||
unknownTranslated := translate("Unknown")
|
||||
unknownLabel := getBoldLabelCentered(unknownTranslated)
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
offspringOutcomeScoresColumn.Add(unknownLabel)
|
||||
} else {
|
||||
|
||||
outcomeNamesList := helpers.GetListOfMapKeys(offspringAverageOutcomeScoresMap)
|
||||
|
||||
// We have to sort outcome names so they always show up in the same order
|
||||
helpers.SortStringListToUnicodeOrder(outcomeNamesList)
|
||||
|
||||
for index, outcomeName := range outcomeNamesList{
|
||||
|
||||
outcomeScore, exists := offspringAverageOutcomeScoresMap[outcomeName]
|
||||
if (exists == false){
|
||||
return nil, errors.New("Outcome name not found in outcomeScoresMap after being found already.")
|
||||
if (neuralNetworkAnalysisExists == false){
|
||||
return false, nil
|
||||
}
|
||||
|
||||
outcomeScoreString := helpers.ConvertFloat64ToStringRounded(outcomeScore, 2)
|
||||
return true, offspringOutcomeProbabilitiesMap_NeuralNetwork
|
||||
}
|
||||
|
||||
outcomeRow := getBoldLabelCentered(outcomeName + ": " + outcomeScoreString)
|
||||
offspringOutcomeScoresColumn.Add(outcomeRow)
|
||||
//anyRulesExist must be true
|
||||
if (rulesAnalysisExists == false){
|
||||
return false, nil
|
||||
}
|
||||
return true, offspringOutcomeProbabilitiesMap_Rules
|
||||
}
|
||||
|
||||
if (index > 0){
|
||||
outcomeProbabilitiesExist, outcomeProbabilitiesMap := getOutcomeProbabilitiesMap()
|
||||
if (outcomeProbabilitiesExist == false){
|
||||
unknownLabel := getItalicLabelCentered("Unknown")
|
||||
predictedProbabilitiesColumn.Add(unknownLabel)
|
||||
} else {
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
outcomeNamesList := traitObject.OutcomesList
|
||||
|
||||
traitNameColumn.Add(emptyLabelA)
|
||||
conflictExistsColumn.Add(emptyLabelB)
|
||||
viewButtonsColumn.Add(emptyLabelC)
|
||||
outcomeNamesListSorted := helpers.CopyAndSortStringListToUnicodeOrder(outcomeNamesList)
|
||||
|
||||
addedItems := 0
|
||||
|
||||
for _, outcomeName := range outcomeNamesListSorted{
|
||||
|
||||
outcomeProbability, exists := outcomeProbabilitiesMap[outcomeName]
|
||||
if (exists == false){
|
||||
continue
|
||||
}
|
||||
|
||||
if (outcomeProbability == 0){
|
||||
continue
|
||||
}
|
||||
|
||||
outcomeProbabilityString := helpers.ConvertIntToString(outcomeProbability)
|
||||
|
||||
outcomeRowLabel := getBoldLabel(outcomeName + ": " + outcomeProbabilityString + "%")
|
||||
|
||||
predictedProbabilitiesColumn.Add(outcomeRowLabel)
|
||||
|
||||
addedItems += 1
|
||||
|
||||
if (addedItems != 1){
|
||||
// We have to add whitespace to the other columns
|
||||
traitNameColumn.Add(widget.NewLabel(""))
|
||||
quantityOfLociKnownColumn.Add(widget.NewLabel(""))
|
||||
conflictExistsColumn.Add(widget.NewLabel(""))
|
||||
viewDetailsButtonsColumn.Add(widget.NewLabel(""))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
traitNameColumn.Add(widget.NewSeparator())
|
||||
offspringOutcomeScoresColumn.Add(widget.NewSeparator())
|
||||
predictedProbabilitiesColumn.Add(widget.NewSeparator())
|
||||
quantityOfLociKnownColumn.Add(widget.NewSeparator())
|
||||
conflictExistsColumn.Add(widget.NewSeparator())
|
||||
viewButtonsColumn.Add(widget.NewSeparator())
|
||||
viewDetailsButtonsColumn.Add(widget.NewSeparator())
|
||||
}
|
||||
|
||||
offspringOutcomeScoresHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringTraitOutcomeScoresExplainerPage(window, currentPage)
|
||||
predictedProbabilitiesHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
offspringOutcomeScoresColumn.Add(offspringOutcomeScoresHelpButton)
|
||||
predictedProbabilitiesColumn.Add(predictedProbabilitiesHelpButton)
|
||||
|
||||
traitsGrid := container.NewHBox(layout.NewSpacer(), traitNameColumn, offspringOutcomeScoresColumn)
|
||||
quantityOfLociKnownHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownHelpButton)
|
||||
|
||||
traitsGrid := container.NewHBox(layout.NewSpacer(), traitNameColumn, predictedProbabilitiesColumn, quantityOfLociKnownColumn)
|
||||
|
||||
if (secondGenomePairExists == true){
|
||||
|
||||
|
|
@ -1985,7 +2076,7 @@ func setViewCoupleGeneticAnalysisTraitsPage(window fyne.Window, person1Name stri
|
|||
traitsGrid.Add(conflictExistsColumn)
|
||||
}
|
||||
|
||||
traitsGrid.Add(viewButtonsColumn)
|
||||
traitsGrid.Add(viewDetailsButtonsColumn)
|
||||
traitsGrid.Add(layout.NewSpacer())
|
||||
|
||||
return traitsGrid, nil
|
||||
|
|
@ -2003,10 +2094,9 @@ func setViewCoupleGeneticAnalysisTraitsPage(window fyne.Window, person1Name stri
|
|||
}
|
||||
|
||||
|
||||
func setViewCoupleGeneticAnalysisDiscreteTraitDetailsPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, previousPage func()){
|
||||
|
||||
func setViewCoupleGeneticAnalysisTraitDetailsPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, previousPage func()){
|
||||
|
||||
currentPage := func(){setViewCoupleGeneticAnalysisTraitDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, previousPage)}
|
||||
currentPage := func(){setViewCoupleGeneticAnalysisDiscreteTraitDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("Viewing Couple Analysis - " + traitName)
|
||||
|
||||
|
|
@ -2043,17 +2133,32 @@ func setViewCoupleGeneticAnalysisTraitDetailsPage(window fyne.Window, person1Nam
|
|||
})
|
||||
traitNameRow := container.NewHBox(layout.NewSpacer(), traitNameLabel, traitNameText, traitNameInfoButton, layout.NewSpacer())
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
neuralNetworkExists, _ := geneticPredictionModels.GetGeneticPredictionModelBytes(traitName)
|
||||
|
||||
offspringOutcomeScoresLabel := getItalicLabelCentered("Offspring Outcome Scores")
|
||||
emptyLabel1 := widget.NewLabel("")
|
||||
emptyLabel2 := widget.NewLabel("")
|
||||
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
emptyLabel3 := widget.NewLabel("")
|
||||
genomePairLabel := getItalicLabelCentered("Genome Pair")
|
||||
|
||||
viewGenomePairButtonsColumn := container.NewVBox(emptyLabelA, widget.NewSeparator())
|
||||
pairNameColumn := container.NewVBox(emptyLabelB, widget.NewSeparator())
|
||||
offspringOutcomeScoresColumn := container.NewVBox(offspringOutcomeScoresLabel, widget.NewSeparator())
|
||||
viewOffspringRulesButtonsColumn := container.NewVBox(emptyLabelC, widget.NewSeparator())
|
||||
emptyLabel4 := widget.NewLabel("")
|
||||
predictedProbabilitiesLabel := getItalicLabelCentered("Predicted Probabilities")
|
||||
|
||||
predictionLabel := getItalicLabelCentered("Prediction")
|
||||
confidenceLabel := getItalicLabelCentered("Confidence")
|
||||
|
||||
quantityOfLabel := getItalicLabelCentered("Quantity Of")
|
||||
rulesTestedLabel := getItalicLabelCentered("Rules Tested")
|
||||
|
||||
emptyLabel5 := widget.NewLabel("")
|
||||
emptyLabel6 := widget.NewLabel("")
|
||||
|
||||
viewGenomePairButtonsColumn := container.NewVBox(emptyLabel1, emptyLabel2, widget.NewSeparator())
|
||||
pairNameColumn := container.NewVBox(emptyLabel3, genomePairLabel, widget.NewSeparator())
|
||||
predictedProbabilitiesColumn := container.NewVBox(emptyLabel4, predictedProbabilitiesLabel, widget.NewSeparator())
|
||||
neuralNetworkPredictionConfidenceColumn := container.NewVBox(predictionLabel, confidenceLabel, widget.NewSeparator())
|
||||
quantityOfRulesTestedColumn := container.NewVBox(quantityOfLabel, rulesTestedLabel, widget.NewSeparator())
|
||||
viewDetailsButtonsColumn := container.NewVBox(emptyLabel5, emptyLabel6, widget.NewSeparator())
|
||||
|
||||
addGenomePairRow := func(genomePairName string, person1GenomeIdentifier [16]byte, person2GenomeIdentifier [16]byte)error{
|
||||
|
||||
|
|
@ -2062,65 +2167,143 @@ func setViewCoupleGeneticAnalysisTraitDetailsPage(window fyne.Window, person1Nam
|
|||
genomePairNameLabel := getBoldLabelCentered(genomePairName)
|
||||
|
||||
viewGenomePairButton := widget.NewButtonWithIcon("", theme.InfoIcon(), func(){
|
||||
setViewCoupleGeneticAnalysisTraitGenomePairDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, currentPage)
|
||||
setViewCoupleGeneticAnalysisDiscreteTraitGenomePairDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, currentPage)
|
||||
})
|
||||
|
||||
|
||||
viewOffspringRulesButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
setViewCoupleTraitRulesPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, currentPage)
|
||||
viewAnalysisDetailsButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
if (neuralNetworkExists == true){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
} else {
|
||||
setViewCoupleDiscreteTraitRulesPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, currentPage)
|
||||
}
|
||||
})
|
||||
|
||||
// We add all of the columns except for the trait rule column, which may be multiple rows high
|
||||
|
||||
viewGenomePairButtonsColumn.Add(viewGenomePairButton)
|
||||
pairNameColumn.Add(genomePairNameLabel)
|
||||
viewOffspringRulesButtonsColumn.Add(viewOffspringRulesButton)
|
||||
viewDetailsButtonsColumn.Add(viewAnalysisDetailsButton)
|
||||
|
||||
offspringOutcomeScoresKnown, offspringOutcomeScoresMap, _, _, err := readGeneticAnalysis.GetOffspringTraitInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, genomePairIdentifier)
|
||||
traitObject, err := traits.GetTraitObject(traitName)
|
||||
if (err != nil) { return err }
|
||||
if (offspringOutcomeScoresKnown == false){
|
||||
|
||||
unknownTranslated := translate("Unknown")
|
||||
unknownLabel := getBoldLabelCentered(unknownTranslated)
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
if (traitIsDiscreteOrNumeric != "Discrete"){
|
||||
return errors.New("setViewCoupleGeneticAnalysisDiscreteTraitDetailsPage called with non-discrete trait: " + traitName)
|
||||
}
|
||||
|
||||
offspringOutcomeScoresColumn.Add(unknownLabel)
|
||||
neuralNetworkExists, neuralNetworkAnalysisExists, offspringOutcomeProbabilitiesMap_NeuralNetwork, neuralNetworkPredictionConfidence, _, _, anyRulesExist, rulesAnalysisExists, offspringOutcomeProbabilitiesMap_Rules, _, quantityOfRulesTested, _, _, err := readGeneticAnalysis.GetOffspringDiscreteTraitInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, genomePairIdentifier)
|
||||
if (err != nil) { return err }
|
||||
if (neuralNetworkExists == false && anyRulesExist == false){
|
||||
return errors.New("setViewCoupleGeneticAnalysisDiscreteTraitDetailsPage called with trait that is not analyzable.")
|
||||
}
|
||||
|
||||
// First we add analysis details to their respective column
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
if (neuralNetworkAnalysisExists == false){
|
||||
|
||||
neuralNetworkPredictionConfidenceColumn.Add(getLabelCentered("-"))
|
||||
} else {
|
||||
|
||||
predictionConfidenceString := helpers.ConvertIntToString(neuralNetworkPredictionConfidence)
|
||||
|
||||
predictionConfidenceLabel := getBoldLabelCentered(predictionConfidenceString + "%")
|
||||
|
||||
neuralNetworkPredictionConfidenceColumn.Add(predictionConfidenceLabel)
|
||||
}
|
||||
|
||||
} else {
|
||||
if (anyRulesExist == false){
|
||||
return errors.New("setViewCoupleGeneticAnalysisDiscreteTraitDetailsPage called with analysis which is missing ")
|
||||
}
|
||||
|
||||
outcomeNamesList := helpers.GetListOfMapKeys(offspringOutcomeScoresMap)
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
// We have to sort the outcome names so they always show up in the same order
|
||||
helpers.SortStringListToUnicodeOrder(outcomeNamesList)
|
||||
totalNumberOfRules := len(traitRulesList)
|
||||
|
||||
for index, outcomeName := range outcomeNamesList{
|
||||
totalNumberOfRulesString := helpers.ConvertIntToString(totalNumberOfRules)
|
||||
|
||||
outcomeScore, exists := offspringOutcomeScoresMap[outcomeName]
|
||||
if (exists == false){
|
||||
return errors.New("Outcome name not found in outcome scores map after being found already.")
|
||||
quantityOfRulesTestedString := helpers.ConvertIntToString(quantityOfRulesTested)
|
||||
|
||||
quantityOfRulesTestedFormatted := quantityOfRulesTestedString + "/" + totalNumberOfRulesString
|
||||
|
||||
quantityOfRulesTestedLabel := getBoldLabelCentered(quantityOfRulesTestedFormatted)
|
||||
|
||||
quantityOfRulesTestedColumn.Add(quantityOfRulesTestedLabel)
|
||||
}
|
||||
|
||||
// Now we add the outcome probabilities cell
|
||||
|
||||
// Outputs:
|
||||
// -bool: Outcome probabilities exist
|
||||
// -map[string]int: Outcome Name -> Probability of outcome (0-100)
|
||||
getOutcomeProbabilitiesMap := func()(bool, map[string]int){
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
if (neuralNetworkAnalysisExists == false){
|
||||
return false, nil
|
||||
}
|
||||
|
||||
outcomeScoreString := helpers.ConvertFloat64ToStringRounded(outcomeScore, 2)
|
||||
return true, offspringOutcomeProbabilitiesMap_NeuralNetwork
|
||||
}
|
||||
|
||||
outcomeRow := getBoldLabelCentered(outcomeName + ": " + outcomeScoreString)
|
||||
offspringOutcomeScoresColumn.Add(outcomeRow)
|
||||
//anyRulesExist must be true
|
||||
if (rulesAnalysisExists == false){
|
||||
return false, nil
|
||||
}
|
||||
return true, offspringOutcomeProbabilitiesMap_Rules
|
||||
}
|
||||
|
||||
if (index > 0){
|
||||
outcomeProbabilitiesExist, outcomeProbabilitiesMap := getOutcomeProbabilitiesMap()
|
||||
if (outcomeProbabilitiesExist == false){
|
||||
unknownLabel := getItalicLabelCentered("Unknown")
|
||||
predictedProbabilitiesColumn.Add(unknownLabel)
|
||||
} else {
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
outcomeNamesList := traitObject.OutcomesList
|
||||
|
||||
pairNameColumn.Add(emptyLabelA)
|
||||
viewGenomePairButtonsColumn.Add(emptyLabelB)
|
||||
viewOffspringRulesButtonsColumn.Add(emptyLabelC)
|
||||
outcomeNamesListSorted := helpers.CopyAndSortStringListToUnicodeOrder(outcomeNamesList)
|
||||
|
||||
addedItems := 0
|
||||
|
||||
for _, outcomeName := range outcomeNamesListSorted{
|
||||
|
||||
outcomeProbability, exists := outcomeProbabilitiesMap[outcomeName]
|
||||
if (exists == false){
|
||||
continue
|
||||
}
|
||||
|
||||
if (outcomeProbability == 0){
|
||||
continue
|
||||
}
|
||||
|
||||
outcomeProbabilityString := helpers.ConvertIntToString(outcomeProbability)
|
||||
|
||||
outcomeRowLabel := getBoldLabel(outcomeName + ": " + outcomeProbabilityString + "%")
|
||||
|
||||
predictedProbabilitiesColumn.Add(outcomeRowLabel)
|
||||
|
||||
addedItems += 1
|
||||
|
||||
if (addedItems > 1){
|
||||
// We have to add whitespace to the other columns
|
||||
viewGenomePairButtonsColumn.Add(widget.NewLabel(""))
|
||||
pairNameColumn.Add(widget.NewLabel(""))
|
||||
neuralNetworkPredictionConfidenceColumn.Add(widget.NewLabel(""))
|
||||
quantityOfRulesTestedColumn.Add(widget.NewLabel(""))
|
||||
viewDetailsButtonsColumn.Add(widget.NewLabel(""))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
viewGenomePairButtonsColumn.Add(widget.NewSeparator())
|
||||
pairNameColumn.Add(widget.NewSeparator())
|
||||
offspringOutcomeScoresColumn.Add(widget.NewSeparator())
|
||||
viewOffspringRulesButtonsColumn.Add(widget.NewSeparator())
|
||||
predictedProbabilitiesColumn.Add(widget.NewSeparator())
|
||||
neuralNetworkPredictionConfidenceColumn.Add(widget.NewSeparator())
|
||||
quantityOfRulesTestedColumn.Add(widget.NewSeparator())
|
||||
viewDetailsButtonsColumn.Add(widget.NewSeparator())
|
||||
|
||||
return nil
|
||||
}
|
||||
|
|
@ -2139,13 +2322,39 @@ func setViewCoupleGeneticAnalysisTraitDetailsPage(window fyne.Window, person1Nam
|
|||
}
|
||||
}
|
||||
|
||||
offspringOutcomeScoresHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringTraitOutcomeScoresExplainerPage(window, currentPage)
|
||||
predictedProbabilitiesHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
|
||||
offspringOutcomeScoresColumn.Add(offspringOutcomeScoresHelpButton)
|
||||
predictedProbabilitiesColumn.Add(predictedProbabilitiesHelpButton)
|
||||
|
||||
genomesContainer := container.NewHBox(layout.NewSpacer(), viewGenomePairButtonsColumn, pairNameColumn, offspringOutcomeScoresColumn, viewOffspringRulesButtonsColumn, layout.NewSpacer())
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
neuralNetworkPredictionConfidenceHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringDiscreteTraitNeuralNetworkPredictionExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
neuralNetworkPredictionConfidenceColumn.Add(neuralNetworkPredictionConfidenceHelpButton)
|
||||
} else {
|
||||
quantityOfRulesTestedHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringDiscreteTraitQuantityOfRulesTestedExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
quantityOfRulesTestedColumn.Add(quantityOfRulesTestedHelpButton)
|
||||
}
|
||||
|
||||
genomesContainer := container.NewHBox(layout.NewSpacer(), viewGenomePairButtonsColumn, pairNameColumn, predictedProbabilitiesColumn)
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
genomesContainer.Add(neuralNetworkPredictionConfidenceColumn)
|
||||
} else {
|
||||
genomesContainer.Add(quantityOfRulesTestedColumn)
|
||||
}
|
||||
|
||||
genomesContainer.Add(viewDetailsButtonsColumn)
|
||||
genomesContainer.Add(layout.NewSpacer())
|
||||
|
||||
page := container.NewVBox(title, backButton, widget.NewSeparator(), descriptionSection, widget.NewSeparator(), traitNameRow, widget.NewSeparator(), genomesContainer)
|
||||
|
||||
|
|
@ -2153,9 +2362,9 @@ func setViewCoupleGeneticAnalysisTraitDetailsPage(window fyne.Window, person1Nam
|
|||
}
|
||||
|
||||
|
||||
func setViewCoupleGeneticAnalysisTraitGenomePairDetailsPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, genomePairIdentifier [32]byte, genomePairName string, previousPage func()){
|
||||
func setViewCoupleGeneticAnalysisDiscreteTraitGenomePairDetailsPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, genomePairIdentifier [32]byte, genomePairName string, previousPage func()){
|
||||
|
||||
currentPage := func(){setViewCoupleGeneticAnalysisTraitGenomePairDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, previousPage)}
|
||||
currentPage := func(){setViewCoupleGeneticAnalysisDiscreteTraitGenomePairDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("Viewing Couple Genome Pair Info")
|
||||
|
||||
|
|
@ -2177,26 +2386,30 @@ func setViewCoupleGeneticAnalysisTraitGenomePairDetailsPage(window fyne.Window,
|
|||
})
|
||||
genomePairRow := container.NewHBox(layout.NewSpacer(), genomePairLabel, genomePairNameLabel, genomePairHelpButton, layout.NewSpacer())
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabel1 := widget.NewLabel("")
|
||||
personNameLabel := getItalicLabelCentered("Person Name")
|
||||
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
emptyLabel2 := widget.NewLabel("")
|
||||
genomeNameLabel := getItalicLabelCentered("Genome Name")
|
||||
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
outcomeScoresLabel := getItalicLabelCentered("Outcome Scores")
|
||||
emptyLabel3 := widget.NewLabel("")
|
||||
predictedOutcomeLabel := getItalicLabelCentered("Predicted Outcome")
|
||||
|
||||
numberOfLabel := getItalicLabelCentered("Number Of")
|
||||
quantityOfLabel1 := getItalicLabelCentered("Quantity Of")
|
||||
lociKnownLabel := getItalicLabelCentered("Loci Known")
|
||||
|
||||
quantityOfLabel2 := getItalicLabelCentered("Quantity Of")
|
||||
rulesTestedLabel := getItalicLabelCentered("Rules Tested")
|
||||
|
||||
emptyLabelD := widget.NewLabel("")
|
||||
emptyLabelE := widget.NewLabel("")
|
||||
emptyLabel4 := widget.NewLabel("")
|
||||
emptyLabel5 := widget.NewLabel("")
|
||||
|
||||
personNameColumn := container.NewVBox(emptyLabelA, personNameLabel, widget.NewSeparator())
|
||||
genomeNameColumn := container.NewVBox(emptyLabelB, genomeNameLabel, widget.NewSeparator())
|
||||
outcomeScoresColumn := container.NewVBox(emptyLabelC, outcomeScoresLabel, widget.NewSeparator())
|
||||
numberOfRulesTestedColumn := container.NewVBox(numberOfLabel, rulesTestedLabel, widget.NewSeparator())
|
||||
viewGenomeButtonsColumn := container.NewVBox(emptyLabelD, emptyLabelE, widget.NewSeparator())
|
||||
personNameColumn := container.NewVBox(emptyLabel1, personNameLabel, widget.NewSeparator())
|
||||
genomeNameColumn := container.NewVBox(emptyLabel2, genomeNameLabel, widget.NewSeparator())
|
||||
predictedOutcomeColumn := container.NewVBox(emptyLabel3, predictedOutcomeLabel, widget.NewSeparator())
|
||||
quantityOfLociKnownColumn := container.NewVBox(quantityOfLabel1, lociKnownLabel, widget.NewSeparator())
|
||||
quantityOfRulesTestedColumn := container.NewVBox(quantityOfLabel2, rulesTestedLabel, widget.NewSeparator())
|
||||
viewGenomeButtonsColumn := container.NewVBox(emptyLabel4, emptyLabel5, widget.NewSeparator())
|
||||
|
||||
addGenomeRow := func(isPerson1 bool, personName string, inputGenomeIdentifier [16]byte)error{
|
||||
|
||||
|
|
@ -2238,68 +2451,103 @@ func setViewCoupleGeneticAnalysisTraitGenomePairDetailsPage(window fyne.Window,
|
|||
|
||||
genomeNameLabel := getBoldLabelCentered(genomeName)
|
||||
|
||||
// We add all of the columns except for the trait rule column, which may be multiple rows high
|
||||
|
||||
_, anyTraitRuleTested, outcomeScoresMap, numberOfRulesTested, _, err := readGeneticAnalysis.GetPersonTraitInfoFromGeneticAnalysis(personAnalysisObject, traitName, personAnalysisGenomeIdentifier)
|
||||
neuralNetworkExists, neuralNetworkAnalysisExists, neuralNetworkPredictedOutcome, _, neuralNetworkQuantityOfLociTested, _, _, rulesAnalysisExists, _, rulesPredictedOutcomeExists, rulesPredictedOutcome, quantityOfRulesTested, _, _, err := readGeneticAnalysis.GetPersonDiscreteTraitInfoFromGeneticAnalysis(personAnalysisObject, traitName, personAnalysisGenomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
|
||||
numberOfRulesTestedString := helpers.ConvertIntToString(numberOfRulesTested)
|
||||
numberOfRulesTestedText := getBoldLabelCentered(numberOfRulesTestedString)
|
||||
|
||||
viewGenomeButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
setViewPersonGenomeTraitRulesPage(window, personAnalysisObject, traitName, personAnalysisGenomeIdentifier, genomeName, currentPage)
|
||||
})
|
||||
|
||||
personNameColumn.Add(personNameLabel)
|
||||
genomeNameColumn.Add(genomeNameLabel)
|
||||
numberOfRulesTestedColumn.Add(numberOfRulesTestedText)
|
||||
viewGenomeButtonsColumn.Add(viewGenomeButton)
|
||||
|
||||
if (anyTraitRuleTested == false){
|
||||
//Outputs:
|
||||
// -bool: Outcome is known
|
||||
// -string: Prediction outcome
|
||||
getPredictedOutcome := func()(bool, string){
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
unknownTranslated := translate("Unknown")
|
||||
unknownLabel := getBoldLabelCentered(unknownTranslated)
|
||||
if (neuralNetworkAnalysisExists == false){
|
||||
return false, ""
|
||||
}
|
||||
|
||||
outcomeScoresColumn.Add(unknownLabel)
|
||||
return true, neuralNetworkPredictedOutcome
|
||||
}
|
||||
|
||||
// Analysis must be rule-based
|
||||
if (rulesAnalysisExists == false || rulesPredictedOutcomeExists == false){
|
||||
return false, ""
|
||||
}
|
||||
|
||||
return true, rulesPredictedOutcome
|
||||
}
|
||||
|
||||
predictedOutcomeExists, predictedOutcome := getPredictedOutcome()
|
||||
if (predictedOutcomeExists == false){
|
||||
unknownLabel := getItalicLabelCentered(translate("Unknown"))
|
||||
predictedOutcomeColumn.Add(unknownLabel)
|
||||
} else {
|
||||
predictedOutcomeLabel := getBoldLabelCentered(predictedOutcome)
|
||||
predictedOutcomeColumn.Add(predictedOutcomeLabel)
|
||||
}
|
||||
|
||||
// Now we add outcome details
|
||||
|
||||
traitObject, err := traits.GetTraitObject(traitName)
|
||||
if (err != nil) { return err }
|
||||
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
if (traitIsDiscreteOrNumeric != "Discrete"){
|
||||
return errors.New("setViewCoupleGeneticAnalysisDiscreteTraitGenomePairDetailsPage called with non-discrete trait: " + traitName)
|
||||
}
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
traitLociList := traitObject.LociList
|
||||
|
||||
totalQuantityOfLoci := len(traitLociList)
|
||||
|
||||
quantityOfLociKnownString := helpers.ConvertIntToString(neuralNetworkQuantityOfLociTested)
|
||||
totalQuantityOfLociString := helpers.ConvertIntToString(totalQuantityOfLoci)
|
||||
|
||||
quantityOfLociKnownFormatted := quantityOfLociKnownString + "/" + totalQuantityOfLociString
|
||||
|
||||
quantityOfLociKnownLabel := getBoldLabelCentered(quantityOfLociKnownFormatted)
|
||||
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownLabel)
|
||||
|
||||
} else {
|
||||
|
||||
outcomeNamesList := helpers.GetListOfMapKeys(outcomeScoresMap)
|
||||
// Analysis is rule-based
|
||||
|
||||
// We have to sort the outcome names so they always show up in the same order
|
||||
helpers.SortStringListToUnicodeOrder(outcomeNamesList)
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
for index, outcomeName := range outcomeNamesList{
|
||||
totalQuantityOfRules := len(traitRulesList)
|
||||
|
||||
outcomeScore, exists := outcomeScoresMap[outcomeName]
|
||||
if (exists == false){
|
||||
return errors.New("Outcome name not found in outcome scores map after being found already.")
|
||||
}
|
||||
quantityOfRulesTestedString := helpers.ConvertIntToString(quantityOfRulesTested)
|
||||
totalQuantityOfRulesString := helpers.ConvertIntToString(totalQuantityOfRules)
|
||||
|
||||
outcomeScoreString := helpers.ConvertIntToString(outcomeScore)
|
||||
quantityOfRulesTestedFormatted := quantityOfRulesTestedString + "/" + totalQuantityOfRulesString
|
||||
|
||||
outcomeRow := getBoldLabelCentered(outcomeName + ": " + outcomeScoreString)
|
||||
outcomeScoresColumn.Add(outcomeRow)
|
||||
quantityOfRulesTestedLabel := getBoldLabelCentered(quantityOfRulesTestedFormatted)
|
||||
|
||||
if (index > 0){
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
emptyLabelD := widget.NewLabel("")
|
||||
|
||||
personNameColumn.Add(emptyLabelA)
|
||||
genomeNameColumn.Add(emptyLabelB)
|
||||
numberOfRulesTestedColumn.Add(emptyLabelC)
|
||||
viewGenomeButtonsColumn.Add(emptyLabelD)
|
||||
}
|
||||
}
|
||||
quantityOfRulesTestedColumn.Add(quantityOfRulesTestedLabel)
|
||||
}
|
||||
|
||||
viewGenomeButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
} else {
|
||||
setViewPersonGenomeDiscreteTraitRulesPage(window, personAnalysisObject, traitName, personAnalysisGenomeIdentifier, genomeName, currentPage)
|
||||
}
|
||||
})
|
||||
|
||||
viewGenomeButtonsColumn.Add(viewGenomeButton)
|
||||
|
||||
personNameColumn.Add(widget.NewSeparator())
|
||||
genomeNameColumn.Add(widget.NewSeparator())
|
||||
outcomeScoresColumn.Add(widget.NewSeparator())
|
||||
numberOfRulesTestedColumn.Add(widget.NewSeparator())
|
||||
predictedOutcomeColumn.Add(widget.NewSeparator())
|
||||
quantityOfLociKnownColumn.Add(widget.NewSeparator())
|
||||
quantityOfRulesTestedColumn.Add(widget.NewSeparator())
|
||||
viewGenomeButtonsColumn.Add(widget.NewSeparator())
|
||||
|
||||
return nil
|
||||
|
|
@ -2318,19 +2566,44 @@ func setViewCoupleGeneticAnalysisTraitGenomePairDetailsPage(window fyne.Window,
|
|||
return
|
||||
}
|
||||
|
||||
outcomeScoresHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringTraitOutcomeScoresExplainerPage(window, currentPage)
|
||||
neuralNetworkExists, _ := geneticPredictionModels.GetGeneticPredictionModelBytes(traitName)
|
||||
|
||||
predictedOutcomeHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
setDiscreteTraitNeuralNetworkPredictionExplainerPage(window, currentPage)
|
||||
} else {
|
||||
setOffspringDiscreteTraitNeuralNetworkPredictionExplainerPage(window, currentPage)
|
||||
}
|
||||
})
|
||||
|
||||
outcomeScoresColumn.Add(outcomeScoresHelpButton)
|
||||
predictedOutcomeColumn.Add(predictedOutcomeHelpButton)
|
||||
|
||||
quantityOfLociKnownHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownHelpButton)
|
||||
|
||||
numberOfRulesTestedHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringTraitNumberOfRulesTestedExplainerPage(window, currentPage)
|
||||
setOffspringDiscreteTraitQuantityOfRulesTestedExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
numberOfRulesTestedColumn.Add(numberOfRulesTestedHelpButton)
|
||||
quantityOfRulesTestedColumn.Add(numberOfRulesTestedHelpButton)
|
||||
|
||||
genomesGrid := container.NewHBox(layout.NewSpacer(), personNameColumn, genomeNameColumn, outcomeScoresColumn, numberOfRulesTestedColumn, viewGenomeButtonsColumn, layout.NewSpacer())
|
||||
genomesGrid := container.NewHBox(layout.NewSpacer(), personNameColumn, genomeNameColumn, predictedOutcomeColumn)
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
genomesGrid.Add(quantityOfLociKnownColumn)
|
||||
} else {
|
||||
|
||||
genomesGrid.Add(quantityOfRulesTestedColumn)
|
||||
}
|
||||
|
||||
genomesGrid.Add(viewGenomeButtonsColumn)
|
||||
genomesGrid.Add(layout.NewSpacer())
|
||||
|
||||
page := container.NewVBox(title, backButton, widget.NewSeparator(), description, widget.NewSeparator(), traitNameRow, widget.NewSeparator(), genomePairRow, widget.NewSeparator(), genomesGrid)
|
||||
|
||||
|
|
@ -2338,13 +2611,12 @@ func setViewCoupleGeneticAnalysisTraitGenomePairDetailsPage(window fyne.Window,
|
|||
}
|
||||
|
||||
|
||||
|
||||
// This function provides a page to view the couple offspring rule probabilities for a particular genome pair
|
||||
func setViewCoupleTraitRulesPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, genomePairIdentifier [32]byte, genomePairName string, previousPage func()){
|
||||
func setViewCoupleDiscreteTraitRulesPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, genomePairIdentifier [32]byte, genomePairName string, previousPage func()){
|
||||
|
||||
setLoadingScreen(window, "Loading Trait Rules", "Loading trait rules...")
|
||||
|
||||
currentPage := func(){setViewCoupleTraitRulesPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, previousPage)}
|
||||
currentPage := func(){setViewCoupleDiscreteTraitRulesPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("View Offspring Trait Rules - " + traitName)
|
||||
|
||||
|
|
@ -2352,25 +2624,33 @@ func setViewCoupleTraitRulesPage(window fyne.Window, person1Name string, person2
|
|||
|
||||
description1 := widget.NewLabel("Below are the trait rule probabilities for offspring from this genome pair.")
|
||||
traitRulesHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringTraitRulesExplainerPage(window, currentPage)
|
||||
setOffspringDiscreteTraitRulesExplainerPage(window, currentPage)
|
||||
})
|
||||
description1Row := container.NewHBox(layout.NewSpacer(), description1, traitRulesHelpButton, layout.NewSpacer())
|
||||
|
||||
genomePairLabel := widget.NewLabel("Genome Pair:")
|
||||
genomePairNameLabel := getBoldLabel(genomePairName)
|
||||
viewGenomePairInfoButton := widget.NewButtonWithIcon("", theme.InfoIcon(), func(){
|
||||
setViewCoupleGeneticAnalysisTraitGenomePairDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, currentPage)
|
||||
setViewCoupleGeneticAnalysisDiscreteTraitGenomePairDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, currentPage)
|
||||
})
|
||||
|
||||
genomePairRow := container.NewHBox(layout.NewSpacer(), genomePairLabel, genomePairNameLabel, viewGenomePairInfoButton, layout.NewSpacer())
|
||||
|
||||
_, _, numberOfRulesTested, _, err := readGeneticAnalysis.GetOffspringTraitInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, genomePairIdentifier)
|
||||
neuralNetworkExists, _, _, _, _, _, anyRulesExist, rulesAnalysisExists, _, _, quantityOfRulesTested, _, _, err := readGeneticAnalysis.GetOffspringDiscreteTraitInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, genomePairIdentifier)
|
||||
if (err != nil){
|
||||
setErrorEncounteredPage(window, err, previousPage)
|
||||
return
|
||||
}
|
||||
if (neuralNetworkExists == true){
|
||||
setErrorEncounteredPage(window, errors.New("setViewCoupleTraitRulesPage called when neural network analysis for trait exists."), previousPage)
|
||||
return
|
||||
}
|
||||
if (anyRulesExist == false){
|
||||
setErrorEncounteredPage(window, errors.New("GetOffspringTraitInfoFromGeneticAnalysis claiming that no analysis method exists for triat: " + traitName), previousPage)
|
||||
return
|
||||
}
|
||||
|
||||
numberOfRulesTestedString := helpers.ConvertIntToString(numberOfRulesTested)
|
||||
quantityOfRulesTestedString := helpers.ConvertIntToString(quantityOfRulesTested)
|
||||
|
||||
traitRulesMap, err := traits.GetTraitRulesMap(traitName)
|
||||
if (err != nil){
|
||||
|
|
@ -2382,9 +2662,9 @@ func setViewCoupleTraitRulesPage(window fyne.Window, person1Name string, person2
|
|||
totalNumberOfRulesString := helpers.ConvertIntToString(totalNumberOfRules)
|
||||
|
||||
rulesTestedLabel := widget.NewLabel("Rules Tested:")
|
||||
rulesTestedText := getBoldLabel(numberOfRulesTestedString + "/" + totalNumberOfRulesString)
|
||||
rulesTestedText := getBoldLabel(quantityOfRulesTestedString + "/" + totalNumberOfRulesString)
|
||||
rulesTestedHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringTraitNumberOfRulesTestedExplainerPage(window, currentPage)
|
||||
setOffspringDiscreteTraitQuantityOfRulesTestedExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
rulesTestedRow := container.NewHBox(layout.NewSpacer(), rulesTestedLabel, rulesTestedText, rulesTestedHelpButton, layout.NewSpacer())
|
||||
|
|
@ -2415,25 +2695,33 @@ func setViewCoupleTraitRulesPage(window fyne.Window, person1Name string, person2
|
|||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil) { return err }
|
||||
|
||||
offspringRuleProbabilityKnown, _, offspringProbabilityOfPassingRuleFormatted, err := readGeneticAnalysis.GetOffspringTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, ruleIdentifier, genomePairIdentifier)
|
||||
if (err != nil) { return err }
|
||||
getProbabilityOfPassingRuleText := func()(string, error){
|
||||
|
||||
viewRuleDetailsButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
setViewCoupleGeneticAnalysisTraitRuleDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, ruleIdentifier, currentPage)
|
||||
})
|
||||
if (rulesAnalysisExists == false){
|
||||
// No rules were tested
|
||||
result := translate("Unknown")
|
||||
return result, nil
|
||||
}
|
||||
|
||||
getProbabilityOfPassingRuleText := func()string{
|
||||
offspringRuleProbabilityKnown, _, offspringProbabilityOfPassingRuleFormatted, err := readGeneticAnalysis.GetOffspringDiscreteTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, ruleIdentifier, genomePairIdentifier)
|
||||
if (err != nil) { return "", err }
|
||||
if (offspringRuleProbabilityKnown == false){
|
||||
|
||||
result := translate("Unknown")
|
||||
return result
|
||||
return result, nil
|
||||
}
|
||||
return offspringProbabilityOfPassingRuleFormatted
|
||||
|
||||
return offspringProbabilityOfPassingRuleFormatted, nil
|
||||
}
|
||||
|
||||
probabilityOfPassingRuleText := getProbabilityOfPassingRuleText()
|
||||
probabilityOfPassingRuleText, err := getProbabilityOfPassingRuleText()
|
||||
if (err != nil) { return err }
|
||||
probabilityOfPassingRuleTextLabel := getBoldLabelCentered(probabilityOfPassingRuleText)
|
||||
|
||||
viewRuleDetailsButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
setViewCoupleGeneticAnalysisDiscreteTraitRuleDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, ruleIdentifier, currentPage)
|
||||
})
|
||||
|
||||
// We add all of the columns except for the rule effects column
|
||||
// We do this because the rule effects column may be multiple rows tall
|
||||
|
||||
|
|
@ -2504,7 +2792,7 @@ func setViewCoupleTraitRulesPage(window fyne.Window, person1Name string, person2
|
|||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
offspringRuleProbabilityKnown, _, _, err := readGeneticAnalysis.GetOffspringTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, ruleIdentifier, genomePairIdentifier)
|
||||
offspringRuleProbabilityKnown, _, _, err := readGeneticAnalysis.GetOffspringDiscreteTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, ruleIdentifier, genomePairIdentifier)
|
||||
if (err != nil) { return nil, err }
|
||||
if (offspringRuleProbabilityKnown == true){
|
||||
rulesWithKnownProbabilityList = append(rulesWithKnownProbabilityList, ruleIdentifierHex)
|
||||
|
|
@ -2531,7 +2819,7 @@ func setViewCoupleTraitRulesPage(window fyne.Window, person1Name string, person2
|
|||
}
|
||||
|
||||
ruleEffectsHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitRuleOutcomeEffectsExplainerPage(window, currentPage)
|
||||
setDiscreteTraitRuleOutcomeEffectsExplainerPage(window, currentPage)
|
||||
})
|
||||
ruleEffectsColumn.Add(ruleEffectsHelpButton)
|
||||
|
||||
|
|
@ -2560,9 +2848,9 @@ func setViewCoupleTraitRulesPage(window fyne.Window, person1Name string, person2
|
|||
|
||||
// This function implements a page to view the details of a specific rule from a genetic analysis
|
||||
// It will show the rule details for all of the couple's genome pairs
|
||||
func setViewCoupleGeneticAnalysisTraitRuleDetailsPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, ruleIdentifier [3]byte, previousPage func()){
|
||||
func setViewCoupleGeneticAnalysisDiscreteTraitRuleDetailsPage(window fyne.Window, person1Name string, person2Name string, person1AnalysisObject geneticAnalysis.PersonAnalysis, person2AnalysisObject geneticAnalysis.PersonAnalysis, coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, ruleIdentifier [3]byte, previousPage func()){
|
||||
|
||||
currentPage := func(){setViewCoupleGeneticAnalysisTraitRuleDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, ruleIdentifier, previousPage)}
|
||||
currentPage := func(){setViewCoupleGeneticAnalysisDiscreteTraitRuleDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, ruleIdentifier, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("Trait Rule Details - " + traitName)
|
||||
|
||||
|
|
@ -2575,7 +2863,7 @@ func setViewCoupleGeneticAnalysisTraitRuleDetailsPage(window fyne.Window, person
|
|||
ruleIdentifierLabel := widget.NewLabel("Rule Identifier:")
|
||||
ruleIdentifierText := getBoldLabel(ruleIdentifierHex)
|
||||
ruleInfoButton := widget.NewButtonWithIcon("", theme.InfoIcon(), func(){
|
||||
setViewTraitRuleDetailsPage(window, traitName, ruleIdentifierHex, currentPage)
|
||||
setViewDiscreteTraitRuleDetailsPage(window, traitName, ruleIdentifierHex, currentPage)
|
||||
})
|
||||
ruleIdentifierRow := container.NewHBox(layout.NewSpacer(), ruleIdentifierLabel, ruleIdentifierText, ruleInfoButton, layout.NewSpacer())
|
||||
|
||||
|
|
@ -2596,7 +2884,7 @@ func setViewCoupleGeneticAnalysisTraitRuleDetailsPage(window fyne.Window, person
|
|||
|
||||
addGenomePairRow := func(genomePairName string, genomePairIdentifier [32]byte)error{
|
||||
|
||||
offspringRuleProbabilityKnown, _, offspringProbabilityOfPassingRuleFormatted, err := readGeneticAnalysis.GetOffspringTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, ruleIdentifier, genomePairIdentifier)
|
||||
offspringRuleProbabilityKnown, _, offspringProbabilityOfPassingRuleFormatted, err := readGeneticAnalysis.GetOffspringDiscreteTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, ruleIdentifier, genomePairIdentifier)
|
||||
if (err != nil) { return err }
|
||||
|
||||
getOffspringProbabilityOfPassingRuleText := func()string{
|
||||
|
|
@ -2612,7 +2900,7 @@ func setViewCoupleGeneticAnalysisTraitRuleDetailsPage(window fyne.Window, person
|
|||
offspringProbabilityOfPassingRuleText := getOffspringProbabilityOfPassingRuleText()
|
||||
|
||||
viewGenomePairInfoButton := widget.NewButtonWithIcon("", theme.InfoIcon(), func(){
|
||||
setViewCoupleGeneticAnalysisTraitGenomePairDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, currentPage)
|
||||
setViewCoupleGeneticAnalysisDiscreteTraitGenomePairDetailsPage(window, person1Name, person2Name, person1AnalysisObject, person2AnalysisObject, coupleAnalysisObject, traitName, genomePairIdentifier, genomePairName, currentPage)
|
||||
})
|
||||
|
||||
genomePairNameLabel := getBoldLabelCentered(genomePairName)
|
||||
|
|
|
|||
|
|
@ -13,6 +13,7 @@ import "fyne.io/fyne/v2/layout"
|
|||
import "fyne.io/fyne/v2/theme"
|
||||
import "fyne.io/fyne/v2/widget"
|
||||
|
||||
import "seekia/resources/geneticPredictionModels"
|
||||
import "seekia/resources/geneticReferences/monogenicDiseases"
|
||||
import "seekia/resources/geneticReferences/polygenicDiseases"
|
||||
import "seekia/resources/geneticReferences/traits"
|
||||
|
|
@ -70,11 +71,15 @@ func setViewPersonGeneticAnalysisPage(window fyne.Window, personIdentifier strin
|
|||
polygenicDiseasesButton := widget.NewButton("Polygenic Diseases", func(){
|
||||
setViewPersonGeneticAnalysisPolygenicDiseasesPage(window, personIdentifier, analysisObject, currentPage)
|
||||
})
|
||||
traitsButton := widget.NewButton("Traits", func(){
|
||||
setViewPersonGeneticAnalysisTraitsPage(window, personIdentifier, analysisObject, currentPage)
|
||||
discreteTraitsButton := widget.NewButton("Discrete Traits", func(){
|
||||
setViewPersonGeneticAnalysisDiscreteTraitsPage(window, personIdentifier, analysisObject, currentPage)
|
||||
})
|
||||
numericTraitsButton := widget.NewButton("Numeric Traits", func(){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
|
||||
categoryButtonsGrid := getContainerCentered(container.NewGridWithColumns(1, generalButton, monogenicDiseasesButton, polygenicDiseasesButton, traitsButton))
|
||||
categoryButtonsGrid := getContainerCentered(container.NewGridWithColumns(1, generalButton, monogenicDiseasesButton, polygenicDiseasesButton, discreteTraitsButton, numericTraitsButton))
|
||||
|
||||
page := container.NewVBox(title, backButton, widget.NewSeparator(), warningLabel1, warningLabel2, widget.NewSeparator(), personNameRow, numberOfAnalyzedGenomesRow, widget.NewSeparator(), categoryButtonsGrid)
|
||||
|
||||
|
|
@ -94,7 +99,7 @@ func setViewPersonGeneticAnalysisMonogenicDiseasesPage(window fyne.Window, analy
|
|||
|
||||
getMonogenicDiseasesContainer := func()(*fyne.Container, error){
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, _, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
if (err != nil){ return nil, err }
|
||||
|
||||
// Outputs:
|
||||
|
|
@ -241,7 +246,7 @@ func setViewPersonGeneticAnalysisMonogenicDiseaseDetailsPage(window fyne.Window,
|
|||
|
||||
backButton := getBackButtonCentered(previousPage)
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
if (err != nil) {
|
||||
setErrorEncounteredPage(window, err, previousPage)
|
||||
return
|
||||
|
|
@ -280,8 +285,6 @@ func setViewPersonGeneticAnalysisMonogenicDiseaseDetailsPage(window fyne.Window,
|
|||
totalNumberOfVariants := len(diseaseVariantsMap)
|
||||
totalNumberOfVariantsString := helpers.ConvertIntToString(totalNumberOfVariants)
|
||||
|
||||
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
genomeNameLabel := getItalicLabelCentered("Genome Name")
|
||||
|
||||
|
|
@ -736,7 +739,7 @@ func setViewPersonGeneticAnalysisMonogenicDiseaseVariantDetailsPage(window fyne.
|
|||
|
||||
getGenomesHaveVariantGrid := func()(*fyne.Container, error){
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(geneticAnalysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(geneticAnalysisObject)
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
genomeNameLabel := getItalicLabelCentered("Genome Name")
|
||||
|
|
@ -894,7 +897,7 @@ func setViewPersonGeneticAnalysisPolygenicDiseasesPage(window fyne.Window, perso
|
|||
|
||||
getPolygenicDiseasesContainer := func()(*fyne.Container, error){
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, _, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
if (err != nil){ return nil, err }
|
||||
|
||||
// Outputs:
|
||||
|
|
@ -935,7 +938,7 @@ func setViewPersonGeneticAnalysisPolygenicDiseasesPage(window fyne.Window, perso
|
|||
|
||||
diseaseNameText := getBoldLabelCentered(diseaseName)
|
||||
|
||||
personRiskScoreKnown, _, personRiskScoreFormatted, _, _, conflictExists, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(analysisObject, diseaseName, mainGenomeIdentifier)
|
||||
personRiskScoreKnown, _, personRiskScoreFormatted, _, conflictExists, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(analysisObject, diseaseName, mainGenomeIdentifier)
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
getPersonRiskScoreLabelText := func()string{
|
||||
|
|
@ -1015,7 +1018,7 @@ func setViewPersonGeneticAnalysisPolygenicDiseaseDetailsPage(window fyne.Window,
|
|||
|
||||
backButton := getBackButtonCentered(previousPage)
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
if (err != nil) {
|
||||
setErrorEncounteredPage(window, err, previousPage)
|
||||
return
|
||||
|
|
@ -1054,7 +1057,6 @@ func setViewPersonGeneticAnalysisPolygenicDiseaseDetailsPage(window fyne.Window,
|
|||
totalNumberOfLoci := len(diseaseLociMap)
|
||||
totalNumberOfLociString := helpers.ConvertIntToString(totalNumberOfLoci)
|
||||
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
genomeNameLabel := getItalicLabelCentered("Genome Name")
|
||||
|
||||
|
|
@ -1096,7 +1098,7 @@ func setViewPersonGeneticAnalysisPolygenicDiseaseDetailsPage(window fyne.Window,
|
|||
|
||||
genomeNameCell := getGenomeNameCell()
|
||||
|
||||
diseaseRiskScoreKnown, _, diseaseRiskScoreFormatted, _, numberOfLociTested, _, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(analysisObject, diseaseName, genomeIdentifier)
|
||||
diseaseRiskScoreKnown, _, diseaseRiskScoreFormatted, numberOfLociTested, _, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(analysisObject, diseaseName, genomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
|
||||
getRiskScoreLabelText := func()string{
|
||||
|
|
@ -1622,7 +1624,7 @@ func setViewPersonGeneticAnalysisPolygenicDiseaseLocusDetailsPage(window fyne.Wi
|
|||
|
||||
getGenomesLocusInfoGrid := func()(*fyne.Container, error){
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(geneticAnalysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(geneticAnalysisObject)
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
genomeNameLabel := getItalicLabelCentered("Genome Name")
|
||||
|
|
@ -1765,19 +1767,19 @@ func setViewPersonGeneticAnalysisPolygenicDiseaseLocusDetailsPage(window fyne.Wi
|
|||
}
|
||||
|
||||
|
||||
func setViewPersonGeneticAnalysisTraitsPage(window fyne.Window, personIdentifier string, analysisObject geneticAnalysis.PersonAnalysis, previousPage func()){
|
||||
func setViewPersonGeneticAnalysisDiscreteTraitsPage(window fyne.Window, personIdentifier string, analysisObject geneticAnalysis.PersonAnalysis, previousPage func()){
|
||||
|
||||
currentPage := func(){setViewPersonGeneticAnalysisTraitsPage(window, personIdentifier, analysisObject, previousPage)}
|
||||
currentPage := func(){setViewPersonGeneticAnalysisDiscreteTraitsPage(window, personIdentifier, analysisObject, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("Viewing Genetic Analysis - Traits")
|
||||
title := getPageTitleCentered("Viewing Genetic Analysis - Discrete Traits")
|
||||
|
||||
backButton := getBackButtonCentered(previousPage)
|
||||
|
||||
description := getLabelCentered("Below is an analysis of the traits for this person's genome.")
|
||||
description := getLabelCentered("Below is an analysis of the discrete traits for this person's genome.")
|
||||
|
||||
getTraitsContainer := func()(*fyne.Container, error){
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, _, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
if (err != nil){ return nil, err }
|
||||
|
||||
// Outputs:
|
||||
|
|
@ -1798,102 +1800,154 @@ func setViewPersonGeneticAnalysisTraitsPage(window fyne.Window, personIdentifier
|
|||
mainGenomeIdentifier, err := getMainGenomeIdentifier()
|
||||
if (err != nil){ return nil, err }
|
||||
|
||||
emptyLabel1 := widget.NewLabel("")
|
||||
traitNameLabel := getItalicLabelCentered("Trait Name")
|
||||
|
||||
outcomeScoresLabel := getItalicLabelCentered("Outcome Scores")
|
||||
emptyLabel2 := widget.NewLabel("")
|
||||
predictedOutcomeLabel := getItalicLabelCentered("Predicted Outcome")
|
||||
|
||||
quantityOfLabel := getItalicLabelCentered("Quantity Of")
|
||||
lociKnownLabel := getItalicLabelCentered("Loci Known")
|
||||
|
||||
emptyLabel3 := widget.NewLabel("")
|
||||
conflictExistsLabel := getItalicLabelCentered("Conflict Exists?")
|
||||
|
||||
emptyLabel := widget.NewLabel("")
|
||||
emptyLabel4 := widget.NewLabel("")
|
||||
emptyLabel5 := widget.NewLabel("")
|
||||
|
||||
traitNameColumn := container.NewVBox(traitNameLabel, widget.NewSeparator())
|
||||
outcomeScoresColumn := container.NewVBox(outcomeScoresLabel, widget.NewSeparator())
|
||||
conflictExistsColumn := container.NewVBox(conflictExistsLabel, widget.NewSeparator())
|
||||
viewButtonsColumn := container.NewVBox(emptyLabel, widget.NewSeparator())
|
||||
traitNameColumn := container.NewVBox(emptyLabel1, traitNameLabel, widget.NewSeparator())
|
||||
predictedOutcomeColumn := container.NewVBox(emptyLabel2, predictedOutcomeLabel, widget.NewSeparator())
|
||||
quantityOfLociKnownColumn := container.NewVBox(quantityOfLabel, lociKnownLabel, widget.NewSeparator())
|
||||
conflictExistsColumn := container.NewVBox(emptyLabel3, conflictExistsLabel, widget.NewSeparator())
|
||||
viewButtonsColumn := container.NewVBox(emptyLabel4, emptyLabel5, widget.NewSeparator())
|
||||
|
||||
traitObjectsList, err := traits.GetTraitObjectsList()
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
for _, traitObject := range traitObjectsList{
|
||||
|
||||
traitName := traitObject.TraitName
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
if (len(traitRulesList) == 0){
|
||||
// This trait does not have any rules
|
||||
// We cannot analyze it yet
|
||||
// We will add neural network prediction so we can predict these traits
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
if (traitIsDiscreteOrNumeric != "Discrete"){
|
||||
continue
|
||||
}
|
||||
traitOutcomeNamesList := traitObject.OutcomesList
|
||||
|
||||
_, anyTraitRuleTested, outcomeScoresMap, _, conflictExists, err := readGeneticAnalysis.GetPersonTraitInfoFromGeneticAnalysis(analysisObject, traitName, mainGenomeIdentifier)
|
||||
traitName := traitObject.TraitName
|
||||
traitLociList := traitObject.LociList
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
if (len(traitLociList) == 0 && len(traitRulesList) == 0){
|
||||
// This trait does not have any rules or loci to analyze
|
||||
// We cannot analyze it yet
|
||||
continue
|
||||
}
|
||||
|
||||
traitNameText := getBoldLabelCentered(traitName)
|
||||
|
||||
neuralNetworkExists, neuralNetworkAnalysisExists, neuralNetworkPredictedOutcome, _, quantityOfLociKnown_NeuralNetwork, _, anyRulesExist, rulesAnalysisExists, _, rulesPredictedOutcomeExists, rulesPredictedOutcome, _, quantityOfLociKnown_Rules, conflictExists, err := readGeneticAnalysis.GetPersonDiscreteTraitInfoFromGeneticAnalysis(analysisObject, traitName, mainGenomeIdentifier)
|
||||
if (err != nil) { return nil, err }
|
||||
if (neuralNetworkExists == false && anyRulesExist == false){
|
||||
// We can't analyze this trait
|
||||
continue
|
||||
}
|
||||
|
||||
// We add all of the columns except for the trait outcomes column, which may be multiple rows high
|
||||
getPredictionLabel := func()fyne.Widget{
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
if (neuralNetworkAnalysisExists == false){
|
||||
result := getItalicLabel("Unknown")
|
||||
return result
|
||||
}
|
||||
|
||||
result := getBoldLabel(neuralNetworkPredictedOutcome)
|
||||
|
||||
return result
|
||||
}
|
||||
// anyRulesExist must be true
|
||||
|
||||
if (rulesAnalysisExists == false || rulesPredictedOutcomeExists == false){
|
||||
result := getItalicLabel("Unknown")
|
||||
return result
|
||||
}
|
||||
|
||||
result := getBoldLabel(rulesPredictedOutcome)
|
||||
|
||||
return result
|
||||
}
|
||||
|
||||
predictionLabel := getPredictionLabel()
|
||||
|
||||
predictionLabelCentered := getWidgetCentered(predictionLabel)
|
||||
|
||||
getQuantityOfLociKnown := func()int{
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
return quantityOfLociKnown_NeuralNetwork
|
||||
}
|
||||
return quantityOfLociKnown_Rules
|
||||
}
|
||||
|
||||
quantityOfLociKnown := getQuantityOfLociKnown()
|
||||
|
||||
getTotalQuantityOfLoci := func()int{
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
totalQuantityOfLoci := len(traitLociList)
|
||||
|
||||
return totalQuantityOfLoci
|
||||
}
|
||||
|
||||
traitLociList_Rules := traitObject.LociList_Rules
|
||||
|
||||
totalQuantityOfLoci := len(traitLociList_Rules)
|
||||
|
||||
return totalQuantityOfLoci
|
||||
}
|
||||
|
||||
totalQuantityOfLoci := getTotalQuantityOfLoci()
|
||||
|
||||
quantityOfLociKnownString := helpers.ConvertIntToString(quantityOfLociKnown)
|
||||
totalQuantityOfLociString := helpers.ConvertIntToString(totalQuantityOfLoci)
|
||||
|
||||
quantityOfLociKnownFormatted := quantityOfLociKnownString + "/" + totalQuantityOfLociString
|
||||
|
||||
quantityOfLociKnownLabel := getBoldLabelCentered(quantityOfLociKnownFormatted)
|
||||
|
||||
conflictExistsString := helpers.ConvertBoolToYesOrNoString(conflictExists)
|
||||
conflictExistsLabel := getBoldLabelCentered(conflictExistsString)
|
||||
|
||||
viewDetailsButton := getWidgetCentered(widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
setViewPersonGeneticAnalysisTraitDetailsPage(window, personIdentifier, analysisObject, traitName, currentPage)
|
||||
setViewPersonGeneticAnalysisDiscreteTraitDetailsPage(window, personIdentifier, analysisObject, traitName, currentPage)
|
||||
}))
|
||||
|
||||
traitNameText := getBoldLabelCentered(traitName)
|
||||
|
||||
traitNameColumn.Add(traitNameText)
|
||||
predictedOutcomeColumn.Add(predictionLabelCentered)
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownLabel)
|
||||
conflictExistsColumn.Add(conflictExistsLabel)
|
||||
viewButtonsColumn.Add(viewDetailsButton)
|
||||
|
||||
if (anyTraitRuleTested == false){
|
||||
|
||||
unknownTranslated := translate("Unknown")
|
||||
unknownLabel := getBoldLabelCentered(unknownTranslated)
|
||||
|
||||
outcomeScoresColumn.Add(unknownLabel)
|
||||
} else {
|
||||
|
||||
// We have to sort outcome names so they always show up in the same order
|
||||
|
||||
traitOutcomeNamesListSorted := helpers.CopyAndSortStringListToUnicodeOrder(traitOutcomeNamesList)
|
||||
|
||||
for index, outcomeName := range traitOutcomeNamesListSorted{
|
||||
|
||||
outcomeScore, exists := outcomeScoresMap[outcomeName]
|
||||
if (exists == false){
|
||||
return nil, errors.New("Outcome name not found in outcomeScoresMap: " + outcomeName)
|
||||
}
|
||||
|
||||
outcomeScoreString := helpers.ConvertIntToString(outcomeScore)
|
||||
|
||||
outcomeRow := getBoldLabelCentered(outcomeName + ": " + outcomeScoreString)
|
||||
outcomeScoresColumn.Add(outcomeRow)
|
||||
|
||||
if (index > 0){
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
|
||||
traitNameColumn.Add(emptyLabelA)
|
||||
conflictExistsColumn.Add(emptyLabelB)
|
||||
viewButtonsColumn.Add(emptyLabelC)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
traitNameColumn.Add(widget.NewSeparator())
|
||||
outcomeScoresColumn.Add(widget.NewSeparator())
|
||||
predictedOutcomeColumn.Add(widget.NewSeparator())
|
||||
quantityOfLociKnownColumn.Add(widget.NewSeparator())
|
||||
conflictExistsColumn.Add(widget.NewSeparator())
|
||||
viewButtonsColumn.Add(widget.NewSeparator())
|
||||
}
|
||||
|
||||
outcomeScoresHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitOutcomeScoresExplainerPage(window, currentPage)
|
||||
predictedOutcomeHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
outcomeScoresColumn.Add(outcomeScoresHelpButton)
|
||||
predictedOutcomeColumn.Add(predictedOutcomeHelpButton)
|
||||
|
||||
traitsContainer := container.NewHBox(layout.NewSpacer(), traitNameColumn, outcomeScoresColumn)
|
||||
quantityOfLociKnownHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownHelpButton)
|
||||
|
||||
traitsContainer := container.NewHBox(layout.NewSpacer(), traitNameColumn, predictedOutcomeColumn, quantityOfLociKnownColumn)
|
||||
|
||||
if (multipleGenomesExist == true){
|
||||
|
||||
|
|
@ -1923,16 +1977,15 @@ func setViewPersonGeneticAnalysisTraitsPage(window fyne.Window, personIdentifier
|
|||
}
|
||||
|
||||
|
||||
func setViewPersonGeneticAnalysisDiscreteTraitDetailsPage(window fyne.Window, personIdentifier string, analysisObject geneticAnalysis.PersonAnalysis, traitName string, previousPage func()){
|
||||
|
||||
func setViewPersonGeneticAnalysisTraitDetailsPage(window fyne.Window, personIdentifier string, analysisObject geneticAnalysis.PersonAnalysis, traitName string, previousPage func()){
|
||||
|
||||
currentPage := func(){setViewPersonGeneticAnalysisTraitDetailsPage(window, personIdentifier, analysisObject, traitName, previousPage)}
|
||||
currentPage := func(){setViewPersonGeneticAnalysisDiscreteTraitDetailsPage(window, personIdentifier, analysisObject, traitName, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("Viewing Genetic Analysis - " + traitName)
|
||||
|
||||
backButton := getBackButtonCentered(previousPage)
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(analysisObject)
|
||||
if (err != nil) {
|
||||
setErrorEncounteredPage(window, err, previousPage)
|
||||
return
|
||||
|
|
@ -1963,30 +2016,48 @@ func setViewPersonGeneticAnalysisTraitDetailsPage(window fyne.Window, personIden
|
|||
})
|
||||
traitNameRow := container.NewHBox(layout.NewSpacer(), traitNameLabel, traitNameText, traitInfoButton, layout.NewSpacer())
|
||||
|
||||
neuralNetworkExists, _ := geneticPredictionModels.GetGeneticPredictionModelBytes(traitName)
|
||||
|
||||
getGenomesContainer := func()(*fyne.Container, error){
|
||||
|
||||
traitRulesMap, err := traits.GetTraitRulesMap(traitName)
|
||||
if (err != nil){ return nil, err }
|
||||
|
||||
totalNumberOfRules := len(traitRulesMap)
|
||||
totalNumberOfRulesString := helpers.ConvertIntToString(totalNumberOfRules)
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabel1 := widget.NewLabel("")
|
||||
genomeNameLabel := getItalicLabelCentered("Genome Name")
|
||||
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
outcomeScoresLabel := getItalicLabelCentered("Outcome Scores")
|
||||
emptyLabel2 := widget.NewLabel("")
|
||||
predictedOutcomeLabel := getItalicLabelCentered("Predicted Outcome")
|
||||
|
||||
numberOfLabel := getItalicLabelCentered("Number of")
|
||||
emptyLabel3 := widget.NewLabel("")
|
||||
predictionConfidenceLabel := getItalicLabelCentered("Prediction Confidence")
|
||||
|
||||
quantityOfLabel := getItalicLabelCentered("Quantity Of")
|
||||
rulesTestedLabel := getItalicLabelCentered("Rules Tested")
|
||||
|
||||
emptyLabelD := widget.NewLabel("")
|
||||
emptyLabelE := widget.NewLabel("")
|
||||
emptyLabel4 := widget.NewLabel("")
|
||||
emptyLabel5 := widget.NewLabel("")
|
||||
|
||||
genomeNameColumn := container.NewVBox(emptyLabelA, genomeNameLabel, widget.NewSeparator())
|
||||
outcomeScoresColumn := container.NewVBox(emptyLabelB, outcomeScoresLabel, widget.NewSeparator())
|
||||
numberOfRulesTestedColumn := container.NewVBox(numberOfLabel, rulesTestedLabel, widget.NewSeparator())
|
||||
viewRulesButtonsColumn := container.NewVBox(emptyLabelD, emptyLabelE, widget.NewSeparator())
|
||||
genomeNameColumn := container.NewVBox()
|
||||
predictedOutcomeColumn := container.NewVBox()
|
||||
neuralNetworkPredictionConfidenceColumn := container.NewVBox()
|
||||
numberOfRulesTestedColumn := container.NewVBox(quantityOfLabel, rulesTestedLabel, widget.NewSeparator())
|
||||
viewDetailsButtonsColumn := container.NewVBox()
|
||||
|
||||
if (neuralNetworkExists == false){
|
||||
// We only need an extra header row if the numberOfRulesTested column is shown
|
||||
genomeNameColumn.Add(emptyLabel1)
|
||||
predictedOutcomeColumn.Add(emptyLabel2)
|
||||
neuralNetworkPredictionConfidenceColumn.Add(emptyLabel3)
|
||||
viewDetailsButtonsColumn.Add(emptyLabel4)
|
||||
}
|
||||
|
||||
genomeNameColumn.Add(genomeNameLabel)
|
||||
predictedOutcomeColumn.Add(predictedOutcomeLabel)
|
||||
neuralNetworkPredictionConfidenceColumn.Add(predictionConfidenceLabel)
|
||||
viewDetailsButtonsColumn.Add(emptyLabel5)
|
||||
|
||||
genomeNameColumn.Add(widget.NewSeparator())
|
||||
predictedOutcomeColumn.Add(widget.NewSeparator())
|
||||
neuralNetworkPredictionConfidenceColumn.Add(widget.NewSeparator())
|
||||
viewDetailsButtonsColumn.Add(widget.NewSeparator())
|
||||
|
||||
addGenomeRow := func(genomeName string, genomeIdentifier [16]byte, isACombinedGenome bool)error{
|
||||
|
||||
|
|
@ -2008,66 +2079,121 @@ func setViewPersonGeneticAnalysisTraitDetailsPage(window fyne.Window, personIden
|
|||
|
||||
genomeNameCell := getGenomeNameCell()
|
||||
|
||||
_, anyTraitRuleTested, outcomeScoresMap, numberOfRulesTested, _, err := readGeneticAnalysis.GetPersonTraitInfoFromGeneticAnalysis(analysisObject, traitName, genomeIdentifier)
|
||||
neuralNetworkExists, neuralNetworkAnalysisExists, neuralNetworkPredictedOutcome, neuralNetworkPredictionConfidence, _, _, anyRulesExist, rulesAnalysisExists, _, rulesPredictedOutcomeExists, rulesPredictedOutcome, quantityOfRulesTested, _, _, err := readGeneticAnalysis.GetPersonDiscreteTraitInfoFromGeneticAnalysis(analysisObject, traitName, genomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
|
||||
// We add all of the columns except for the trait rule column, which may be multiple rows high
|
||||
if (neuralNetworkExists == false && anyRulesExist == false){
|
||||
// This trait is not analyzable
|
||||
return errors.New("setViewPersonGeneticAnalysisTraitDetailsPage called with trait which cannot be analyzed via neural networks and traits.")
|
||||
}
|
||||
|
||||
genomeNumberOfRulesTestedString := helpers.ConvertIntToString(numberOfRulesTested)
|
||||
numberOfRulesTestedLabel := getBoldLabelCentered(genomeNumberOfRulesTestedString + "/" + totalNumberOfRulesString)
|
||||
getPredictedOutcomeLabel := func()fyne.Widget{
|
||||
|
||||
viewRulesButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
setViewPersonGenomeTraitRulesPage(window, analysisObject, traitName, genomeIdentifier, genomeName, currentPage)
|
||||
if (neuralNetworkExists == true){
|
||||
if (neuralNetworkAnalysisExists == false){
|
||||
|
||||
predictedOutcomeLabel := getItalicLabel("Unknown")
|
||||
|
||||
return predictedOutcomeLabel
|
||||
}
|
||||
|
||||
predictedOutcomeLabel := getBoldLabel(neuralNetworkPredictedOutcome)
|
||||
|
||||
return predictedOutcomeLabel
|
||||
}
|
||||
|
||||
// anyRulesExist must be true
|
||||
|
||||
if (rulesAnalysisExists == false || rulesPredictedOutcomeExists == false){
|
||||
|
||||
predictedOutcomeLabel := getItalicLabel("Unknown")
|
||||
return predictedOutcomeLabel
|
||||
}
|
||||
|
||||
predictedOutcomeLabel := getBoldLabel(rulesPredictedOutcome)
|
||||
|
||||
return predictedOutcomeLabel
|
||||
}
|
||||
|
||||
predictedOutcomeLabel := getPredictedOutcomeLabel()
|
||||
|
||||
predictedOutcomeLabelCentered := getWidgetCentered(predictedOutcomeLabel)
|
||||
|
||||
getNeuralNetworkConfidenceLabel := func()fyne.Widget{
|
||||
|
||||
if (neuralNetworkExists == false){
|
||||
|
||||
emptyLabel := widget.NewLabel("")
|
||||
|
||||
return emptyLabel
|
||||
}
|
||||
if (neuralNetworkAnalysisExists == false){
|
||||
|
||||
predictedOutcomeConfidenceLabel := getItalicLabel("Unknown")
|
||||
|
||||
return predictedOutcomeConfidenceLabel
|
||||
}
|
||||
|
||||
neuralNetworkPredictionConfidenceString := helpers.ConvertIntToString(neuralNetworkPredictionConfidence)
|
||||
predictedOutcomeConfidenceLabel := getBoldLabel(neuralNetworkPredictionConfidenceString + "%")
|
||||
|
||||
return predictedOutcomeConfidenceLabel
|
||||
}
|
||||
|
||||
predictedOutcomeConfidenceLabel := getNeuralNetworkConfidenceLabel()
|
||||
predictedOutcomeConfidenceLabelCentered := getWidgetCentered(predictedOutcomeConfidenceLabel)
|
||||
|
||||
getQuantityOfRulesTestedLabel := func()(fyne.Widget, error){
|
||||
|
||||
if (anyRulesExist == false){
|
||||
|
||||
emptyLabel := widget.NewLabel("")
|
||||
return emptyLabel, nil
|
||||
}
|
||||
|
||||
traitRulesMap, err := traits.GetTraitRulesMap(traitName)
|
||||
if (err != nil){ return nil, err }
|
||||
|
||||
totalNumberOfRules := len(traitRulesMap)
|
||||
totalNumberOfRulesString := helpers.ConvertIntToString(totalNumberOfRules)
|
||||
|
||||
if (rulesAnalysisExists == false){
|
||||
quantityOfRulesTestedLabel := getItalicLabel("0/" + totalNumberOfRulesString)
|
||||
return quantityOfRulesTestedLabel, nil
|
||||
}
|
||||
|
||||
quantityOfRulesTestedString := helpers.ConvertIntToString(quantityOfRulesTested)
|
||||
|
||||
quantityOfRulesTestedLabel := getBoldLabel(quantityOfRulesTestedString + "/" + totalNumberOfRulesString)
|
||||
|
||||
return quantityOfRulesTestedLabel, nil
|
||||
}
|
||||
|
||||
quantityOfRulesTestedLabel, err := getQuantityOfRulesTestedLabel()
|
||||
if (err != nil) { return err }
|
||||
|
||||
quantityOfRulesTestedLabelCentered := getWidgetCentered(quantityOfRulesTestedLabel)
|
||||
|
||||
viewDetailsButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
if (neuralNetworkExists == true){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
} else {
|
||||
setViewPersonGenomeDiscreteTraitRulesPage(window, analysisObject, traitName, genomeIdentifier, genomeName, currentPage)
|
||||
}
|
||||
})
|
||||
|
||||
genomeNameColumn.Add(genomeNameCell)
|
||||
numberOfRulesTestedColumn.Add(numberOfRulesTestedLabel)
|
||||
viewRulesButtonsColumn.Add(viewRulesButton)
|
||||
|
||||
if (anyTraitRuleTested == false){
|
||||
|
||||
unknownTranslated := translate("Unknown")
|
||||
unknownLabel := getBoldLabelCentered(unknownTranslated)
|
||||
|
||||
outcomeScoresColumn.Add(unknownLabel)
|
||||
|
||||
} else {
|
||||
|
||||
// We have to sort the outcome names so they always show up in the same order
|
||||
|
||||
outcomeNamesList := helpers.GetListOfMapKeys(outcomeScoresMap)
|
||||
|
||||
helpers.SortStringListToUnicodeOrder(outcomeNamesList)
|
||||
|
||||
for index, outcomeName := range outcomeNamesList{
|
||||
|
||||
outcomeScore, exists := outcomeScoresMap[outcomeName]
|
||||
if (exists == false){
|
||||
return errors.New("Outcome name not found in outcome scores map after being found already: " + outcomeName)
|
||||
}
|
||||
|
||||
outcomeScoreString := helpers.ConvertIntToString(outcomeScore)
|
||||
|
||||
outcomeRow := getBoldLabelCentered(outcomeName + ": " + outcomeScoreString)
|
||||
outcomeScoresColumn.Add(outcomeRow)
|
||||
|
||||
if (index > 0){
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
|
||||
genomeNameColumn.Add(emptyLabelA)
|
||||
numberOfRulesTestedColumn.Add(emptyLabelB)
|
||||
viewRulesButtonsColumn.Add(emptyLabelC)
|
||||
}
|
||||
}
|
||||
}
|
||||
predictedOutcomeColumn.Add(predictedOutcomeLabelCentered)
|
||||
neuralNetworkPredictionConfidenceColumn.Add(predictedOutcomeConfidenceLabelCentered)
|
||||
numberOfRulesTestedColumn.Add(quantityOfRulesTestedLabelCentered)
|
||||
viewDetailsButtonsColumn.Add(viewDetailsButton)
|
||||
|
||||
genomeNameColumn.Add(widget.NewSeparator())
|
||||
outcomeScoresColumn.Add(widget.NewSeparator())
|
||||
predictedOutcomeColumn.Add(widget.NewSeparator())
|
||||
neuralNetworkPredictionConfidenceColumn.Add(widget.NewSeparator())
|
||||
numberOfRulesTestedColumn.Add(widget.NewSeparator())
|
||||
viewRulesButtonsColumn.Add(widget.NewSeparator())
|
||||
viewDetailsButtonsColumn.Add(widget.NewSeparator())
|
||||
|
||||
return nil
|
||||
}
|
||||
|
|
@ -2112,17 +2238,41 @@ func setViewPersonGeneticAnalysisTraitDetailsPage(window fyne.Window, personIden
|
|||
if (err != nil){ return nil, err }
|
||||
}
|
||||
|
||||
outcomeScoresHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitOutcomeScoresExplainerPage(window, currentPage)
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
neuralNetworksHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setDiscreteTraitNeuralNetworkPredictionExplainerPage(window, currentPage)
|
||||
})
|
||||
predictedOutcomeColumn.Add(neuralNetworksHelpButton)
|
||||
} else {
|
||||
|
||||
rulesHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setDiscreteTraitRulesPredictionExplainerPage(window, currentPage)
|
||||
})
|
||||
predictedOutcomeColumn.Add(rulesHelpButton)
|
||||
}
|
||||
|
||||
neuralNetworkConfidenceHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
showUnderConstructionDialog(window)
|
||||
//TODO
|
||||
})
|
||||
outcomeScoresColumn.Add(outcomeScoresHelpButton)
|
||||
neuralNetworkPredictionConfidenceColumn.Add(neuralNetworkConfidenceHelpButton)
|
||||
|
||||
numberOfRulesTestedHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitNumberOfRulesTestedExplainerPage(window, currentPage)
|
||||
setDiscreteTraitQuantityOfRulesTestedExplainerPage(window, currentPage)
|
||||
})
|
||||
numberOfRulesTestedColumn.Add(numberOfRulesTestedHelpButton)
|
||||
|
||||
genomesContainer := container.NewHBox(layout.NewSpacer(), genomeNameColumn, outcomeScoresColumn, numberOfRulesTestedColumn, viewRulesButtonsColumn, layout.NewSpacer())
|
||||
genomesContainer := container.NewHBox(layout.NewSpacer(), genomeNameColumn, predictedOutcomeColumn)
|
||||
|
||||
if (neuralNetworkExists == true){
|
||||
genomesContainer.Add(neuralNetworkPredictionConfidenceColumn)
|
||||
} else {
|
||||
genomesContainer.Add(numberOfRulesTestedColumn)
|
||||
}
|
||||
|
||||
genomesContainer.Add(viewDetailsButtonsColumn)
|
||||
genomesContainer.Add(layout.NewSpacer())
|
||||
|
||||
return genomesContainer, nil
|
||||
}
|
||||
|
|
@ -2140,12 +2290,12 @@ func setViewPersonGeneticAnalysisTraitDetailsPage(window fyne.Window, personIden
|
|||
|
||||
|
||||
|
||||
// Ths function provides a page to view the trait rules for a particular genome from a genetic analysis
|
||||
func setViewPersonGenomeTraitRulesPage(window fyne.Window, geneticAnalysisObject geneticAnalysis.PersonAnalysis, traitName string, genomeIdentifier [16]byte, genomeName string, previousPage func()){
|
||||
// Ths function provides a page to view the discrete trait rules for a particular genome from a genetic analysis
|
||||
func setViewPersonGenomeDiscreteTraitRulesPage(window fyne.Window, geneticAnalysisObject geneticAnalysis.PersonAnalysis, traitName string, genomeIdentifier [16]byte, genomeName string, previousPage func()){
|
||||
|
||||
setLoadingScreen(window, "Loading Trait Rules", "Loading trait rules...")
|
||||
|
||||
currentPage := func(){setViewPersonGenomeTraitRulesPage(window, geneticAnalysisObject, traitName, genomeIdentifier, genomeName, previousPage)}
|
||||
currentPage := func(){setViewPersonGenomeDiscreteTraitRulesPage(window, geneticAnalysisObject, traitName, genomeIdentifier, genomeName, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("View Trait Rules - " + traitName)
|
||||
|
||||
|
|
@ -2153,7 +2303,7 @@ func setViewPersonGenomeTraitRulesPage(window fyne.Window, geneticAnalysisObject
|
|||
|
||||
description1 := widget.NewLabel("Below are the trait rule results for this genome.")
|
||||
rulesHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitRulesExplainerPage(window, currentPage)
|
||||
setDiscreteTraitRulesExplainerPage(window, currentPage)
|
||||
})
|
||||
description1Row := container.NewHBox(layout.NewSpacer(), description1, rulesHelpButton, layout.NewSpacer())
|
||||
|
||||
|
|
@ -2195,7 +2345,7 @@ func setViewPersonGenomeTraitRulesPage(window fyne.Window, geneticAnalysisObject
|
|||
return
|
||||
}
|
||||
|
||||
ruleStatusIsKnown, genomePassesRule, err := readGeneticAnalysis.GetPersonTraitRuleInfoFromGeneticAnalysis(geneticAnalysisObject, traitName, ruleIdentifier, genomeIdentifier)
|
||||
ruleStatusIsKnown, genomePassesRule, err := readGeneticAnalysis.GetPersonDiscreteTraitRuleInfoFromGeneticAnalysis(geneticAnalysisObject, traitName, ruleIdentifier, genomeIdentifier)
|
||||
if (err != nil){
|
||||
setErrorEncounteredPage(window, err, previousPage)
|
||||
return
|
||||
|
|
@ -2221,7 +2371,7 @@ func setViewPersonGenomeTraitRulesPage(window fyne.Window, geneticAnalysisObject
|
|||
rulesTestedLabel := widget.NewLabel("Rules Tested:")
|
||||
rulesTestedText := getBoldLabel(numberOfRulesTestedString + "/" + totalNumberOfRulesString)
|
||||
rulesTestedHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitNumberOfRulesTestedExplainerPage(window, currentPage)
|
||||
setDiscreteTraitQuantityOfRulesTestedExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
rulesTestedRow := container.NewHBox(layout.NewSpacer(), rulesTestedLabel, rulesTestedText, rulesTestedHelpButton, layout.NewSpacer())
|
||||
|
|
@ -2245,7 +2395,7 @@ func setViewPersonGenomeTraitRulesPage(window fyne.Window, geneticAnalysisObject
|
|||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil){ return err }
|
||||
|
||||
ruleStatusIsKnown, genomePassesRule, err := readGeneticAnalysis.GetPersonTraitRuleInfoFromGeneticAnalysis(geneticAnalysisObject, traitName, ruleIdentifier, genomeIdentifier)
|
||||
ruleStatusIsKnown, genomePassesRule, err := readGeneticAnalysis.GetPersonDiscreteTraitRuleInfoFromGeneticAnalysis(geneticAnalysisObject, traitName, ruleIdentifier, genomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
|
||||
getGenomePassesRuleText := func()string{
|
||||
|
|
@ -2267,7 +2417,7 @@ func setViewPersonGenomeTraitRulesPage(window fyne.Window, geneticAnalysisObject
|
|||
// We do this because the rule effects column may be multiple rows tall
|
||||
|
||||
viewRuleButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
setViewPersonGeneticAnalysisTraitRuleDetailsPage(window, geneticAnalysisObject, traitName, ruleIdentifier, currentPage)
|
||||
setViewPersonGeneticAnalysisDiscreteTraitRuleDetailsPage(window, geneticAnalysisObject, traitName, ruleIdentifier, currentPage)
|
||||
})
|
||||
|
||||
ruleIdentifierColumn.Add(ruleIdentifierLabel)
|
||||
|
|
@ -2352,12 +2502,12 @@ func setViewPersonGenomeTraitRulesPage(window fyne.Window, geneticAnalysisObject
|
|||
}
|
||||
|
||||
ruleEffectsHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitRuleOutcomeEffectsExplainerPage(window, currentPage)
|
||||
setDiscreteTraitRuleOutcomeEffectsExplainerPage(window, currentPage)
|
||||
})
|
||||
ruleEffectsColumn.Add(ruleEffectsHelpButton)
|
||||
|
||||
genomePassesRuleHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setGenomePassesTraitRuleExplainerPage(window, currentPage)
|
||||
setGenomePassesDiscreteTraitRuleExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
genomePassesRuleColumn.Add(genomePassesRuleHelpButton)
|
||||
|
|
@ -2381,9 +2531,9 @@ func setViewPersonGenomeTraitRulesPage(window fyne.Window, geneticAnalysisObject
|
|||
|
||||
// This function provides a page to view the details of a specific trait rule from a person genetic analysis
|
||||
// The page will show the rule details for all of the person's genomes
|
||||
func setViewPersonGeneticAnalysisTraitRuleDetailsPage(window fyne.Window, geneticAnalysisObject geneticAnalysis.PersonAnalysis, traitName string, ruleIdentifier [3]byte, previousPage func()){
|
||||
func setViewPersonGeneticAnalysisDiscreteTraitRuleDetailsPage(window fyne.Window, geneticAnalysisObject geneticAnalysis.PersonAnalysis, traitName string, ruleIdentifier [3]byte, previousPage func()){
|
||||
|
||||
currentPage := func(){setViewPersonGeneticAnalysisTraitRuleDetailsPage(window, geneticAnalysisObject, traitName, ruleIdentifier, previousPage)}
|
||||
currentPage := func(){setViewPersonGeneticAnalysisDiscreteTraitRuleDetailsPage(window, geneticAnalysisObject, traitName, ruleIdentifier, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("Trait Rule Details - " + traitName)
|
||||
|
||||
|
|
@ -2396,13 +2546,13 @@ func setViewPersonGeneticAnalysisTraitRuleDetailsPage(window fyne.Window, geneti
|
|||
ruleIdentifierLabel := widget.NewLabel("Rule Identifier:")
|
||||
ruleIdentifierText := getBoldLabel(ruleIdentifierHex)
|
||||
ruleInfoButton := widget.NewButtonWithIcon("", theme.InfoIcon(), func(){
|
||||
setViewTraitRuleDetailsPage(window, traitName, ruleIdentifierHex, currentPage)
|
||||
setViewDiscreteTraitRuleDetailsPage(window, traitName, ruleIdentifierHex, currentPage)
|
||||
})
|
||||
ruleIdentifierRow := container.NewHBox(layout.NewSpacer(), ruleIdentifierLabel, ruleIdentifierText, ruleInfoButton, layout.NewSpacer())
|
||||
|
||||
getGenomesRuleInfoGrid := func()(*fyne.Container, error){
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(geneticAnalysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(geneticAnalysisObject)
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
genomeNameLabel := getItalicLabelCentered("Genome Name")
|
||||
|
|
@ -2413,7 +2563,7 @@ func setViewPersonGeneticAnalysisTraitRuleDetailsPage(window fyne.Window, geneti
|
|||
|
||||
addGenomeRow := func(genomeName string, genomeIdentifier [16]byte, isACombinedGenome bool)error{
|
||||
|
||||
genomeRuleStatusKnown, genomePassesRule, err := readGeneticAnalysis.GetPersonTraitRuleInfoFromGeneticAnalysis(geneticAnalysisObject, traitName, ruleIdentifier, genomeIdentifier)
|
||||
genomeRuleStatusKnown, genomePassesRule, err := readGeneticAnalysis.GetPersonDiscreteTraitRuleInfoFromGeneticAnalysis(geneticAnalysisObject, traitName, ruleIdentifier, genomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
|
||||
getGenomePassesRuleText := func()string{
|
||||
|
|
@ -2501,7 +2651,7 @@ func setViewPersonGeneticAnalysisTraitRuleDetailsPage(window fyne.Window, geneti
|
|||
}
|
||||
|
||||
genomePassesRuleHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setGenomePassesTraitRuleExplainerPage(window, currentPage)
|
||||
setGenomePassesDiscreteTraitRuleExplainerPage(window, currentPage)
|
||||
})
|
||||
genomePassesRuleColumn.Add(genomePassesRuleHelpButton)
|
||||
|
||||
|
|
|
|||
|
|
@ -510,7 +510,7 @@ func setViewTraitDetailsPage(window fyne.Window, traitName string, previousPage
|
|||
}
|
||||
|
||||
traitDescription := traitObject.TraitDescription
|
||||
traitReferencesMap := traitObject.References
|
||||
traitReferencesMap := traitObject.ReferencesMap
|
||||
|
||||
traitNameLabel := widget.NewLabel("Trait Name:")
|
||||
traitNameText := getBoldLabel(traitName)
|
||||
|
|
@ -538,9 +538,9 @@ func setViewTraitDetailsPage(window fyne.Window, traitName string, previousPage
|
|||
setPageContent(page, window)
|
||||
}
|
||||
|
||||
func setViewTraitRuleDetailsPage(window fyne.Window, traitName string, ruleIdentifier string, previousPage func()){
|
||||
func setViewDiscreteTraitRuleDetailsPage(window fyne.Window, traitName string, ruleIdentifier string, previousPage func()){
|
||||
|
||||
currentPage := func(){setViewTraitRuleDetailsPage(window, traitName, ruleIdentifier, previousPage)}
|
||||
currentPage := func(){setViewDiscreteTraitRuleDetailsPage(window, traitName, ruleIdentifier, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("Viewing Rule Details")
|
||||
|
||||
|
|
@ -561,7 +561,7 @@ func setViewTraitRuleDetailsPage(window fyne.Window, traitName string, ruleIdent
|
|||
}
|
||||
|
||||
ruleOutcomePointsMap := traitRuleObject.OutcomePointsMap
|
||||
ruleReferencesMap := traitRuleObject.References
|
||||
ruleReferencesMap := traitRuleObject.ReferencesMap
|
||||
|
||||
viewReferencesButton := getWidgetCentered(widget.NewButtonWithIcon("View References", theme.ListIcon(), func(){
|
||||
setViewGeneticAnalysisReferencesPage(window, "Rule", ruleReferencesMap, currentPage)
|
||||
|
|
@ -605,7 +605,7 @@ func setViewTraitRuleDetailsPage(window fyne.Window, traitName string, ruleIdent
|
|||
}
|
||||
|
||||
outcomeEffectHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitRuleOutcomeEffectsExplainerPage(window, currentPage)
|
||||
setDiscreteTraitRuleOutcomeEffectsExplainerPage(window, currentPage)
|
||||
})
|
||||
outcomeEffectColumn.Add(outcomeEffectHelpButton)
|
||||
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@ import "fyne.io/fyne/v2/widget"
|
|||
|
||||
import "seekia/resources/worldLanguages"
|
||||
import "seekia/resources/worldLocations"
|
||||
import "seekia/resources/geneticPredictionModels"
|
||||
import "seekia/resources/geneticReferences/monogenicDiseases"
|
||||
import "seekia/resources/geneticReferences/polygenicDiseases"
|
||||
import "seekia/resources/geneticReferences/traits"
|
||||
|
|
@ -1270,7 +1271,7 @@ func setViewUserProfilePage_Category(window fyne.Window, profileIsMine bool, cat
|
|||
})
|
||||
|
||||
geneticTraitsButton := widget.NewButton("Genetic Traits", func(){
|
||||
setViewMateProfilePage_GeneticTraits(window, "Offspring", getAnyUserProfileAttributeFunction, currentPage)
|
||||
setViewMateProfilePage_GeneticTraits(window, getAnyUserProfileAttributeFunction, currentPage)
|
||||
})
|
||||
|
||||
buttonsGrid := getContainerCentered(container.NewGridWithColumns(2, racialSimilarityButton, totalDiseaseRiskButton, ancestryCompositionButton, monogenicDiseasesButton, haplogroupsButton, polygenicDiseasesButton, neanderthalVariantsButton, geneticTraitsButton))
|
||||
|
|
@ -2097,9 +2098,9 @@ func setViewMateProfilePage_RacialSimilarity(window fyne.Window, getAnyUserProfi
|
|||
if (err != nil) { return err }
|
||||
|
||||
traitLociList := traitObject.LociList
|
||||
numberOfTraitLoci := len(traitLociList)
|
||||
quantityOfTraitLoci := len(traitLociList)
|
||||
|
||||
numberOfTraitLociString := helpers.ConvertIntToString(numberOfTraitLoci)
|
||||
quantityOfTraitLociString := helpers.ConvertIntToString(quantityOfTraitLoci)
|
||||
|
||||
geneticSimilarityIsKnown, _, attributeValue, err := getAnyUserProfileAttributeFunction(geneticSimilarityAttributeName)
|
||||
if (err != nil) { return err }
|
||||
|
|
@ -2108,11 +2109,11 @@ func setViewMateProfilePage_RacialSimilarity(window fyne.Window, getAnyUserProfi
|
|||
|
||||
geneticSimilarityColumn.Add(unknownLabel)
|
||||
|
||||
numberOfTestedLociText := "0/" + numberOfTraitLociString
|
||||
quantityOfTestedLociText := "0/" + quantityOfTraitLociString
|
||||
|
||||
numberOfTestedLociLabel := getBoldLabelCentered(numberOfTestedLociText)
|
||||
quantityOfTestedLociLabel := getBoldLabelCentered(quantityOfTestedLociText)
|
||||
|
||||
numberOfTestedLociColumn.Add(numberOfTestedLociLabel)
|
||||
numberOfTestedLociColumn.Add(quantityOfTestedLociLabel)
|
||||
} else {
|
||||
|
||||
similarityFormatted := attributeValue + "%"
|
||||
|
|
@ -2147,7 +2148,7 @@ func setViewMateProfilePage_RacialSimilarity(window fyne.Window, getAnyUserProfi
|
|||
|
||||
numberOfTestedLociString := helpers.ConvertIntToString(numberOfTestedLoci)
|
||||
|
||||
numberOfTestedLociLabelText := numberOfTestedLociString + "/" + numberOfTraitLociString
|
||||
numberOfTestedLociLabelText := numberOfTestedLociString + "/" + quantityOfTraitLociString
|
||||
|
||||
numberOfTestedLociLabel := getBoldLabelCentered(numberOfTestedLociLabelText)
|
||||
|
||||
|
|
@ -2959,24 +2960,25 @@ func setViewMateProfilePage_PolygenicDiseases(window fyne.Window, userOrOffsprin
|
|||
//Outputs:
|
||||
// -map[int64]locusValue.LocusValue
|
||||
// -error
|
||||
getMyDiseaseLocusValuesMap := func()(map[int64]locusValue.LocusValue, error){
|
||||
getMyGenomeLocusValuesMap := func()(map[int64]locusValue.LocusValue, error){
|
||||
|
||||
if (myPersonChosen == false || myGenomesExist == false || myAnalysisIsReady == false){
|
||||
emptyMap := make(map[int64]locusValue.LocusValue)
|
||||
return emptyMap, nil
|
||||
}
|
||||
|
||||
anyMyLociValuesExist, _, _, myDiseaseLocusValuesMap, _, _, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(myAnalysisObject, diseaseName, myGenomeIdentifier)
|
||||
_, _, _, _, myGenomesMap, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(myAnalysisObject)
|
||||
if (err != nil) { return nil, err }
|
||||
if (anyMyLociValuesExist == false){
|
||||
emptyMap := make(map[int64]locusValue.LocusValue)
|
||||
return emptyMap, nil
|
||||
|
||||
myGenomeLocusValuesMap, exists := myGenomesMap[myGenomeIdentifier]
|
||||
if (exists == false){
|
||||
return nil, errors.New("GetMyChosenMateGeneticAnalysis returning analysis which is missing genome with myGenomeIdentifier.")
|
||||
}
|
||||
|
||||
return myDiseaseLocusValuesMap, nil
|
||||
return myGenomeLocusValuesMap, nil
|
||||
}
|
||||
|
||||
myDiseaseLocusValuesMap, err := getMyDiseaseLocusValuesMap()
|
||||
myGenomeLocusValuesMap, err := getMyGenomeLocusValuesMap()
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
// Map Structure: Locus rsID -> Locus Value
|
||||
|
|
@ -3031,7 +3033,7 @@ func setViewMateProfilePage_PolygenicDiseases(window fyne.Window, userOrOffsprin
|
|||
userDiseaseRiskScoreString, err := getUserDiseaseRiskScoreString()
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
anyOffspringLociTested, offspringDiseaseRiskScore, offspringNumberOfLociTested, _, offspringSampleRiskScoresList, err := createCoupleGeneticAnalysis.GetOffspringPolygenicDiseaseInfo(diseaseLociList, myDiseaseLocusValuesMap, userDiseaseLocusValuesMap)
|
||||
anyOffspringLociTested, offspringDiseaseRiskScore, offspringNumberOfLociTested, _, offspringSampleRiskScoresList, err := createCoupleGeneticAnalysis.GetOffspringPolygenicDiseaseInfo(diseaseLociList, myGenomeLocusValuesMap, userDiseaseLocusValuesMap)
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
getOffspringDiseaseRiskScoreFormatted := func()(string, error){
|
||||
|
|
@ -3172,7 +3174,7 @@ func setViewMateProfilePage_PolygenicDiseaseLoci(window fyne.Window, diseaseName
|
|||
// Outputs:
|
||||
// -map[int64]locusValue.LocusValue: Map Structure: Locus rsID -> Locus Value
|
||||
// -error
|
||||
getMyDiseaseLocusValuesMap := func()(map[int64]locusValue.LocusValue, error){
|
||||
getMyGenomeLocusValuesMap := func()(map[int64]locusValue.LocusValue, error){
|
||||
|
||||
myPersonChosen, myGenomesExist, myAnalysisIsReady, myAnalysisObject, myGenomeIdentifier, _, err := myChosenAnalysis.GetMyChosenMateGeneticAnalysis()
|
||||
if (err != nil) { return nil, err }
|
||||
|
|
@ -3183,17 +3185,18 @@ func setViewMateProfilePage_PolygenicDiseaseLoci(window fyne.Window, diseaseName
|
|||
return emptyMap, nil
|
||||
}
|
||||
|
||||
anyLocusValuesExist, _, _, myLocusValuesMap, _, _, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(myAnalysisObject, diseaseName, myGenomeIdentifier)
|
||||
_, _, _, _, myGenomesMap, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(myAnalysisObject)
|
||||
if (err != nil) { return nil, err }
|
||||
if (anyLocusValuesExist == false){
|
||||
emptyMap := make(map[int64]locusValue.LocusValue)
|
||||
return emptyMap, nil
|
||||
|
||||
myGenomeLocusValuesMap, exists := myGenomesMap[myGenomeIdentifier]
|
||||
if (exists == false){
|
||||
return nil, errors.New("GetMyChosenMateGeneticAnalysis returning analysis which is missing genome with myGenomeIdentifier.")
|
||||
}
|
||||
|
||||
return myLocusValuesMap, nil
|
||||
return myGenomeLocusValuesMap, nil
|
||||
}
|
||||
|
||||
myDiseaseLocusValuesMap, err := getMyDiseaseLocusValuesMap()
|
||||
myGenomeLocusValuesMap, err := getMyGenomeLocusValuesMap()
|
||||
if (err != nil) {
|
||||
setErrorEncounteredPage(window, err, previousPage)
|
||||
return
|
||||
|
|
@ -3248,7 +3251,7 @@ func setViewMateProfilePage_PolygenicDiseaseLoci(window fyne.Window, diseaseName
|
|||
return
|
||||
}
|
||||
|
||||
anyOffspringLociTested, _, offspringNumberOfLociTested, offspringLociInfoMap, _, err := createCoupleGeneticAnalysis.GetOffspringPolygenicDiseaseInfo(diseaseLocusObjectsList, myDiseaseLocusValuesMap, userDiseaseLocusValuesMap)
|
||||
anyOffspringLociTested, _, offspringNumberOfLociTested, offspringLociInfoMap, _, err := createCoupleGeneticAnalysis.GetOffspringPolygenicDiseaseInfo(diseaseLocusObjectsList, myGenomeLocusValuesMap, userDiseaseLocusValuesMap)
|
||||
if (err != nil) {
|
||||
setErrorEncounteredPage(window, err, previousPage)
|
||||
return
|
||||
|
|
@ -3513,9 +3516,9 @@ func setViewMateProfilePage_PolygenicDiseaseLoci(window fyne.Window, diseaseName
|
|||
setPageContent(page, window)
|
||||
}
|
||||
|
||||
func setViewMateProfilePage_GeneticTraits(window fyne.Window, userOrOffspring string, getAnyUserProfileAttributeFunction func(string)(bool, int, string, error), previousPage func()){
|
||||
func setViewMateProfilePage_GeneticTraits(window fyne.Window, getAnyUserProfileAttributeFunction func(string)(bool, int, string, error), previousPage func()){
|
||||
|
||||
currentPage := func(){setViewMateProfilePage_GeneticTraits(window, userOrOffspring, getAnyUserProfileAttributeFunction, previousPage)}
|
||||
currentPage := func(){setViewMateProfilePage_GeneticTraits(window, getAnyUserProfileAttributeFunction, previousPage)}
|
||||
|
||||
title := getPageTitleCentered(translate("View Profile - Physical"))
|
||||
|
||||
|
|
@ -3523,7 +3526,46 @@ func setViewMateProfilePage_GeneticTraits(window fyne.Window, userOrOffspring st
|
|||
|
||||
subtitle := getPageSubtitleCentered(translate("Genetic Traits"))
|
||||
|
||||
description1 := getLabelCentered("Below is the genetic trait analysis for this user.")
|
||||
description1 := getLabelCentered("Choose if you want to view Discrete traits or Numeric traits.")
|
||||
description2 := getLabelCentered("Discrete traits are traits which have discrete outcomes, such as Eye Color")
|
||||
description3 := getLabelCentered("Numeric traits are traits with numeric outcomes, such as Height.")
|
||||
|
||||
discreteTraitsButton := widget.NewButton("Discrete Traits", func(){
|
||||
setViewMateProfilePage_DiscreteGeneticTraits(window, "Offspring", getAnyUserProfileAttributeFunction, currentPage)
|
||||
})
|
||||
|
||||
numericTraitsButton := widget.NewButton("Numeric Traits", func(){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
|
||||
buttonsGrid := getContainerCentered(container.NewGridWithColumns(1, discreteTraitsButton, numericTraitsButton))
|
||||
|
||||
page := container.NewVBox(title, backButton, widget.NewSeparator(), subtitle, widget.NewSeparator(), description1, description2, description3, widget.NewSeparator(), buttonsGrid)
|
||||
|
||||
setPageContent(page, window)
|
||||
}
|
||||
|
||||
func setViewMateProfilePage_DiscreteGeneticTraits(window fyne.Window, userOrOffspring string, getAnyUserProfileAttributeFunction func(string)(bool, int, string, error), previousPage func()){
|
||||
|
||||
if (userOrOffspring != "User" && userOrOffspring != "Offspring"){
|
||||
setErrorEncounteredPage(window, errors.New("setViewMateProfilePage_DiscreteGeneticTraits called with invalid userOrOffspring: " + userOrOffspring), previousPage)
|
||||
return
|
||||
}
|
||||
|
||||
if (userOrOffspring == "Offspring"){
|
||||
setLoadingScreen(window, "View Profile - Physical", "Computing Genetic Analysis...")
|
||||
}
|
||||
|
||||
currentPage := func(){setViewMateProfilePage_DiscreteGeneticTraits(window, userOrOffspring, getAnyUserProfileAttributeFunction, previousPage)}
|
||||
|
||||
title := getPageTitleCentered(translate("View Profile - Physical"))
|
||||
|
||||
backButton := getBackButtonCentered(previousPage)
|
||||
|
||||
subtitle := getPageSubtitleCentered(translate("Discrete Genetic Traits"))
|
||||
|
||||
description1 := getLabelCentered("Below is the discrete genetic trait analysis for this user.")
|
||||
description2 := getLabelCentered("You can choose to view the analysis of the user or an offspring between you and the user.")
|
||||
description3 := getLabelCentered("You must link your genome person in the Build Profile menu to see offspring information.")
|
||||
|
||||
|
|
@ -3531,7 +3573,7 @@ func setViewMateProfilePage_GeneticTraits(window fyne.Window, userOrOffspring st
|
|||
if (userOrOffspring == newUserOrOffspring){
|
||||
return
|
||||
}
|
||||
setViewMateProfilePage_GeneticTraits(window, newUserOrOffspring, getAnyUserProfileAttributeFunction, previousPage)
|
||||
setViewMateProfilePage_DiscreteGeneticTraits(window, newUserOrOffspring, getAnyUserProfileAttributeFunction, previousPage)
|
||||
}
|
||||
|
||||
userOrOffspringSelector := widget.NewSelect([]string{"User", "Offspring"}, handleSelectButton)
|
||||
|
|
@ -3541,63 +3583,96 @@ func setViewMateProfilePage_GeneticTraits(window fyne.Window, userOrOffspring st
|
|||
|
||||
getTraitsInfoGrid := func()(*fyne.Container, error){
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
traitNameLabel := getItalicLabelCentered("Trait Name")
|
||||
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
userOutcomeScoresLabel := getItalicLabelCentered("User Outcome Scores")
|
||||
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
offspringOutcomeScoresLabel := getItalicLabelCentered("Offspring Outcome Scores")
|
||||
|
||||
numberOfLabelA := getItalicLabelCentered("Number Of")
|
||||
rulesTestedLabelA := getItalicLabelCentered("Rules Tested")
|
||||
|
||||
numberOfLabelB := getItalicLabelCentered("Number Of")
|
||||
rulesTestedLabelB := getItalicLabelCentered("Rules Tested")
|
||||
|
||||
emptyLabelD := widget.NewLabel("")
|
||||
emptyLabelE := widget.NewLabel("")
|
||||
|
||||
traitNameColumn := container.NewVBox(emptyLabelA, traitNameLabel, widget.NewSeparator())
|
||||
userOutcomeScoresColumn := container.NewVBox(emptyLabelB, userOutcomeScoresLabel, widget.NewSeparator())
|
||||
offspringOutcomeScoresColumn := container.NewVBox(emptyLabelC, offspringOutcomeScoresLabel, widget.NewSeparator())
|
||||
userNumberOfRulesTestedColumn := container.NewVBox(numberOfLabelA, rulesTestedLabelA, widget.NewSeparator())
|
||||
offspringNumberOfRulesTestedColumn := container.NewVBox(numberOfLabelB, rulesTestedLabelB, widget.NewSeparator())
|
||||
viewTraitDetailsButtonsColumn := container.NewVBox(emptyLabelD, emptyLabelE, widget.NewSeparator())
|
||||
|
||||
myPersonChosen, myGenomesExist, myAnalysisIsReady, myAnalysisObject, myGenomeIdentifier, _, err := myChosenAnalysis.GetMyChosenMateGeneticAnalysis()
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
//Outputs:
|
||||
// -map[int64]locusValue.LocusValue
|
||||
// -error
|
||||
getMyGenomeLocusValuesMap := func()(map[int64]locusValue.LocusValue, error){
|
||||
|
||||
if (myPersonChosen == false || myGenomesExist == false || myAnalysisIsReady == false){
|
||||
emptyMap := make(map[int64]locusValue.LocusValue)
|
||||
return emptyMap, nil
|
||||
}
|
||||
|
||||
_, _, _, _, myGenomesMap, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(myAnalysisObject)
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
myGenomeLocusValuesMap, exists := myGenomesMap[myGenomeIdentifier]
|
||||
if (exists == false){
|
||||
return nil, errors.New("GetMyChosenMateGeneticAnalysis returning analysis which is missing genome with myGenomeIdentifier.")
|
||||
}
|
||||
|
||||
return myGenomeLocusValuesMap, nil
|
||||
}
|
||||
|
||||
myGenomeLocusValuesMap, err := getMyGenomeLocusValuesMap()
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
|
||||
emptyLabel1 := widget.NewLabel("")
|
||||
traitNameLabel := getItalicLabelCentered("Trait Name")
|
||||
|
||||
emptyLabel2 := widget.NewLabel("")
|
||||
userPredictedOutcomeTitle := getItalicLabelCentered("User Predicted Outcome")
|
||||
|
||||
emptyLabel3 := widget.NewLabel("")
|
||||
offspringOutcomeProbabilitiesLabel := getItalicLabelCentered("Offspring Outcome Probabilities")
|
||||
|
||||
quantityOfLabel1 := getItalicLabelCentered("Quantity Of")
|
||||
lociKnownLabel := getItalicLabelCentered("Loci Known")
|
||||
|
||||
emptyLabel4 := widget.NewLabel("")
|
||||
emptyLabel5 := widget.NewLabel("")
|
||||
|
||||
traitNameColumn := container.NewVBox(emptyLabel1, traitNameLabel, widget.NewSeparator())
|
||||
userPredictedOutcomeColumn := container.NewVBox(emptyLabel2, userPredictedOutcomeTitle, widget.NewSeparator())
|
||||
|
||||
offspringOutcomeProbabilitiesColumn := container.NewVBox(emptyLabel3, offspringOutcomeProbabilitiesLabel, widget.NewSeparator())
|
||||
|
||||
quantityOfLociKnownColumn := container.NewVBox(quantityOfLabel1, lociKnownLabel, widget.NewSeparator())
|
||||
viewTraitDetailsButtonsColumn := container.NewVBox(emptyLabel4, emptyLabel5, widget.NewSeparator())
|
||||
|
||||
traitObjectsList, err := traits.GetTraitObjectsList()
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
for _, traitObject := range traitObjectsList{
|
||||
|
||||
traitName := traitObject.TraitName
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
if (traitIsDiscreteOrNumeric != "Discrete"){
|
||||
continue
|
||||
}
|
||||
|
||||
traitRulesList := traitObject.RulesList
|
||||
totalNumberOfTraitRules := len(traitRulesList)
|
||||
|
||||
if (totalNumberOfTraitRules == 0){
|
||||
traitLociList := traitObject.LociList
|
||||
|
||||
numberOfTraitLoci := len(traitLociList)
|
||||
|
||||
if (totalNumberOfTraitRules == 0 && numberOfTraitLoci == 0){
|
||||
// We are not able to analyze these traits yet
|
||||
// We will once we add neural network prediction
|
||||
continue
|
||||
}
|
||||
|
||||
totalNumberOfTraitRulesString := helpers.ConvertIntToString(totalNumberOfTraitRules)
|
||||
|
||||
traitOutcomeNamesList := traitObject.OutcomesList
|
||||
|
||||
// We have to sort outcome names so they always show up in the same order
|
||||
|
||||
traitOutcomeNamesListSorted := helpers.CopyAndSortStringListToUnicodeOrder(traitOutcomeNamesList)
|
||||
traitNeuralNetworkExists, _ := geneticPredictionModels.GetGeneticPredictionModelBytes(traitName)
|
||||
if (traitNeuralNetworkExists == false && totalNumberOfTraitRules == 0){
|
||||
// We are not able to analyze these traits yet
|
||||
continue
|
||||
}
|
||||
|
||||
traitNameText := getBoldLabelCentered(translate(traitName))
|
||||
traitNameColumn.Add(traitNameText)
|
||||
|
||||
viewTraitDetailsButton := widget.NewButtonWithIcon("", theme.VisibilityIcon(), func(){
|
||||
setViewMateProfilePage_TraitRules(window, traitName, userOrOffspring, getAnyUserProfileAttributeFunction, currentPage)
|
||||
if (traitNeuralNetworkExists == true){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
} else {
|
||||
setViewMateProfilePage_DiscreteTraitRules(window, traitName, userOrOffspring, getAnyUserProfileAttributeFunction, currentPage)
|
||||
}
|
||||
})
|
||||
|
||||
viewTraitDetailsButtonsColumn.Add(viewTraitDetailsButton)
|
||||
|
|
@ -3606,8 +3681,6 @@ func setViewMateProfilePage_GeneticTraits(window fyne.Window, userOrOffspring st
|
|||
// Map Structure: Locus rsID -> locusValue.LocusValue
|
||||
userTraitLocusValuesMap := make(map[int64]locusValue.LocusValue)
|
||||
|
||||
traitLociList := traitObject.LociList
|
||||
|
||||
for _, rsID := range traitLociList{
|
||||
|
||||
rsIDString := helpers.ConvertInt64ToString(rsID)
|
||||
|
|
@ -3635,200 +3708,244 @@ func setViewMateProfilePage_GeneticTraits(window fyne.Window, userOrOffspring st
|
|||
userTraitLocusValuesMap[rsID] = userLocusValue
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
// -bool: At least 1 rule is known
|
||||
// -map[string]int: Outcome name -> Outcome score
|
||||
// -int: Number of rules tested
|
||||
// -error
|
||||
getUserTraitOutcomeScoresMap := func()(bool, map[string]int, int, error){
|
||||
|
||||
userTraitOutcomeScoresMap := make(map[string]int)
|
||||
userNumberOfRulesTested := 0
|
||||
|
||||
for _, traitRuleObject := range traitRulesList{
|
||||
|
||||
ruleLociList := traitRuleObject.LociList
|
||||
|
||||
userRuleStatusIsKnown, userPassesRule, err := createPersonGeneticAnalysis.GetGenomePassesTraitRuleStatus(ruleLociList, userTraitLocusValuesMap, true)
|
||||
if (err != nil) { return false, nil, 0, err }
|
||||
if (userRuleStatusIsKnown == false){
|
||||
continue
|
||||
}
|
||||
userNumberOfRulesTested += 1
|
||||
|
||||
if (userPassesRule == true){
|
||||
|
||||
ruleOutcomePointsMap := traitRuleObject.OutcomePointsMap
|
||||
|
||||
for traitOutcome, pointsEffect := range ruleOutcomePointsMap{
|
||||
|
||||
userTraitOutcomeScoresMap[traitOutcome] += pointsEffect
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (userNumberOfRulesTested == 0){
|
||||
return false, nil, 0, nil
|
||||
}
|
||||
|
||||
traitOutcomesList := traitObject.OutcomesList
|
||||
|
||||
// We add all outcomes for which there were no points
|
||||
|
||||
for _, traitOutcome := range traitOutcomesList{
|
||||
|
||||
_, exists := userTraitOutcomeScoresMap[traitOutcome]
|
||||
if (exists == false){
|
||||
userTraitOutcomeScoresMap[traitOutcome] = 0
|
||||
}
|
||||
}
|
||||
|
||||
return true, userTraitOutcomeScoresMap, userNumberOfRulesTested, nil
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
// -bool: At least 1 rule is known
|
||||
// -map[string]float64: Outcome name -> Outcome score
|
||||
// -int: Number of rules tested
|
||||
// -error
|
||||
getOffspringTraitOutcomeScoresMap := func()(bool, map[string]float64, int, error){
|
||||
|
||||
if (myPersonChosen == false || myGenomesExist == false || myAnalysisIsReady == false){
|
||||
// Without my genome person chosen, all offspring rules and outcome scores are unknown
|
||||
return false, nil, 0, nil
|
||||
}
|
||||
|
||||
myTraitLocusValuesMap, _, _, _, _, err := readGeneticAnalysis.GetPersonTraitInfoFromGeneticAnalysis(myAnalysisObject, traitName, myGenomeIdentifier)
|
||||
if (err != nil) { return false, nil, 0, err }
|
||||
|
||||
anyRuleTested, offspringNumberOfRulesTested, _, offspringAverageOutcomeScoresMap, err := createCoupleGeneticAnalysis.GetOffspringTraitInfo(traitObject, myTraitLocusValuesMap, userTraitLocusValuesMap)
|
||||
if (err != nil) { return false, nil, 0, err }
|
||||
if (anyRuleTested == false){
|
||||
return false, nil, 0, nil
|
||||
}
|
||||
|
||||
return true, offspringAverageOutcomeScoresMap, offspringNumberOfRulesTested, nil
|
||||
}
|
||||
|
||||
if (userOrOffspring == "User"){
|
||||
|
||||
userTraitOutcomeScoresKnown, userTraitOutcomeScoresMap, userNumberOfRulesTested, err := getUserTraitOutcomeScoresMap()
|
||||
if (err != nil) { return nil, err }
|
||||
if (traitNeuralNetworkExists == true){
|
||||
|
||||
numberOfRulesTestedString := helpers.ConvertIntToString(userNumberOfRulesTested)
|
||||
numberOfRulesTestedFormatted := numberOfRulesTestedString + "/" + totalNumberOfTraitRulesString
|
||||
numberOfRulesTestedLabel := getBoldLabelCentered(numberOfRulesTestedFormatted)
|
||||
userNumberOfRulesTestedColumn.Add(numberOfRulesTestedLabel)
|
||||
traitNeuralNetworkExists, anyLocusValuesAreKnown, predictedOutcome, _, quantityOfLociKnown, _, err := createPersonGeneticAnalysis.GetGenomeDiscreteTraitAnalysis_NeuralNetwork(traitObject, userTraitLocusValuesMap, true)
|
||||
if (err != nil) { return nil, err }
|
||||
if (traitNeuralNetworkExists == false){
|
||||
return nil, errors.New("GetGenomeTraitAnalysis_NeuralNetwork claims neural network doesn't exist for trait, but we already checked.")
|
||||
}
|
||||
if (anyLocusValuesAreKnown == false){
|
||||
unknownLabel := getItalicLabelCentered(translate("Unknown"))
|
||||
userPredictedOutcomeColumn.Add(unknownLabel)
|
||||
} else {
|
||||
predictedOutcomeLabel := getBoldLabelCentered(predictedOutcome)
|
||||
userPredictedOutcomeColumn.Add(predictedOutcomeLabel)
|
||||
}
|
||||
|
||||
if (userTraitOutcomeScoresKnown == false){
|
||||
unknownTranslated := translate("Unknown")
|
||||
unknownLabel := getBoldLabelCentered(unknownTranslated)
|
||||
totalNumberOfLociString := helpers.ConvertIntToString(numberOfTraitLoci)
|
||||
|
||||
quantityOfLociKnownString := helpers.ConvertIntToString(quantityOfLociKnown)
|
||||
|
||||
quantityOfLociKnownFormatted := quantityOfLociKnownString + "/" + totalNumberOfLociString
|
||||
|
||||
quantityOfLociKnownLabel := getBoldLabelCentered(quantityOfLociKnownFormatted)
|
||||
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownLabel)
|
||||
|
||||
userOutcomeScoresColumn.Add(unknownLabel)
|
||||
} else {
|
||||
|
||||
for index, outcomeName := range traitOutcomeNamesListSorted{
|
||||
// We use the rules-based analysis
|
||||
|
||||
outcomeScore, exists := userTraitOutcomeScoresMap[outcomeName]
|
||||
if (exists == false){
|
||||
return nil, errors.New("Outcome not found in userTraitOutcomeScoresMap.")
|
||||
}
|
||||
anyRulesExist, _, quantityOfLociKnown_Rules, _, predictedOutcomeIsKnown, predictedOutcome, err := createPersonGeneticAnalysis.GetGenomeDiscreteTraitAnalysis_Rules(traitObject, userTraitLocusValuesMap, true)
|
||||
if (err != nil) { return nil, err }
|
||||
if (anyRulesExist == false){
|
||||
return nil, errors.New("GetGenomeTraitAnalysis_Rules claims no rules exist when we already checked.")
|
||||
}
|
||||
|
||||
outcomeScoreString := helpers.ConvertIntToString(outcomeScore)
|
||||
if (predictedOutcomeIsKnown == false){
|
||||
unknownLabel := getItalicLabelCentered("Unknown")
|
||||
userPredictedOutcomeColumn.Add(unknownLabel)
|
||||
} else {
|
||||
predictedOutcomeLabel := getBoldLabelCentered(predictedOutcome)
|
||||
userPredictedOutcomeColumn.Add(predictedOutcomeLabel)
|
||||
}
|
||||
|
||||
outcomeRow := getBoldLabelCentered(outcomeName + ": " + outcomeScoreString)
|
||||
userOutcomeScoresColumn.Add(outcomeRow)
|
||||
traitLociList_Rules := traitObject.LociList_Rules
|
||||
|
||||
if (index > 0){
|
||||
totalQuantityOfLoci := len(traitLociList_Rules)
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
quantityOfLociKnownString := helpers.ConvertIntToString(quantityOfLociKnown_Rules)
|
||||
totalQuantityOfLociString := helpers.ConvertIntToString(totalQuantityOfLoci)
|
||||
|
||||
traitNameColumn.Add(emptyLabelA)
|
||||
userNumberOfRulesTestedColumn.Add(emptyLabelB)
|
||||
viewTraitDetailsButtonsColumn.Add(emptyLabelC)
|
||||
quantityOfLociKnownFormatted := quantityOfLociKnownString + "/" + totalQuantityOfLociString
|
||||
|
||||
quantityOfLociKnownLabel := getBoldLabelCentered(quantityOfLociKnownFormatted)
|
||||
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownLabel)
|
||||
}
|
||||
} else {
|
||||
|
||||
// userOrOffspring == "Offspring"
|
||||
|
||||
if (traitNeuralNetworkExists == true){
|
||||
|
||||
neuralNetworkExists, anyLociKnown, outcomeProbabilitiesMap, _, quantityOfLociKnown, _, err := createCoupleGeneticAnalysis.GetOffspringDiscreteTraitInfo_NeuralNetwork(traitObject, userTraitLocusValuesMap, myGenomeLocusValuesMap)
|
||||
if (err != nil) { return nil, err }
|
||||
if (neuralNetworkExists == false){
|
||||
return nil, errors.New("GetOffspringTraitInfo_NeuralNetwork claiming that neural network doesn't exist when we already checked.")
|
||||
}
|
||||
|
||||
totalNumberOfLociString := helpers.ConvertIntToString(numberOfTraitLoci)
|
||||
|
||||
quantityOfLociKnownString := helpers.ConvertIntToString(quantityOfLociKnown)
|
||||
|
||||
quantityOfLociKnownFormatted := quantityOfLociKnownString + "/" + totalNumberOfLociString
|
||||
|
||||
quantityOfLociKnownLabel := getBoldLabelCentered(quantityOfLociKnownFormatted)
|
||||
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownLabel)
|
||||
|
||||
if (anyLociKnown == false){
|
||||
unknownLabel := getItalicLabelCentered("Unknown")
|
||||
|
||||
offspringOutcomeProbabilitiesColumn.Add(unknownLabel)
|
||||
|
||||
} else {
|
||||
|
||||
outcomesList := helpers.GetListOfMapKeys(outcomeProbabilitiesMap)
|
||||
|
||||
// We sort the outcomes in alphabetical order so they show up the same way each time
|
||||
slices.Sort(outcomesList)
|
||||
|
||||
quantityOfAddedItems := 0
|
||||
|
||||
for _, outcomeName := range outcomesList{
|
||||
|
||||
outcomeProbability, exists := outcomeProbabilitiesMap[outcomeName]
|
||||
if (exists == false){
|
||||
return nil, errors.New("GetListOfMapKeys returning element which doesn't exist in map.")
|
||||
}
|
||||
if (outcomeProbability == 0){
|
||||
continue
|
||||
}
|
||||
|
||||
outcomeProbabilityString := helpers.ConvertIntToString(outcomeProbability)
|
||||
outcomeProbabilityLabelText := outcomeName + ": " + outcomeProbabilityString + "%"
|
||||
|
||||
outcomeProbabilityLabel := getBoldLabelCentered(outcomeProbabilityLabelText)
|
||||
|
||||
offspringOutcomeProbabilitiesColumn.Add(outcomeProbabilityLabel)
|
||||
|
||||
quantityOfAddedItems += 1
|
||||
|
||||
if (quantityOfAddedItems > 1){
|
||||
// We add whitespace for the other columns
|
||||
traitNameColumn.Add(widget.NewLabel(""))
|
||||
quantityOfLociKnownColumn.Add(widget.NewLabel(""))
|
||||
viewTraitDetailsButtonsColumn.Add(widget.NewLabel(""))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} else if (userOrOffspring == "Offspring"){
|
||||
|
||||
offspringTraitOutcomeScoresKnown, offspringTraitOutcomeScoresMap, offspringNumberOfRulesTested, err := getOffspringTraitOutcomeScoresMap()
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
numberOfRulesTestedString := helpers.ConvertIntToString(offspringNumberOfRulesTested)
|
||||
numberOfRulesTestedFormatted := numberOfRulesTestedString + "/" + totalNumberOfTraitRulesString
|
||||
numberOfRulesTestedLabel := getBoldLabelCentered(numberOfRulesTestedFormatted)
|
||||
offspringNumberOfRulesTestedColumn.Add(numberOfRulesTestedLabel)
|
||||
|
||||
if (offspringTraitOutcomeScoresKnown == false){
|
||||
unknownTranslated := translate("Unknown")
|
||||
unknownLabel := getBoldLabelCentered(unknownTranslated)
|
||||
|
||||
offspringOutcomeScoresColumn.Add(unknownLabel)
|
||||
} else {
|
||||
|
||||
for index, outcomeName := range traitOutcomeNamesListSorted{
|
||||
// We use the rules-based analysis
|
||||
|
||||
outcomeScore, exists := offspringTraitOutcomeScoresMap[outcomeName]
|
||||
if (exists == false){
|
||||
return nil, errors.New("Outcome not found in offspringTraitOutcomeScoresMap.")
|
||||
}
|
||||
anyRulesExist, rulesAnalysisExists, _, offspringQuantityOfLociKnown, _, outcomeProbabilitiesMap, err := createCoupleGeneticAnalysis.GetOffspringDiscreteTraitInfo_Rules(traitObject, myGenomeLocusValuesMap, userTraitLocusValuesMap)
|
||||
if (err != nil) { return nil, err }
|
||||
if (anyRulesExist == false){
|
||||
return nil, errors.New("GetOffspringDiscreteTraitInfo_Rules claiming that no rules exist when we already checked.")
|
||||
}
|
||||
|
||||
outcomeScoreString := helpers.ConvertFloat64ToStringRounded(outcomeScore, 2)
|
||||
lociList_Rules := traitObject.LociList_Rules
|
||||
|
||||
outcomeRow := getBoldLabelCentered(outcomeName + ": " + outcomeScoreString)
|
||||
offspringOutcomeScoresColumn.Add(outcomeRow)
|
||||
totalQuantityOfLoci := len(lociList_Rules)
|
||||
|
||||
if (index > 0){
|
||||
quantityOfLociKnownString := helpers.ConvertIntToString(offspringQuantityOfLociKnown)
|
||||
totalQuantityOfLociString := helpers.ConvertIntToString(totalQuantityOfLoci)
|
||||
|
||||
emptyLabelA := widget.NewLabel("")
|
||||
emptyLabelB := widget.NewLabel("")
|
||||
emptyLabelC := widget.NewLabel("")
|
||||
quantityOfLociKnownFormatted := quantityOfLociKnownString + "/" + totalQuantityOfLociString
|
||||
quantityOfLociKnownLabel := getBoldLabelCentered(quantityOfLociKnownFormatted)
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownLabel)
|
||||
|
||||
traitNameColumn.Add(emptyLabelA)
|
||||
offspringNumberOfRulesTestedColumn.Add(emptyLabelB)
|
||||
viewTraitDetailsButtonsColumn.Add(emptyLabelC)
|
||||
if (rulesAnalysisExists == false){
|
||||
unknownLabel := getItalicLabelCentered(translate("Unknown"))
|
||||
|
||||
offspringOutcomeProbabilitiesColumn.Add(unknownLabel)
|
||||
} else {
|
||||
|
||||
outcomesList := helpers.GetListOfMapKeys(outcomeProbabilitiesMap)
|
||||
|
||||
// We sort the outcomes in alphabetical order so they show up the same way each time
|
||||
slices.Sort(outcomesList)
|
||||
|
||||
quantityOfAddedItems := 0
|
||||
|
||||
for _, outcomeName := range outcomesList{
|
||||
|
||||
outcomeProbability, exists := outcomeProbabilitiesMap[outcomeName]
|
||||
if (exists == false){
|
||||
return nil, errors.New("GetListOfMapKeys returning element which doesn't exist in map.")
|
||||
}
|
||||
|
||||
if (outcomeProbability == 0){
|
||||
continue
|
||||
}
|
||||
|
||||
outcomeProbabilityString := helpers.ConvertIntToString(outcomeProbability)
|
||||
outcomeProbabilityLabelText := outcomeName + ": " + outcomeProbabilityString + "%"
|
||||
|
||||
outcomeProbabilityLabel := getBoldLabelCentered(outcomeProbabilityLabelText)
|
||||
|
||||
offspringOutcomeProbabilitiesColumn.Add(outcomeProbabilityLabel)
|
||||
|
||||
quantityOfAddedItems += 1
|
||||
|
||||
if (quantityOfAddedItems > 1){
|
||||
// We add whitespace for the other columns
|
||||
traitNameColumn.Add(widget.NewLabel(""))
|
||||
quantityOfLociKnownColumn.Add(widget.NewLabel(""))
|
||||
viewTraitDetailsButtonsColumn.Add(widget.NewLabel(""))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
traitNameColumn.Add(widget.NewSeparator())
|
||||
userOutcomeScoresColumn.Add(widget.NewSeparator())
|
||||
offspringOutcomeScoresColumn.Add(widget.NewSeparator())
|
||||
userNumberOfRulesTestedColumn.Add(widget.NewSeparator())
|
||||
offspringNumberOfRulesTestedColumn.Add(widget.NewSeparator())
|
||||
userPredictedOutcomeColumn.Add(widget.NewSeparator())
|
||||
offspringOutcomeProbabilitiesColumn.Add(widget.NewSeparator())
|
||||
quantityOfLociKnownColumn.Add(widget.NewSeparator())
|
||||
viewTraitDetailsButtonsColumn.Add(widget.NewSeparator())
|
||||
}
|
||||
|
||||
userOutcomeScoresHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitOutcomeScoresExplainerPage(window, currentPage)
|
||||
if (userOrOffspring == "User"){
|
||||
|
||||
predictedOutcomeHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
|
||||
userPredictedOutcomeColumn.Add(predictedOutcomeHelpButton)
|
||||
|
||||
} else {
|
||||
// userOrOffspring == "Offspring"
|
||||
|
||||
outcomeProbabilitiesHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
|
||||
offspringOutcomeProbabilitiesColumn.Add(outcomeProbabilitiesHelpButton)
|
||||
}
|
||||
|
||||
quantityOfLociKnownHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
//TODO
|
||||
showUnderConstructionDialog(window)
|
||||
})
|
||||
|
||||
offspringOutcomeScoresHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringTraitOutcomeScoresExplainerPage(window, currentPage)
|
||||
})
|
||||
quantityOfLociKnownColumn.Add(quantityOfLociKnownHelpButton)
|
||||
|
||||
userNumberOfRulesTestedHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitNumberOfRulesTestedExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
offspringNumberOfRulesTestedHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setOffspringTraitNumberOfRulesTestedExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
userOutcomeScoresColumn.Add(userOutcomeScoresHelpButton)
|
||||
offspringOutcomeScoresColumn.Add(offspringOutcomeScoresHelpButton)
|
||||
userNumberOfRulesTestedColumn.Add(userNumberOfRulesTestedHelpButton)
|
||||
offspringNumberOfRulesTestedColumn.Add(offspringNumberOfRulesTestedHelpButton)
|
||||
traitsInfoGrid := container.NewHBox(layout.NewSpacer(), traitNameColumn)
|
||||
|
||||
if (userOrOffspring == "User"){
|
||||
traitsInfoGrid := container.NewHBox(layout.NewSpacer(), traitNameColumn, userOutcomeScoresColumn, userNumberOfRulesTestedColumn, viewTraitDetailsButtonsColumn, layout.NewSpacer())
|
||||
|
||||
return traitsInfoGrid, nil
|
||||
traitsInfoGrid.Add(userPredictedOutcomeColumn)
|
||||
|
||||
} else {
|
||||
|
||||
// userOrOffspring == "Offspring"
|
||||
|
||||
traitsInfoGrid.Add(offspringOutcomeProbabilitiesColumn)
|
||||
}
|
||||
traitsInfoGrid := container.NewHBox(layout.NewSpacer(), traitNameColumn, offspringOutcomeScoresColumn, offspringNumberOfRulesTestedColumn, viewTraitDetailsButtonsColumn, layout.NewSpacer())
|
||||
|
||||
traitsInfoGrid.Add(quantityOfLociKnownColumn)
|
||||
traitsInfoGrid.Add(viewTraitDetailsButtonsColumn)
|
||||
traitsInfoGrid.Add(layout.NewSpacer())
|
||||
|
||||
return traitsInfoGrid, nil
|
||||
}
|
||||
|
|
@ -3844,9 +3961,9 @@ func setViewMateProfilePage_GeneticTraits(window fyne.Window, userOrOffspring st
|
|||
setPageContent(page, window)
|
||||
}
|
||||
|
||||
func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, userOrOffspring string, getAnyUserProfileAttributeFunction func(string)(bool, int, string, error), previousPage func()){
|
||||
func setViewMateProfilePage_DiscreteTraitRules(window fyne.Window, traitName string, userOrOffspring string, getAnyUserProfileAttributeFunction func(string)(bool, int, string, error), previousPage func()){
|
||||
|
||||
currentPage := func(){setViewMateProfilePage_TraitRules(window, traitName, userOrOffspring, getAnyUserProfileAttributeFunction, previousPage)}
|
||||
currentPage := func(){setViewMateProfilePage_DiscreteTraitRules(window, traitName, userOrOffspring, getAnyUserProfileAttributeFunction, previousPage)}
|
||||
|
||||
title := getPageTitleCentered("View Profile - Physical")
|
||||
|
||||
|
|
@ -3868,7 +3985,7 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
// -bool: Any trait locus value exists for this myself
|
||||
// -map[int64]locusValue.LocusValue: My locus values map
|
||||
// -error
|
||||
getMyTraitLocusValuesMap := func()(bool, map[int64]locusValue.LocusValue, error){
|
||||
getMyGenomeLocusValuesMap := func()(bool, map[int64]locusValue.LocusValue, error){
|
||||
|
||||
myPersonChosen, myGenomesExist, myAnalysisIsReady, myAnalysisObject, myGenomeIdentifier, _, err := myChosenAnalysis.GetMyChosenMateGeneticAnalysis()
|
||||
if (err != nil) { return false, nil, err }
|
||||
|
|
@ -3878,17 +3995,18 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
return false, nil, nil
|
||||
}
|
||||
|
||||
myTraitLocusValuesMap, _, _, _, _, err := readGeneticAnalysis.GetPersonTraitInfoFromGeneticAnalysis(myAnalysisObject, traitName, myGenomeIdentifier)
|
||||
if (err != nil) { return false, nil, err }
|
||||
_, _, _, _, myGenomesMap, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(myAnalysisObject)
|
||||
if (err != nil){ return false, nil, err }
|
||||
|
||||
if (len(myTraitLocusValuesMap) == 0){
|
||||
return false, nil, nil
|
||||
myGenomeMap, exists := myGenomesMap[myGenomeIdentifier]
|
||||
if (exists == false){
|
||||
return false, nil, errors.New("GetMyChosenMateGeneticAnalysis returning analysis which does not contain genome matching myGenomeIdentifier")
|
||||
}
|
||||
|
||||
return true, myTraitLocusValuesMap, nil
|
||||
return true, myGenomeMap, nil
|
||||
}
|
||||
|
||||
anyMyTraitLocusValuesExist, myTraitLocusValuesMap, err := getMyTraitLocusValuesMap()
|
||||
anyMyLocusValuesExist, myLocusValuesMap, err := getMyGenomeLocusValuesMap()
|
||||
if (err != nil){
|
||||
setErrorEncounteredPage(window, err, previousPage)
|
||||
return
|
||||
|
|
@ -3900,9 +4018,14 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
return
|
||||
}
|
||||
|
||||
traitLociList := traitObject.LociList
|
||||
traitLociList_Rules := traitObject.LociList_Rules
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
if (len(traitRulesList) == 0){
|
||||
setErrorEncounteredPage(window, errors.New("setViewMateProfilePage_DiscreteTraitRules called with trait which has no rules."), previousPage)
|
||||
return
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
// -bool: Any trait locus value exists for this user
|
||||
// -map[int64]locusValue.LocusValue: User locus values map
|
||||
|
|
@ -3913,7 +4036,7 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
// Map Structure: Locus rsID -> locusValue.LocusValue
|
||||
userTraitLocusValuesMap := make(map[int64]locusValue.LocusValue)
|
||||
|
||||
for _, rsID := range traitLociList{
|
||||
for _, rsID := range traitLociList_Rules{
|
||||
|
||||
rsIDString := helpers.ConvertInt64ToString(rsID)
|
||||
|
||||
|
|
@ -3959,12 +4082,15 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
// -error
|
||||
getOffspringProbabilityOfPassingRulesMap := func()(bool, map[[3]byte]int, error){
|
||||
|
||||
if (anyMyTraitLocusValuesExist == false || anyUserTraitLocusValueExists == false){
|
||||
if (anyMyLocusValuesExist == false || anyUserTraitLocusValueExists == false){
|
||||
return false, nil, nil
|
||||
}
|
||||
|
||||
anyOffspringRulesTested, _, offspringProbabilityOfPassingRulesMap, _, err := createCoupleGeneticAnalysis.GetOffspringTraitInfo(traitObject, myTraitLocusValuesMap, userTraitLocusValuesMap)
|
||||
anyRulesExist, anyOffspringRulesTested, _, _, offspringProbabilityOfPassingRulesMap, _, err := createCoupleGeneticAnalysis.GetOffspringDiscreteTraitInfo_Rules(traitObject, myLocusValuesMap, userTraitLocusValuesMap)
|
||||
if (err != nil) { return false, nil, err }
|
||||
if (anyRulesExist == false){
|
||||
return false, nil, errors.New("GetOffspringDiscreteTraitInfo claiming no trait rules exist when we already checked.")
|
||||
}
|
||||
if (anyOffspringRulesTested == false){
|
||||
return false, nil, nil
|
||||
}
|
||||
|
|
@ -4000,7 +4126,7 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
|
||||
ruleLociList := ruleObject.LociList
|
||||
|
||||
ruleStatusIsKnown, _, err := createPersonGeneticAnalysis.GetGenomePassesTraitRuleStatus(ruleLociList, userTraitLocusValuesMap, true)
|
||||
ruleStatusIsKnown, _, err := createPersonGeneticAnalysis.GetGenomePassesDiscreteTraitRuleStatus(ruleLociList, userTraitLocusValuesMap, true)
|
||||
if (err != nil) { return 0, err }
|
||||
if (ruleStatusIsKnown == true){
|
||||
numberOfRulesTested += 1
|
||||
|
|
@ -4027,9 +4153,9 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
|
||||
numberOfRulesTestedHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
if (userOrOffspring == "User"){
|
||||
setTraitNumberOfRulesTestedExplainerPage(window, currentPage)
|
||||
setDiscreteTraitQuantityOfRulesTestedExplainerPage(window, currentPage)
|
||||
} else {
|
||||
setOffspringTraitNumberOfRulesTestedExplainerPage(window, currentPage)
|
||||
setOffspringDiscreteTraitQuantityOfRulesTestedExplainerPage(window, currentPage)
|
||||
}
|
||||
})
|
||||
|
||||
|
|
@ -4093,7 +4219,7 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
|
||||
getUserPassesRuleString := func()(string, error){
|
||||
|
||||
userRuleStatusIsKnown, userPassesRule, err := createPersonGeneticAnalysis.GetGenomePassesTraitRuleStatus(ruleLociList, userTraitLocusValuesMap, true)
|
||||
userRuleStatusIsKnown, userPassesRule, err := createPersonGeneticAnalysis.GetGenomePassesDiscreteTraitRuleStatus(ruleLociList, userTraitLocusValuesMap, true)
|
||||
if (err != nil) { return "", err }
|
||||
|
||||
if (userRuleStatusIsKnown == false){
|
||||
|
|
@ -4134,7 +4260,7 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
// We do this because the rule effects column may be multiple rows tall
|
||||
|
||||
viewRuleInfoButton := widget.NewButtonWithIcon("", theme.InfoIcon(), func(){
|
||||
setViewTraitRuleDetailsPage(window, traitName, ruleIdentifierHex, currentPage)
|
||||
setViewDiscreteTraitRuleDetailsPage(window, traitName, ruleIdentifierHex, currentPage)
|
||||
})
|
||||
ruleIdentifierLabel := getBoldLabelCentered(ruleIdentifierHex)
|
||||
userPassesRuleLabel := getBoldLabelCentered(userPassesRuleString)
|
||||
|
|
@ -4200,11 +4326,11 @@ func setViewMateProfilePage_TraitRules(window fyne.Window, traitName string, use
|
|||
}
|
||||
|
||||
ruleEffectsHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setTraitRuleOutcomeEffectsExplainerPage(window, currentPage)
|
||||
setDiscreteTraitRuleOutcomeEffectsExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
userPassesRuleHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
setPersonPassesTraitRuleExplainerPage(window, currentPage)
|
||||
setPersonPassesDiscreteTraitRuleExplainerPage(window, currentPage)
|
||||
})
|
||||
|
||||
offspringProbabilityOfPassingRuleHelpButton := widget.NewButtonWithIcon("", theme.QuestionIcon(), func(){
|
||||
|
|
@ -4491,29 +4617,29 @@ func get23andMeAncestryCompositionDisplay(inputContinentPercentagesMap map[strin
|
|||
// We sort region subregions list
|
||||
// We sort them from highest to lowest in percentage.
|
||||
|
||||
compareSubregionsFunction := func(subregionADescription string, subregionBDescription string)int{
|
||||
compareSubregionsFunction := func(subregion1Description string, subregion2Description string)int{
|
||||
|
||||
if (subregionADescription == subregionBDescription){
|
||||
if (subregion1Description == subregion2Description){
|
||||
panic("compareSubregionsFunction called with identical subregion descriptions.")
|
||||
}
|
||||
|
||||
subregionAPercentage, exists := subregionDescriptionPercentagesMap[subregionADescription]
|
||||
subregion1Percentage, exists := subregionDescriptionPercentagesMap[subregion1Description]
|
||||
if (exists == false){
|
||||
panic("subregionPercentagesMap missing subregion during sort.")
|
||||
}
|
||||
|
||||
subregionBPercentage, exists := subregionDescriptionPercentagesMap[subregionBDescription]
|
||||
subregion2Percentage, exists := subregionDescriptionPercentagesMap[subregion2Description]
|
||||
if (exists == false){
|
||||
panic("subregionPercentagesMap missing subregion during sort.")
|
||||
}
|
||||
if (subregionAPercentage == subregionBPercentage){
|
||||
if (subregion1Percentage == subregion2Percentage){
|
||||
// We sort subregions in unicode order
|
||||
if (subregionADescription < subregionBDescription){
|
||||
if (subregion1Description < subregion2Description){
|
||||
return -1
|
||||
}
|
||||
return 1
|
||||
}
|
||||
if (subregionAPercentage > subregionBPercentage){
|
||||
if (subregion1Percentage > subregion2Percentage){
|
||||
return -1
|
||||
}
|
||||
|
||||
|
|
@ -4527,32 +4653,33 @@ func get23andMeAncestryCompositionDisplay(inputContinentPercentagesMap map[strin
|
|||
|
||||
// We sort continent regions list by highest to lowest percentage.
|
||||
|
||||
compareRegionsFunction := func(regionADescription string, regionBDescription string)int{
|
||||
compareRegionsFunction := func(region1Description string, region2Description string)int{
|
||||
|
||||
if (regionADescription == regionBDescription){
|
||||
if (region1Description == region2Description){
|
||||
panic("compareRegionsFunction called with identical regions.")
|
||||
}
|
||||
|
||||
regionAPercentage, exists := regionDescriptionPercentagesMap[regionADescription]
|
||||
region1Percentage, exists := regionDescriptionPercentagesMap[region1Description]
|
||||
if (exists == false){
|
||||
panic("regionPercentagesMap missing subregion during sort.")
|
||||
}
|
||||
|
||||
regionBPercentage, exists := regionDescriptionPercentagesMap[regionBDescription]
|
||||
region2Percentage, exists := regionDescriptionPercentagesMap[region2Description]
|
||||
if (exists == false){
|
||||
panic("regionPercentagesMap missing subregion during sort.")
|
||||
}
|
||||
if (regionAPercentage == regionBPercentage){
|
||||
if (region1Percentage == region2Percentage){
|
||||
// We sort regions in unicode order
|
||||
if (regionADescription < regionBDescription){
|
||||
if (region1Description < region2Description){
|
||||
return -1
|
||||
}
|
||||
return 1
|
||||
}
|
||||
|
||||
if (regionAPercentage > regionBPercentage){
|
||||
if (region1Percentage > region2Percentage){
|
||||
return -1
|
||||
}
|
||||
|
||||
return 1
|
||||
}
|
||||
|
||||
|
|
@ -4563,29 +4690,29 @@ func get23andMeAncestryCompositionDisplay(inputContinentPercentagesMap map[strin
|
|||
|
||||
// We sort root list by highest to lowest proportions
|
||||
|
||||
compareContinentsFunction := func(continentADescription string, continentBDescription string)int{
|
||||
compareContinentsFunction := func(continent1Description string, continent2Description string)int{
|
||||
|
||||
if (continentADescription == continentBDescription){
|
||||
if (continent1Description == continent2Description){
|
||||
panic("compareContinentsFunction called with identical continents.")
|
||||
}
|
||||
|
||||
continentAPercentage, exists := continentDescriptionPercentagesMap[continentADescription]
|
||||
continent1Percentage, exists := continentDescriptionPercentagesMap[continent1Description]
|
||||
if (exists == false){
|
||||
panic("Continent percentage not found when sorting root list.")
|
||||
}
|
||||
|
||||
continentBPercentage, exists := continentDescriptionPercentagesMap[continentBDescription]
|
||||
continent2Percentage, exists := continentDescriptionPercentagesMap[continent2Description]
|
||||
if (exists == false){
|
||||
panic("Continent percentage not found when sorting root list.")
|
||||
}
|
||||
if (continentAPercentage == continentBPercentage){
|
||||
if (continent1Percentage == continent2Percentage){
|
||||
// We sort continents in unicode order
|
||||
if (continentADescription < continentBDescription){
|
||||
if (continent1Description < continent2Description){
|
||||
return -1
|
||||
}
|
||||
return 1
|
||||
}
|
||||
if (continentAPercentage > continentBPercentage){
|
||||
if (continent1Percentage > continent2Percentage){
|
||||
return -1
|
||||
}
|
||||
return 1
|
||||
|
|
|
|||
|
|
@ -932,7 +932,7 @@ func GetFakeProfile(profileType string, identityPublicKey [32]byte, identityPriv
|
|||
|
||||
traitLociList := traitObject.LociList
|
||||
|
||||
for _, rsID := range traitLociList{
|
||||
for _, rsID := range traitLociList{
|
||||
|
||||
shareableRSIDsMap[rsID] = struct{}{}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -9,21 +9,10 @@ package createCoupleGeneticAnalysis
|
|||
|
||||
// Disclaimer: I am a novice in the ways of genetics. This package could be flawed in numerous ways.
|
||||
|
||||
// TODO: We want to eventually use neural nets for both trait and polygenic disease analysis (see geneticPrediction.go)
|
||||
// These will be trained on a set of genomes and will output a probability analysis for each trait/disease
|
||||
// TODO: We want to eventually use neural nets for polygenic disease analysis (see geneticPrediction.go)
|
||||
// This is only possible once we get access to the necessary training data
|
||||
//
|
||||
// This is how offspring trait prediction could work with the neural net model:
|
||||
// Both users will share all relevant SNPS base pairs that determine the trait on their profile.
|
||||
// Each location has 4 possible outcomes, so for 1000 SNPs, there are 4^1000 possible offspring outcomes for a given couple. (this
|
||||
// is actually too high because recombination break points do not occur at each locus, see genetic linkage)
|
||||
// This is too many options for us to check all of them.
|
||||
// Seekia will create 100 offspring that would be produced from both users, and run each offspring through the neural net.
|
||||
// Each offspring would be different. The allele from each parent for each SNP would be randomly chosen.
|
||||
// The user can choose how many prospective offspring to create in the settings.
|
||||
// More offspring will take longer, but will yield a more accurate trait probability.
|
||||
// Seekia will show the the average trait result and a chart showing the trait results for all created offspring.
|
||||
|
||||
import "seekia/resources/geneticPredictionModels"
|
||||
import "seekia/resources/geneticReferences/locusMetadata"
|
||||
import "seekia/resources/geneticReferences/monogenicDiseases"
|
||||
import "seekia/resources/geneticReferences/polygenicDiseases"
|
||||
|
|
@ -40,6 +29,7 @@ import "errors"
|
|||
import mathRand "math/rand/v2"
|
||||
import "slices"
|
||||
import "maps"
|
||||
import "reflect"
|
||||
|
||||
|
||||
//Outputs:
|
||||
|
|
@ -86,6 +76,30 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
return false, "", nil
|
||||
}
|
||||
|
||||
// This map stores each genome's locus values
|
||||
// Map Structure: Genome Identifier -> Genome locus values map (rsID -> Locus Value)
|
||||
person1GenomesMap := make(map[[16]byte]map[int64]locusValue.LocusValue)
|
||||
|
||||
for _, genomeWithMetadata := range person1GenomesWithMetadataList{
|
||||
|
||||
genomeIdentifier := genomeWithMetadata.GenomeIdentifier
|
||||
genomeMap := genomeWithMetadata.GenomeMap
|
||||
|
||||
person1GenomesMap[genomeIdentifier] = genomeMap
|
||||
}
|
||||
|
||||
// This map stores each genome's locus values
|
||||
// Map Structure: Genome Identifier -> Genome locus values map (rsID -> Locus Value)
|
||||
person2GenomesMap := make(map[[16]byte]map[int64]locusValue.LocusValue)
|
||||
|
||||
for _, genomeWithMetadata := range person2GenomesWithMetadataList{
|
||||
|
||||
genomeIdentifier := genomeWithMetadata.GenomeIdentifier
|
||||
genomeMap := genomeWithMetadata.GenomeMap
|
||||
|
||||
person2GenomesMap[genomeIdentifier] = genomeMap
|
||||
}
|
||||
|
||||
// The analysis will analyze either 1 or 2 genome pairs
|
||||
// The gui will display the results from each pair
|
||||
//Outputs:
|
||||
|
|
@ -172,9 +186,9 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
person2DiseaseAnalysisObject, err := createPersonGeneticAnalysis.GetPersonMonogenicDiseaseAnalysis(person2GenomesWithMetadataList, diseaseObject)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
// This map stores the number of variants tested in each person's genome
|
||||
// This map stores the quantity of variants tested in each person's genome
|
||||
// Map Structure: Genome Identifier -> Number of variants tested
|
||||
numberOfVariantsTestedMap := make(map[[16]byte]int)
|
||||
quantityOfVariantsTestedMap := make(map[[16]byte]int)
|
||||
|
||||
// This map stores the offspring disease probabilities for each genome pair.
|
||||
// A genome pair is a concatenation of two genome identifiers
|
||||
|
|
@ -184,7 +198,7 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
|
||||
// This will calculate the probability of monogenic disease for the offspring from the two specified genomes
|
||||
// It also calculates the probabilities for each monogenic disease variant for the offspring
|
||||
// It then adds the genome pair disease information to the offspringMonogenicDiseaseInfoMap and numberOfVariantsTestedMap
|
||||
// It then adds the genome pair disease information to the offspringMonogenicDiseaseInfoMap and quantityOfVariantsTestedMap
|
||||
addGenomePairInfoToDiseaseMaps := func(person1GenomeIdentifier [16]byte, person2GenomeIdentifier [16]byte)error{
|
||||
|
||||
//Outputs:
|
||||
|
|
@ -202,9 +216,9 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
|
||||
personGenomeProbabilityOfPassingADiseaseVariant := personGenomeDiseaseInfoObject.ProbabilityOfPassingADiseaseVariant
|
||||
|
||||
personGenomeNumberOfVariantsTested := personGenomeDiseaseInfoObject.NumberOfVariantsTested
|
||||
personGenomeQuantityOfVariantsTested := personGenomeDiseaseInfoObject.QuantityOfVariantsTested
|
||||
|
||||
return true, personGenomeProbabilityOfPassingADiseaseVariant, personGenomeNumberOfVariantsTested
|
||||
return true, personGenomeProbabilityOfPassingADiseaseVariant, personGenomeQuantityOfVariantsTested
|
||||
}
|
||||
|
||||
person1ProbabilityIsKnown, person1WillPassVariantProbability, person1NumberOfVariantsTested := getPersonWillPassDiseaseVariantProbability(person1DiseaseAnalysisObject, person1GenomeIdentifier)
|
||||
|
|
@ -362,8 +376,8 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
return nil
|
||||
}
|
||||
|
||||
numberOfVariantsTestedMap[person1GenomeIdentifier] = person1NumberOfVariantsTested
|
||||
numberOfVariantsTestedMap[person2GenomeIdentifier] = person2NumberOfVariantsTested
|
||||
quantityOfVariantsTestedMap[person1GenomeIdentifier] = person1NumberOfVariantsTested
|
||||
quantityOfVariantsTestedMap[person2GenomeIdentifier] = person2NumberOfVariantsTested
|
||||
|
||||
newOffspringGenomePairMonogenicDiseaseInfoObject := geneticAnalysis.OffspringGenomePairMonogenicDiseaseInfo{
|
||||
ProbabilityOffspringHasDiseaseIsKnown: offspringHasDiseaseProbabilityIsKnown,
|
||||
|
|
@ -390,7 +404,7 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
}
|
||||
|
||||
newOffspringMonogenicDiseaseInfoObject := geneticAnalysis.OffspringMonogenicDiseaseInfo{
|
||||
NumberOfVariantsTestedMap: numberOfVariantsTestedMap,
|
||||
QuantityOfVariantsTestedMap: quantityOfVariantsTestedMap,
|
||||
MonogenicDiseaseInfoMap: offspringMonogenicDiseaseInfoMap,
|
||||
}
|
||||
|
||||
|
|
@ -480,12 +494,6 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
diseaseName := diseaseObject.DiseaseName
|
||||
diseaseLociList := diseaseObject.LociList
|
||||
|
||||
person1DiseaseAnalysisObject, err := createPersonGeneticAnalysis.GetPersonPolygenicDiseaseAnalysis(person1GenomesWithMetadataList, diseaseObject)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
person2DiseaseAnalysisObject, err := createPersonGeneticAnalysis.GetPersonPolygenicDiseaseAnalysis(person2GenomesWithMetadataList, diseaseObject)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
// This map stores the polygenic disease info for each genome pair
|
||||
// Map Structure: Genome Pair Identifier -> OffspringGenomePairPolygenicDiseaseInfo
|
||||
offspringPolygenicDiseaseInfoMap := make(map[[32]byte]geneticAnalysis.OffspringGenomePairPolygenicDiseaseInfo)
|
||||
|
|
@ -494,40 +502,17 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
// It then adds the pair entry to the offspringPolygenicDiseaseInfoMap
|
||||
addGenomePairDiseaseInfoToDiseaseMap := func(person1GenomeIdentifier [16]byte, person2GenomeIdentifier [16]byte)error{
|
||||
|
||||
//Outputs:
|
||||
// -bool: Any locus values exist
|
||||
// -map[int64]locusValue.LocusValue
|
||||
// -error
|
||||
getPersonGenomeDiseaseLocusValuesMap := func(personGenomeIdentifier [16]byte, personDiseaseAnalysisObject geneticAnalysis.PersonPolygenicDiseaseInfo)(bool, map[int64]locusValue.LocusValue, error){
|
||||
|
||||
personPolygenicDiseaseInfoMap := personDiseaseAnalysisObject.PolygenicDiseaseInfoMap
|
||||
|
||||
personGenomeDiseaseInfoObject, exists := personPolygenicDiseaseInfoMap[personGenomeIdentifier]
|
||||
if (exists == false){
|
||||
// This person's genome has no information about loci related to this disease
|
||||
return false, nil, nil
|
||||
}
|
||||
|
||||
personGenomeLocusValuesMap := personGenomeDiseaseInfoObject.LocusValuesMap
|
||||
|
||||
return true, personGenomeLocusValuesMap, nil
|
||||
person1LocusValuesMap, exists := person1GenomesMap[person1GenomeIdentifier]
|
||||
if (exists == false){
|
||||
return errors.New("addGenomePairDiseaseInfoToDiseaseMap called with unknown person1GenomeIdentifier.")
|
||||
}
|
||||
|
||||
anyPerson1LociValuesExist, person1LocusValuesMap, err := getPersonGenomeDiseaseLocusValuesMap(person1GenomeIdentifier, person1DiseaseAnalysisObject)
|
||||
if (err != nil) { return err }
|
||||
if (anyPerson1LociValuesExist == false){
|
||||
// Offspring's disease info for this locus on this genome pair is unknown
|
||||
return nil
|
||||
person2LocusValuesMap, exists := person2GenomesMap[person2GenomeIdentifier]
|
||||
if (exists == false){
|
||||
return errors.New("addGenomePairDiseaseInfoToDiseaseMap called with unknown person2GenomeIdentifier.")
|
||||
}
|
||||
|
||||
anyPerson2LociValuesExist, person2LocusValuesMap, err := getPersonGenomeDiseaseLocusValuesMap(person2GenomeIdentifier, person2DiseaseAnalysisObject)
|
||||
if (err != nil) { return err }
|
||||
if (anyPerson2LociValuesExist == false){
|
||||
// Offspring's disease info for this locus on this genome pair is unknown
|
||||
return nil
|
||||
}
|
||||
|
||||
anyOffspringLocusTested, genomePairOffspringAverageRiskScore, numberOfLociTested, genomePairOffspringDiseaseLociInfoMap, genomePairSampleOffspringRiskScoresList, err := GetOffspringPolygenicDiseaseInfo(diseaseLociList, person1LocusValuesMap, person2LocusValuesMap)
|
||||
anyOffspringLocusTested, genomePairOffspringAverageRiskScore, quantityOfLociTested, genomePairOffspringDiseaseLociInfoMap, genomePairSampleOffspringRiskScoresList, err := GetOffspringPolygenicDiseaseInfo(diseaseLociList, person1LocusValuesMap, person2LocusValuesMap)
|
||||
if (err != nil) { return err }
|
||||
if (anyOffspringLocusTested == false){
|
||||
// We have no information about this genome pair's disease risk
|
||||
|
|
@ -537,7 +522,7 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
|
||||
newOffspringGenomePairPolygenicDiseaseInfo := geneticAnalysis.OffspringGenomePairPolygenicDiseaseInfo{
|
||||
|
||||
NumberOfLociTested: numberOfLociTested,
|
||||
QuantityOfLociTested: quantityOfLociTested,
|
||||
OffspringAverageRiskScore: genomePairOffspringAverageRiskScore,
|
||||
LociInfoMap: genomePairOffspringDiseaseLociInfoMap,
|
||||
SampleOffspringRiskScoresList: genomePairSampleOffspringRiskScoresList,
|
||||
|
|
@ -570,34 +555,20 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
|
||||
checkIfConflictExists := func()(bool, error){
|
||||
|
||||
numberOfLociTested := 0
|
||||
offspringAverageRiskScore := 0
|
||||
offspringLociInfoMap := make(map[[3]byte]geneticAnalysis.OffspringPolygenicDiseaseLocusInfo)
|
||||
currentGenomePairPolygenicDiseaseInfo := geneticAnalysis.OffspringGenomePairPolygenicDiseaseInfo{}
|
||||
|
||||
firstItemReached := false
|
||||
|
||||
for _, genomePairDiseaseInfoObject := range offspringPolygenicDiseaseInfoMap{
|
||||
|
||||
genomePairNumberOfLociTested := genomePairDiseaseInfoObject.NumberOfLociTested
|
||||
genomePairOffspringAverageRiskScore := genomePairDiseaseInfoObject.OffspringAverageRiskScore
|
||||
genomePairLociInfoMap := genomePairDiseaseInfoObject.LociInfoMap
|
||||
|
||||
if (firstItemReached == false){
|
||||
numberOfLociTested = genomePairNumberOfLociTested
|
||||
offspringAverageRiskScore = genomePairOffspringAverageRiskScore
|
||||
offspringLociInfoMap = genomePairLociInfoMap
|
||||
currentGenomePairPolygenicDiseaseInfo = genomePairDiseaseInfoObject
|
||||
firstItemReached = true
|
||||
continue
|
||||
}
|
||||
if (numberOfLociTested != genomePairNumberOfLociTested){
|
||||
return true, nil
|
||||
}
|
||||
if (offspringAverageRiskScore != genomePairOffspringAverageRiskScore){
|
||||
return true, nil
|
||||
}
|
||||
areEqual := maps.Equal(offspringLociInfoMap, genomePairLociInfoMap)
|
||||
|
||||
areEqual := reflect.DeepEqual(genomePairDiseaseInfoObject, currentGenomePairPolygenicDiseaseInfo)
|
||||
if (areEqual == false){
|
||||
// A conflict exists
|
||||
return true, nil
|
||||
}
|
||||
}
|
||||
|
|
@ -622,128 +593,140 @@ func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenom
|
|||
if (err != nil) { return false, "", err }
|
||||
|
||||
// Map Structure: Trait Name -> Trait Info Object
|
||||
offspringTraitsMap := make(map[string]geneticAnalysis.OffspringTraitInfo)
|
||||
offspringDiscreteTraitsMap := make(map[string]geneticAnalysis.OffspringDiscreteTraitInfo)
|
||||
|
||||
// Map Structure: Trait Name -> Trait Info Object
|
||||
offspringNumericTraitsMap := make(map[string]geneticAnalysis.OffspringNumericTraitInfo)
|
||||
|
||||
for _, traitObject := range traitObjectsList{
|
||||
|
||||
traitName := traitObject.TraitName
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
|
||||
person1TraitAnalysisObject, err := createPersonGeneticAnalysis.GetPersonTraitAnalysis(person1GenomesWithMetadataList, traitObject)
|
||||
if (err != nil) { return false, "", err }
|
||||
if (traitIsDiscreteOrNumeric == "Discrete"){
|
||||
|
||||
person2TraitAnalysisObject, err := createPersonGeneticAnalysis.GetPersonTraitAnalysis(person2GenomesWithMetadataList, traitObject)
|
||||
if (err != nil) { return false, "", err }
|
||||
// This map stores the trait info for each genome pair
|
||||
// Map Structure: Genome Pair Identifier -> OffspringGenomePairDiscreteTraitInfo
|
||||
offspringTraitInfoMap := make(map[[32]byte]geneticAnalysis.OffspringGenomePairDiscreteTraitInfo)
|
||||
|
||||
// This map stores the trait info for each genome pair
|
||||
// Map Structure: Genome Pair Identifier -> OffspringGenomePairTraitInfo
|
||||
offspringTraitInfoMap := make(map[[32]byte]geneticAnalysis.OffspringGenomePairTraitInfo)
|
||||
// This will add the offspring trait information for the provided genome pair to the offspringTraitInfoMap
|
||||
addGenomePairTraitInfoToOffspringMap := func(person1GenomeIdentifier [16]byte, person2GenomeIdentifier [16]byte)error{
|
||||
|
||||
// This will add the offspring trait information for the provided genome pair to the offspringTraitInfoMap
|
||||
addGenomePairTraitInfoToOffspringMap := func(person1GenomeIdentifier [16]byte, person2GenomeIdentifier [16]byte)error{
|
||||
person1LocusValuesMap, exists := person1GenomesMap[person1GenomeIdentifier]
|
||||
if (exists == false){
|
||||
return errors.New("addGenomePairTraitInfoToOffspringMap called with unknown person1GenomeIdentifier.")
|
||||
}
|
||||
|
||||
person1TraitInfoMap := person1TraitAnalysisObject.TraitInfoMap
|
||||
person2TraitInfoMap := person2TraitAnalysisObject.TraitInfoMap
|
||||
person2LocusValuesMap, exists := person2GenomesMap[person2GenomeIdentifier]
|
||||
if (exists == false){
|
||||
return errors.New("addGenomePairTraitInfoToOffspringMap called with unknown person2GenomeIdentifier.")
|
||||
}
|
||||
|
||||
person1GenomeTraitInfoObject, exists := person1TraitInfoMap[person1GenomeIdentifier]
|
||||
if (exists == false){
|
||||
// This person has no genome values for any loci for this trait
|
||||
// No predictions are possible
|
||||
return nil
|
||||
}
|
||||
person2GenomeTraitInfoObject, exists := person2TraitInfoMap[person2GenomeIdentifier]
|
||||
if (exists == false){
|
||||
// This person has no genome values for any loci for this trait
|
||||
// No predictions are possible
|
||||
return nil
|
||||
}
|
||||
newOffspringGenomePairTraitInfo := geneticAnalysis.OffspringGenomePairDiscreteTraitInfo{}
|
||||
|
||||
person1LocusValuesMap := person1GenomeTraitInfoObject.LocusValuesMap
|
||||
person2LocusValuesMap := person2GenomeTraitInfoObject.LocusValuesMap
|
||||
neuralNetworkExists, neuralNetworkAnalysisExists, outcomeProbabilitiesMap, averagePredictionConfidence, quantityOfLociTested, quantityOfParentalPhasedLoci, err := GetOffspringDiscreteTraitInfo_NeuralNetwork(traitObject, person1LocusValuesMap, person2LocusValuesMap)
|
||||
if (err != nil) { return err }
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
anyRulesTested, numberOfRulesTested, offspringProbabilityOfPassingRulesMap, offspringAverageOutcomeScoresMap, err := GetOffspringTraitInfo(traitObject, person1LocusValuesMap, person2LocusValuesMap)
|
||||
if (err != nil) { return err }
|
||||
if (anyRulesTested == false){
|
||||
// No rules were tested for this trait
|
||||
// We will not add anything to the trait info map for this genome pair
|
||||
return nil
|
||||
}
|
||||
newOffspringGenomePairTraitInfo.NeuralNetworkExists = true
|
||||
|
||||
newOffspringGenomePairTraitInfoObject := geneticAnalysis.OffspringGenomePairTraitInfo{
|
||||
NumberOfRulesTested: numberOfRulesTested,
|
||||
OffspringAverageOutcomeScoresMap: offspringAverageOutcomeScoresMap,
|
||||
ProbabilityOfPassingRulesMap: offspringProbabilityOfPassingRulesMap,
|
||||
}
|
||||
if (neuralNetworkAnalysisExists == true){
|
||||
newOffspringGenomePairTraitInfo.NeuralNetworkAnalysisExists = true
|
||||
|
||||
genomePairIdentifier := helpers.JoinTwo16ByteArrays(person1GenomeIdentifier, person2GenomeIdentifier)
|
||||
newOffspringGenomePairTraitInfo_NeuralNetwork := geneticAnalysis.OffspringGenomePairDiscreteTraitInfo_NeuralNetwork{
|
||||
|
||||
offspringTraitInfoMap[genomePairIdentifier] = newOffspringGenomePairTraitInfoObject
|
||||
OffspringOutcomeProbabilitiesMap: outcomeProbabilitiesMap,
|
||||
AverageConfidence: averagePredictionConfidence,
|
||||
QuantityOfLociKnown: quantityOfLociTested,
|
||||
QuantityOfParentalPhasedLoci: quantityOfParentalPhasedLoci,
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
err = addGenomePairTraitInfoToOffspringMap(pair1Person1GenomeIdentifier, pair1Person2GenomeIdentifier)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
if (genomePair2Exists == true){
|
||||
|
||||
err := addGenomePairTraitInfoToOffspringMap(pair2Person1GenomeIdentifier, pair2Person2GenomeIdentifier)
|
||||
if (err != nil) { return false, "", err }
|
||||
}
|
||||
|
||||
newOffspringTraitInfoObject := geneticAnalysis.OffspringTraitInfo{
|
||||
TraitInfoMap: offspringTraitInfoMap,
|
||||
}
|
||||
|
||||
if (len(offspringTraitInfoMap) >= 2){
|
||||
|
||||
// We check for conflicts
|
||||
// Conflicts are only possible if two genome pairs exist with information about the trait
|
||||
|
||||
checkIfConflictExists := func()(bool, error){
|
||||
|
||||
// We check for conflicts between each genome pair's outcome scores and trait rules maps
|
||||
|
||||
offspringAverageOutcomeScoresMap := make(map[string]float64)
|
||||
offspringProbabilityOfPassingRulesMap := make(map[[3]byte]int)
|
||||
|
||||
firstItemReached := false
|
||||
|
||||
for _, genomePairTraitInfoObject := range offspringTraitInfoMap{
|
||||
|
||||
currentOffspringAverageOutcomeScoresMap := genomePairTraitInfoObject.OffspringAverageOutcomeScoresMap
|
||||
currentProbabilityOfPassingRulesMap := genomePairTraitInfoObject.ProbabilityOfPassingRulesMap
|
||||
|
||||
if (firstItemReached == false){
|
||||
offspringAverageOutcomeScoresMap = currentOffspringAverageOutcomeScoresMap
|
||||
offspringProbabilityOfPassingRulesMap = currentProbabilityOfPassingRulesMap
|
||||
|
||||
firstItemReached = true
|
||||
continue
|
||||
}
|
||||
|
||||
areEqual := maps.Equal(offspringAverageOutcomeScoresMap, currentOffspringAverageOutcomeScoresMap)
|
||||
if (areEqual == false){
|
||||
return true, nil
|
||||
}
|
||||
areEqual = maps.Equal(offspringProbabilityOfPassingRulesMap, currentProbabilityOfPassingRulesMap)
|
||||
if (areEqual == false){
|
||||
return true, nil
|
||||
newOffspringGenomePairTraitInfo.NeuralNetworkAnalysis = newOffspringGenomePairTraitInfo_NeuralNetwork
|
||||
}
|
||||
}
|
||||
|
||||
return false, nil
|
||||
anyRulesExist, rulesAnalysisExists, quantityOfRulesTested, quantityOfLociKnown, offspringProbabilityOfPassingRulesMap, offspringOutcomeProbabilitiesMap, err := GetOffspringDiscreteTraitInfo_Rules(traitObject, person1LocusValuesMap, person2LocusValuesMap)
|
||||
if (err != nil) { return err }
|
||||
if (anyRulesExist == true){
|
||||
|
||||
newOffspringGenomePairTraitInfo.RulesExist = true
|
||||
|
||||
if (rulesAnalysisExists == true){
|
||||
newOffspringGenomePairTraitInfo.RulesAnalysisExists = true
|
||||
|
||||
newOffspringGenomePairTraitInfo_Rules := geneticAnalysis.OffspringGenomePairDiscreteTraitInfo_Rules{
|
||||
QuantityOfRulesTested: quantityOfRulesTested,
|
||||
QuantityOfLociKnown: quantityOfLociKnown,
|
||||
ProbabilityOfPassingRulesMap: offspringProbabilityOfPassingRulesMap,
|
||||
OffspringOutcomeProbabilitiesMap: offspringOutcomeProbabilitiesMap,
|
||||
}
|
||||
|
||||
newOffspringGenomePairTraitInfo.RulesAnalysis = newOffspringGenomePairTraitInfo_Rules
|
||||
}
|
||||
}
|
||||
|
||||
genomePairIdentifier := helpers.JoinTwo16ByteArrays(person1GenomeIdentifier, person2GenomeIdentifier)
|
||||
|
||||
offspringTraitInfoMap[genomePairIdentifier] = newOffspringGenomePairTraitInfo
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
conflictExists, err := checkIfConflictExists()
|
||||
err = addGenomePairTraitInfoToOffspringMap(pair1Person1GenomeIdentifier, pair1Person2GenomeIdentifier)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
newOffspringTraitInfoObject.ConflictExists = conflictExists
|
||||
}
|
||||
if (genomePair2Exists == true){
|
||||
|
||||
offspringTraitsMap[traitName] = newOffspringTraitInfoObject
|
||||
err := addGenomePairTraitInfoToOffspringMap(pair2Person1GenomeIdentifier, pair2Person2GenomeIdentifier)
|
||||
if (err != nil) { return false, "", err }
|
||||
}
|
||||
|
||||
newOffspringTraitInfoObject := geneticAnalysis.OffspringDiscreteTraitInfo{
|
||||
TraitInfoMap: offspringTraitInfoMap,
|
||||
}
|
||||
|
||||
if (len(offspringTraitInfoMap) >= 2){
|
||||
|
||||
// We check for conflicts
|
||||
// Conflicts are only possible if two genome pairs exist with information about the trait
|
||||
|
||||
checkIfConflictExists := func()(bool, error){
|
||||
|
||||
// We check for conflicts between each genome pair's outcome scores and trait rules maps
|
||||
|
||||
genomePairTraitInfoObject := geneticAnalysis.OffspringGenomePairDiscreteTraitInfo{}
|
||||
|
||||
firstItemReached := false
|
||||
|
||||
for _, currentGenomePairTraitInfoObject := range offspringTraitInfoMap{
|
||||
|
||||
if (firstItemReached == false){
|
||||
genomePairTraitInfoObject = currentGenomePairTraitInfoObject
|
||||
firstItemReached = true
|
||||
continue
|
||||
}
|
||||
|
||||
areEqual := reflect.DeepEqual(genomePairTraitInfoObject, currentGenomePairTraitInfoObject)
|
||||
if (areEqual == false){
|
||||
return true, nil
|
||||
}
|
||||
}
|
||||
|
||||
return false, nil
|
||||
}
|
||||
|
||||
conflictExists, err := checkIfConflictExists()
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
newOffspringTraitInfoObject.ConflictExists = conflictExists
|
||||
}
|
||||
|
||||
offspringDiscreteTraitsMap[traitName] = newOffspringTraitInfoObject
|
||||
}
|
||||
}
|
||||
|
||||
newCoupleAnalysis.TraitsMap = offspringTraitsMap
|
||||
newCoupleAnalysis.DiscreteTraitsMap = offspringDiscreteTraitsMap
|
||||
newCoupleAnalysis.NumericTraitsMap = offspringNumericTraitsMap
|
||||
|
||||
analysisBytes, err := encoding.EncodeMessagePackBytes(newCoupleAnalysis)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
|
@ -1136,144 +1119,187 @@ func GetOffspringPolygenicDiseaseInfo(diseaseLociList []polygenicDiseases.Diseas
|
|||
|
||||
|
||||
//Outputs:
|
||||
// -bool: Any rules tested (if false, no offspring trait information is known)
|
||||
// -int: Number of rules tested
|
||||
// -bool: A neural network exists for this trait
|
||||
// -bool: Analysis exists (at least 1 locus exists for this analysis from both people's genomes
|
||||
// -map[string]int: Outcome probabilities map
|
||||
// Map Structure: Outcome Name -> Offspring probability of outcome
|
||||
// -int: Average prediction confidence (the average prediction confidence for all prospective offspring)
|
||||
// -int: Quantity of loci tested
|
||||
// -int: Quantity of parental phased loci
|
||||
// -error
|
||||
func GetOffspringDiscreteTraitInfo_NeuralNetwork(traitObject traits.Trait, person1LocusValuesMap map[int64]locusValue.LocusValue, person2LocusValuesMap map[int64]locusValue.LocusValue)(bool, bool, map[string]int, int, int, int, error){
|
||||
|
||||
traitName := traitObject.TraitName
|
||||
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
if (traitIsDiscreteOrNumeric != "Discrete"){
|
||||
return false, false, nil, 0, 0, 0, errors.New("GetOffspringDiscreteTraitInfo_NeuralNetwork called with non-discrete trait.")
|
||||
}
|
||||
|
||||
modelExists, _ := geneticPredictionModels.GetGeneticPredictionModelBytes(traitName)
|
||||
if (modelExists == false){
|
||||
// Neural network prediction is not possible for this trait
|
||||
return false, false, nil, 0, 0, 0, nil
|
||||
}
|
||||
|
||||
traitLociList := traitObject.LociList
|
||||
|
||||
// First we count up the quantity of parental phased loci
|
||||
// We only count the quantity of phased loci for loci which are known for both parents
|
||||
|
||||
quantityOfParentalPhasedLoci := 0
|
||||
|
||||
for _, rsID := range traitLociList{
|
||||
|
||||
person1LocusValue, exists := person1LocusValuesMap[rsID]
|
||||
if (exists == false){
|
||||
continue
|
||||
}
|
||||
|
||||
person2LocusValue, exists := person2LocusValuesMap[rsID]
|
||||
if (exists == false){
|
||||
continue
|
||||
}
|
||||
|
||||
person1LocusIsPhased := person1LocusValue.LocusIsPhased
|
||||
if (person1LocusIsPhased == true){
|
||||
quantityOfParentalPhasedLoci += 1
|
||||
}
|
||||
|
||||
person2LocusIsPhased := person2LocusValue.LocusIsPhased
|
||||
if (person2LocusIsPhased == true){
|
||||
quantityOfParentalPhasedLoci += 1
|
||||
}
|
||||
}
|
||||
|
||||
// Next, we create 100 prospective offspring genomes.
|
||||
|
||||
anyLocusValueExists, prospectiveOffspringGenomesList, err := getProspectiveOffspringGenomesList(traitLociList, person1LocusValuesMap, person2LocusValuesMap)
|
||||
if (err != nil) { return false, false, nil, 0, 0, 0, err }
|
||||
if (anyLocusValueExists == false){
|
||||
return true, false, nil, 0, 0, 0, nil
|
||||
}
|
||||
|
||||
// Map Structure: Outcome Name -> Probability of outcome coming true
|
||||
// Because we are summing from 100 offspring, the count of outcomes is the same as the probability of an offspring having the outcome
|
||||
outcomeCountsMap := make(map[string]int)
|
||||
|
||||
// This is a sum of each prediction's confidence
|
||||
predictionConfidencesSum := 0
|
||||
|
||||
quantityOfLociTested := 0
|
||||
|
||||
for index, offspringGenomeMap := range prospectiveOffspringGenomesList{
|
||||
|
||||
neuralNetworkExists, predictionIsKnown, predictedOutcome, predictionConfidence, currentQuantityOfLociTested, _, err := createPersonGeneticAnalysis.GetGenomeDiscreteTraitAnalysis_NeuralNetwork(traitObject, offspringGenomeMap, false)
|
||||
if (err != nil){ return false, false, nil, 0, 0, 0, err }
|
||||
if (neuralNetworkExists == false){
|
||||
return false, false, nil, 0, 0, 0, errors.New("GetGenomeTraitAnalysis_NeuralNetwork claiming that neural network doesn't exist when we already checked.")
|
||||
}
|
||||
if (predictionIsKnown == false){
|
||||
return false, false, nil, 0, 0, 0, errors.New("GetGenomeTraitAnalysis_NeuralNetwork claiming that prediction is impossible when we already know at least 1 locus value exists for trait.")
|
||||
}
|
||||
|
||||
outcomeCountsMap[predictedOutcome] += 1
|
||||
predictionConfidencesSum += predictionConfidence
|
||||
|
||||
if (index == 0){
|
||||
// This value should be the same for each predicted offspring
|
||||
quantityOfLociTested = currentQuantityOfLociTested
|
||||
}
|
||||
}
|
||||
|
||||
averagePredictionConfidence := predictionConfidencesSum/100
|
||||
|
||||
return true, true, outcomeCountsMap, averagePredictionConfidence, quantityOfLociTested, quantityOfParentalPhasedLoci, nil
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
// -bool: Any rules exist (if false, rule-based prediction is not possible for this trait)
|
||||
// -bool: Rule-based analysis exists (if false, no offspring trait information is known, or there is an outcome tie for one of the offspring)
|
||||
// -int: Quantity of rules tested
|
||||
// -int: Quantity of loci known
|
||||
// -map[[3]byte]int: Offspring probability of passing rules map
|
||||
// Map Structure: Rule identifier -> Offspring probability of passing rule (1-100)
|
||||
// -map[string]float64: Offspring average outcome scores map
|
||||
// Map Structure: Outcome Name -> Offspring average outcome score
|
||||
// If a rule entry doesn't exist, we don't know the passes-rule probability for any of the offspring
|
||||
// -map[string]int: Offspring outcome probabilities map
|
||||
// Map Structure: Outcome Name -> Offspring probability of outcome (0-100)
|
||||
// -error
|
||||
func GetOffspringTraitInfo(traitObject traits.Trait, person1LocusValuesMap map[int64]locusValue.LocusValue, person2LocusValuesMap map[int64]locusValue.LocusValue)(bool, int, map[[3]byte]int, map[string]float64, error){
|
||||
func GetOffspringDiscreteTraitInfo_Rules(traitObject traits.Trait, person1LocusValuesMap map[int64]locusValue.LocusValue, person2LocusValuesMap map[int64]locusValue.LocusValue)(bool, bool, int, int, map[[3]byte]int, map[string]int, error){
|
||||
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
if (len(traitRulesList) == 0){
|
||||
return false, false, 0, 0, nil, nil, nil
|
||||
}
|
||||
|
||||
if (len(person1LocusValuesMap) == 0){
|
||||
return false, 0, nil, nil, nil
|
||||
return true, false, 0, 0, nil, nil, nil
|
||||
}
|
||||
if (len(person2LocusValuesMap) == 0){
|
||||
return false, 0, nil, nil, nil
|
||||
return true, false, 0, 0, nil, nil, nil
|
||||
}
|
||||
|
||||
// First, we create 100 prospective offspring genomes.
|
||||
|
||||
traitLociList := traitObject.LociList
|
||||
traitLociList_Rules := traitObject.LociList_Rules
|
||||
|
||||
anyLocusValueExists, prospectiveOffspringGenomesList, err := getProspectiveOffspringGenomesList(traitLociList, person1LocusValuesMap, person2LocusValuesMap)
|
||||
if (err != nil) { return false, 0, nil, nil, err }
|
||||
anyLocusValueExists, prospectiveOffspringGenomesList, err := getProspectiveOffspringGenomesList(traitLociList_Rules, person1LocusValuesMap, person2LocusValuesMap)
|
||||
if (err != nil) { return false, false, 0, 0, nil, nil, err }
|
||||
if (anyLocusValueExists == false){
|
||||
return false, 0, nil, nil, nil
|
||||
return true, false, 0, 0, nil, nil, nil
|
||||
}
|
||||
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
// Map Structure: Rule Identifier -> Number of offspring who pass the rule (out of 100 prospective offspring)
|
||||
// Because there are 100 offspring, this also represents the percentage probability that an offspring will pass the rule
|
||||
offspringPassesRulesCountMap := make(map[[3]byte]int)
|
||||
|
||||
// We use this map to keep track of the rules for which we know every offspring's passes-rule status
|
||||
// Map Structure: Rule Identifier -> Rule Object
|
||||
offspringRulesWithKnownStatusMap := make(map[[3]byte]traits.TraitRule)
|
||||
// This map stores the quantity of offspring who have each outcome
|
||||
// The probability an offspring will have this outcome is the same as the
|
||||
// quantity of offspring who have this outcome in our set of 100 randomly generated offspring
|
||||
// Map structure: Outcome name -> quantity of offspring who have this outcome
|
||||
outcomeCountsMap := make(map[string]int)
|
||||
|
||||
for offspringIndex, offspringGenomeMap := range prospectiveOffspringGenomesList{
|
||||
quantityOfLociKnown := 0
|
||||
|
||||
// We iterate through rules to determine genome pair trait info
|
||||
for index, offspringGenomeMap := range prospectiveOffspringGenomesList{
|
||||
|
||||
for _, ruleObject := range traitRulesList{
|
||||
// Now we get outcome prediction for prospective offspring
|
||||
|
||||
ruleIdentifierHex := ruleObject.RuleIdentifier
|
||||
anyRulesExist, quantityOfRulesTested, currentQuantityOfLociKnown, offspringPassesRulesMap, predictionOutcomeIsKnown, predictedOutcome, err := createPersonGeneticAnalysis.GetGenomeDiscreteTraitAnalysis_Rules(traitObject, offspringGenomeMap, false)
|
||||
if (err != nil) { return false, false, 0, 0, nil, nil, err }
|
||||
if (anyRulesExist == false){
|
||||
return false, false, 0, 0, nil, nil, errors.New("GetGenomeTraitAnalysis_Rules returning noRulesExists when we already checked and trait rules do in-fact exist.")
|
||||
}
|
||||
if (quantityOfRulesTested == 0){
|
||||
// This will be the same for each of the 100 generated offspring
|
||||
// No analysis is possible.
|
||||
return true, false, 0, currentQuantityOfLociKnown, nil, nil, nil
|
||||
}
|
||||
if (index == 0){
|
||||
// currentQuantityOfLociKnown will be the same for each prospective offspring
|
||||
quantityOfLociKnown = currentQuantityOfLociKnown
|
||||
}
|
||||
|
||||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil) { return false, 0, nil, nil, err }
|
||||
|
||||
if (offspringIndex == 0){
|
||||
|
||||
offspringRulesWithKnownStatusMap[ruleIdentifier] = ruleObject
|
||||
} else {
|
||||
|
||||
_, exists := offspringRulesWithKnownStatusMap[ruleIdentifier]
|
||||
if (exists == false){
|
||||
// We already tried to check a previous offspring's passes-rule status for this rule
|
||||
// We know that the offspring's passes-rule status will be unknown for every prospective offspring
|
||||
continue
|
||||
}
|
||||
}
|
||||
|
||||
// This is a list that describes the locus rsids and their values that must be fulfilled to pass the rule
|
||||
ruleLocusObjectsList := ruleObject.LociList
|
||||
|
||||
offspringPassesRuleIsKnown, offspringPassesRule, err := createPersonGeneticAnalysis.GetGenomePassesTraitRuleStatus(ruleLocusObjectsList, offspringGenomeMap, false)
|
||||
if (err != nil){ return false, 0, nil, nil, err }
|
||||
if (offspringPassesRuleIsKnown == false){
|
||||
continue
|
||||
}
|
||||
|
||||
if (offspringPassesRule == true){
|
||||
for ruleIdentifier, genomePassesRule := range offspringPassesRulesMap{
|
||||
if (genomePassesRule == true){
|
||||
offspringPassesRulesCountMap[ruleIdentifier] += 1
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Map Structure: Rule Identifier -> Offspring Probability Of Passing Rule
|
||||
// The map value stores the probability that the offspring will pass the rule
|
||||
// This is a number between 0-100%
|
||||
offspringProbabilityOfPassingRulesMap := make(map[[3]byte]int)
|
||||
|
||||
// Map Structure: Outcome Name -> Outcome Score
|
||||
// Example: "Intolerant" -> 2.5
|
||||
offspringAverageOutcomeScoresMap := make(map[string]float64)
|
||||
|
||||
for ruleIdentifier, ruleObject := range offspringRulesWithKnownStatusMap{
|
||||
|
||||
//Output:
|
||||
// -int: Offspring probability of passing rule (0-100%)
|
||||
getOffspringPercentageProbabilityOfPassingRule := func()int{
|
||||
|
||||
numberOfOffspringWhoPassRule, exists := offspringPassesRulesCountMap[ruleIdentifier]
|
||||
if (exists == false){
|
||||
// None of the offspring passed the rule
|
||||
return 0
|
||||
}
|
||||
|
||||
// There are 100 tested offspring
|
||||
// Thus, the percentage of offspring who passed the rule is the same as the number of offspring who passed the rule
|
||||
// The probability of the offspring passing the rule is the same as the percentage of offspring who passed the rule
|
||||
|
||||
return numberOfOffspringWhoPassRule
|
||||
if (predictionOutcomeIsKnown == false){
|
||||
// There was a tie between outcomes for this offspring
|
||||
// We can't predict anything about this trait for this couple using rules
|
||||
// This is why we need to create rules which make it unlikely for a tie between outcomes to occur.
|
||||
return true, false, 0, 0, nil, nil, nil
|
||||
}
|
||||
|
||||
offspringPercentageProbabilityOfPassingRule := getOffspringPercentageProbabilityOfPassingRule()
|
||||
|
||||
offspringProbabilityOfPassingRulesMap[ruleIdentifier] = offspringPercentageProbabilityOfPassingRule
|
||||
|
||||
// This is the 0 - 1 probability value
|
||||
offspringProbabilityOfPassingRule := float64(offspringPercentageProbabilityOfPassingRule)/100
|
||||
|
||||
ruleOutcomePointsMap := ruleObject.OutcomePointsMap
|
||||
|
||||
for outcomeName, outcomePointsEffect := range ruleOutcomePointsMap{
|
||||
|
||||
pointsToAdd := float64(outcomePointsEffect) * offspringProbabilityOfPassingRule
|
||||
|
||||
offspringAverageOutcomeScoresMap[outcomeName] += pointsToAdd
|
||||
}
|
||||
outcomeCountsMap[predictedOutcome] += 1
|
||||
}
|
||||
|
||||
numberOfRulesTested := len(offspringProbabilityOfPassingRulesMap)
|
||||
quantityOfRulesTested := len(offspringPassesRulesCountMap)
|
||||
|
||||
if (numberOfRulesTested == 0){
|
||||
return false, 0, nil, nil, nil
|
||||
}
|
||||
|
||||
traitOutcomesList := traitObject.OutcomesList
|
||||
|
||||
// We add all outcomes for which there were no points
|
||||
|
||||
for _, traitOutcome := range traitOutcomesList{
|
||||
|
||||
_, exists := offspringAverageOutcomeScoresMap[traitOutcome]
|
||||
if (exists == false){
|
||||
offspringAverageOutcomeScoresMap[traitOutcome] = 0
|
||||
}
|
||||
}
|
||||
|
||||
return true, numberOfRulesTested, offspringProbabilityOfPassingRulesMap, offspringAverageOutcomeScoresMap, nil
|
||||
return true, true, quantityOfRulesTested, quantityOfLociKnown, offspringPassesRulesCountMap, outcomeCountsMap, nil
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -1281,6 +1307,10 @@ func GetOffspringTraitInfo(traitObject traits.Trait, person1LocusValuesMap map[i
|
|||
// Each genome represents an equal-probability offspring genome from both people's genomes
|
||||
// This function takes into account the effects of genetic linkage
|
||||
// Any locations which do not exist in both people's genomes will not be included
|
||||
//
|
||||
// TODO: The user should be able to choose how many prospective offspring to create in the settings.
|
||||
// More offspring will take longer, but will yield a more accurate trait analysis.
|
||||
//
|
||||
//Outputs:
|
||||
// -bool: Any locus value exists between both users
|
||||
// -[]map[int64]locusValue.LocusValue
|
||||
|
|
@ -1388,7 +1418,7 @@ func getProspectiveOffspringGenomesList(lociList []int64, person1LociMap map[int
|
|||
|
||||
// We step by 1,000,000 each time
|
||||
// It would be more realistic if we did it in 1 integer increments, but it would be slower
|
||||
for position := int64(0); position <= chromosomeLength; position += 1000000{
|
||||
for position := int64(0); position < chromosomeLength; position += 1_000_000{
|
||||
|
||||
//From Wikipedia:
|
||||
// A centimorgan (abbreviated cM) is a unit for measuring genetic linkage.
|
||||
|
|
@ -1441,14 +1471,19 @@ func getProspectiveOffspringGenomesList(lociList []int64, person1LociMap map[int
|
|||
}
|
||||
|
||||
personLocusBase1 := personLocusValue.Base1Value
|
||||
personLocusBase2 := personLocusValue.Base1Value
|
||||
personLocusBase2 := personLocusValue.Base2Value
|
||||
personLocusIsPhased := personLocusValue.LocusIsPhased
|
||||
|
||||
if (personLocusBase1 == personLocusBase2){
|
||||
// Phase doesn't matter
|
||||
return true, personLocusBase1, nil
|
||||
}
|
||||
|
||||
if (personLocusIsPhased == false){
|
||||
// Breakpoints are unnecessary
|
||||
// We either choose base 1 or 2
|
||||
randomBool := helpers.GetRandomBool()
|
||||
if (randomBool == true){
|
||||
randomInt := pseudorandomNumberGenerator.IntN(2)
|
||||
if (randomInt == 1){
|
||||
return true, personLocusBase1, nil
|
||||
}
|
||||
return true, personLocusBase2, nil
|
||||
|
|
@ -1490,9 +1525,9 @@ func getProspectiveOffspringGenomesList(lociList []int64, person1LociMap map[int
|
|||
|
||||
getLocusListIndex := func()int{
|
||||
|
||||
for index, breakpoint := range personBreakpointsList{
|
||||
for index, breakpointPosition := range personBreakpointsList{
|
||||
|
||||
if (int64(locusPosition) <= breakpoint){
|
||||
if (int64(locusPosition) <= breakpointPosition){
|
||||
|
||||
return index
|
||||
}
|
||||
|
|
|
|||
|
|
@ -22,13 +22,14 @@ import "seekia/resources/geneticReferences/traits"
|
|||
|
||||
import "seekia/internal/encoding"
|
||||
import "seekia/internal/genetics/geneticAnalysis"
|
||||
import "seekia/internal/genetics/geneticPrediction"
|
||||
import "seekia/internal/genetics/locusValue"
|
||||
import "seekia/internal/genetics/prepareRawGenomes"
|
||||
import "seekia/internal/helpers"
|
||||
|
||||
import "errors"
|
||||
import "slices"
|
||||
import "maps"
|
||||
import "reflect"
|
||||
|
||||
|
||||
//Outputs:
|
||||
|
|
@ -51,10 +52,23 @@ func CreatePersonGeneticAnalysis(genomesList []prepareRawGenomes.RawGenomeWithMe
|
|||
genomesWithMetadataList, allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := prepareRawGenomes.GetGenomesWithMetadataListFromRawGenomesList(genomesList, prepareRawGenomesUpdatePercentageCompleteFunction)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
// This map stores each genome's locus values
|
||||
// Map Structure: Genome Identifier -> Genome locus values map (rsID -> Locus Value)
|
||||
genomesMap := make(map[[16]byte]map[int64]locusValue.LocusValue)
|
||||
|
||||
for _, genomeWithMetadata := range genomesWithMetadataList{
|
||||
|
||||
genomeIdentifier := genomeWithMetadata.GenomeIdentifier
|
||||
genomeMap := genomeWithMetadata.GenomeMap
|
||||
|
||||
genomesMap[genomeIdentifier] = genomeMap
|
||||
}
|
||||
|
||||
newGeneticAnalysisObject := geneticAnalysis.PersonAnalysis{
|
||||
AnalysisVersion: 1,
|
||||
CombinedGenomesExist: multipleGenomesExist,
|
||||
AllRawGenomeIdentifiersList: allRawGenomeIdentifiersList,
|
||||
GenomesMap: genomesMap,
|
||||
}
|
||||
|
||||
if (multipleGenomesExist == true){
|
||||
|
|
@ -107,20 +121,30 @@ func CreatePersonGeneticAnalysis(genomesList []prepareRawGenomes.RawGenomeWithMe
|
|||
traitObjectsList, err := traits.GetTraitObjectsList()
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
// Map Structure: Trait Name -> PersonTraitInfo
|
||||
analysisTraitsMap := make(map[string]geneticAnalysis.PersonTraitInfo)
|
||||
// This map will always contain an entry for each discrete trait
|
||||
// Map Structure: Trait Name -> PersonDiscreteTraitInfo
|
||||
analysisDiscreteTraitsMap := make(map[string]geneticAnalysis.PersonDiscreteTraitInfo)
|
||||
|
||||
// This map will not contain entries for traits which this person's genome has no known loci
|
||||
// Map Structure: Trait Name -> PersonNumericTraitInfo
|
||||
analysisNumericTraitsMap := make(map[string]geneticAnalysis.PersonNumericTraitInfo)
|
||||
|
||||
for _, traitObject := range traitObjectsList{
|
||||
|
||||
personTraitAnalysisObject, err := GetPersonTraitAnalysis(genomesWithMetadataList, traitObject)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
traitName := traitObject.TraitName
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
|
||||
analysisTraitsMap[traitName] = personTraitAnalysisObject
|
||||
if (traitIsDiscreteOrNumeric == "Discrete"){
|
||||
|
||||
personTraitAnalysisObject, err := GetPersonDiscreteTraitAnalysis(genomesWithMetadataList, traitObject)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
||||
analysisDiscreteTraitsMap[traitName] = personTraitAnalysisObject
|
||||
}
|
||||
}
|
||||
|
||||
newGeneticAnalysisObject.TraitsMap = analysisTraitsMap
|
||||
newGeneticAnalysisObject.DiscreteTraitsMap = analysisDiscreteTraitsMap
|
||||
newGeneticAnalysisObject.NumericTraitsMap = analysisNumericTraitsMap
|
||||
|
||||
analysisBytes, err := encoding.EncodeMessagePackBytes(newGeneticAnalysisObject)
|
||||
if (err != nil) { return false, "", err }
|
||||
|
|
@ -505,9 +529,9 @@ func GetPersonMonogenicDiseaseAnalysis(inputGenomesWithMetadataList []prepareRaw
|
|||
|
||||
diseaseAnalysisObject := geneticAnalysis.PersonGenomeMonogenicDiseaseInfo{
|
||||
PersonHasDisease: personHasDisease,
|
||||
NumberOfVariantsTested: numberOfVariantsTested,
|
||||
NumberOfLociTested: numberOfLociTested,
|
||||
NumberOfPhasedLoci: numberOfPhasedLoci,
|
||||
QuantityOfVariantsTested: numberOfVariantsTested,
|
||||
QuantityOfLociTested: numberOfLociTested,
|
||||
QuantityOfPhasedLoci: numberOfPhasedLoci,
|
||||
ProbabilityOfPassingADiseaseVariant: percentageProbabilityPersonWillPassADiseaseVariant,
|
||||
VariantsInfoMap: variantsInfoMap,
|
||||
}
|
||||
|
|
@ -737,16 +761,15 @@ func GetPersonPolygenicDiseaseAnalysis(inputGenomesWithMetadataList []prepareRaw
|
|||
genomeLocusValuesMap[locusRSID] = locusValueObject
|
||||
}
|
||||
|
||||
anyLociTested, personDiseaseRiskScore, genomeNumberOfLociTested, genomeLociInfoMap, err := GetPersonGenomePolygenicDiseaseInfo(diseaseLociList, genomeLocusValuesMap, false)
|
||||
anyLociTested, personDiseaseRiskScore, genomeNumberOfLociTested, genomeLociInfoMap, err := GetPersonGenomePolygenicDiseaseInfo(diseaseLociList, genomeLocusValuesMap, true)
|
||||
if (err != nil) { return emptyDiseaseInfoObject, err }
|
||||
if (anyLociTested == false){
|
||||
continue
|
||||
}
|
||||
|
||||
newDiseaseInfoObject := geneticAnalysis.PersonGenomePolygenicDiseaseInfo{
|
||||
NumberOfLociTested: genomeNumberOfLociTested,
|
||||
QuantityOfLociTested: genomeNumberOfLociTested,
|
||||
RiskScore: personDiseaseRiskScore,
|
||||
LocusValuesMap: genomeLocusValuesMap,
|
||||
LociInfoMap: genomeLociInfoMap,
|
||||
}
|
||||
|
||||
|
|
@ -777,7 +800,7 @@ func GetPersonPolygenicDiseaseAnalysis(inputGenomesWithMetadataList []prepareRaw
|
|||
for _, personGenomeDiseaseInfoObject := range personPolygenicDiseaseInfoMap{
|
||||
|
||||
currentGenomeRiskScore := personGenomeDiseaseInfoObject.RiskScore
|
||||
currentGenomeNumberOfLociTested := personGenomeDiseaseInfoObject.NumberOfLociTested
|
||||
currentGenomeNumberOfLociTested := personGenomeDiseaseInfoObject.QuantityOfLociTested
|
||||
|
||||
if (firstItemReached == false){
|
||||
genomeRiskScore = currentGenomeRiskScore
|
||||
|
|
@ -855,106 +878,68 @@ func GetPersonPolygenicDiseaseAnalysis(inputGenomesWithMetadataList []prepareRaw
|
|||
|
||||
|
||||
//Outputs:
|
||||
// -geneticAnalysis.PersonTraitInfo: Trait analysis object
|
||||
// -geneticAnalysis.PersonDiscreteTraitInfo: Trait analysis object
|
||||
// -error
|
||||
func GetPersonTraitAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.GenomeWithMetadata, traitObject traits.Trait)(geneticAnalysis.PersonTraitInfo, error){
|
||||
func GetPersonDiscreteTraitAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.GenomeWithMetadata, traitObject traits.Trait)(geneticAnalysis.PersonDiscreteTraitInfo, error){
|
||||
|
||||
// We use this when returning errors
|
||||
emptyPersonTraitInfo := geneticAnalysis.PersonTraitInfo{}
|
||||
|
||||
traitLociList := traitObject.LociList
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
// Map Structure: Genome Identifier -> PersonGenomeTraitInfo
|
||||
newPersonTraitInfoMap := make(map[[16]byte]geneticAnalysis.PersonGenomeTraitInfo)
|
||||
// Map Structure: Genome Identifier -> PersonGenomeDiscreteTraitInfo
|
||||
newPersonTraitInfoMap := make(map[[16]byte]geneticAnalysis.PersonGenomeDiscreteTraitInfo)
|
||||
|
||||
for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{
|
||||
|
||||
genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier
|
||||
genomeMap := genomeWithMetadataObject.GenomeMap
|
||||
|
||||
// This map contains the locus values for the genome
|
||||
// If an locus's entry doesn't exist, its value is unknown
|
||||
// Map Structure: Locus rsID -> Locus Value
|
||||
genomeLocusValuesMap := make(map[int64]locusValue.LocusValue)
|
||||
newPersonGenomeTraitInfo := geneticAnalysis.PersonGenomeDiscreteTraitInfo{}
|
||||
|
||||
for _, locusRSID := range traitLociList{
|
||||
neuralNetworkExists, neuralNetworkOutcomeIsKnown, predictedOutcome, predictionConfidence, quantityOfLociTested, quantityOfPhasedLoci, err := GetGenomeDiscreteTraitAnalysis_NeuralNetwork(traitObject, genomeMap, true)
|
||||
if (err != nil) { return geneticAnalysis.PersonDiscreteTraitInfo{}, err }
|
||||
if (neuralNetworkExists == true){
|
||||
|
||||
locusBasePairKnown, _, _, _, locusValueObject, err := GetLocusValueFromGenomeMap(true, genomeMap, locusRSID)
|
||||
if (err != nil) { return emptyPersonTraitInfo, err }
|
||||
if (locusBasePairKnown == false){
|
||||
continue
|
||||
}
|
||||
newPersonGenomeTraitInfo.NeuralNetworkExists = true
|
||||
|
||||
genomeLocusValuesMap[locusRSID] = locusValueObject
|
||||
}
|
||||
if (neuralNetworkOutcomeIsKnown == true){
|
||||
|
||||
// This map contains the trait outcome scores for the genome
|
||||
// Map Structure: Outcome Name -> Score
|
||||
// Example: "Intolerant" -> 5
|
||||
traitOutcomeScoresMap := make(map[string]int)
|
||||
newPersonGenomeTraitInfo.NeuralNetworkAnalysisExists = true
|
||||
|
||||
// Map Structure: Rule Identifier -> Genome Passes rule (true if the genome passes the rule)
|
||||
personPassesRulesMap := make(map[[3]byte]bool)
|
||||
newPersonGenomeTraitInfo_NeuralNetwork := geneticAnalysis.PersonGenomeDiscreteTraitInfo_NeuralNetwork{
|
||||
|
||||
if (len(traitRulesList) != 0){
|
||||
|
||||
// At least 1 rule exists for this trait
|
||||
|
||||
for _, ruleObject := range traitRulesList{
|
||||
|
||||
ruleIdentifierHex := ruleObject.RuleIdentifier
|
||||
|
||||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil) { return emptyPersonTraitInfo, err }
|
||||
|
||||
ruleLociList := ruleObject.LociList
|
||||
|
||||
genomePassesRuleIsKnown, genomePassesRule, err := GetGenomePassesTraitRuleStatus(ruleLociList, genomeMap, false)
|
||||
if (err != nil) { return emptyPersonTraitInfo, err }
|
||||
if (genomePassesRuleIsKnown == false){
|
||||
continue
|
||||
PredictedOutcome: predictedOutcome,
|
||||
PredictionConfidence: predictionConfidence,
|
||||
QuantityOfLociKnown: quantityOfLociTested,
|
||||
QuantityOfPhasedLoci: quantityOfPhasedLoci,
|
||||
}
|
||||
|
||||
personPassesRulesMap[ruleIdentifier] = genomePassesRule
|
||||
newPersonGenomeTraitInfo.NeuralNetworkAnalysis = newPersonGenomeTraitInfo_NeuralNetwork
|
||||
}
|
||||
}
|
||||
|
||||
// The rule has been passed by this genome
|
||||
// We add the outcome points for the rule to the traitOutcomeScoresMap
|
||||
anyRulesExist, quantityOfRulesTested, quantityOfLociKnown, genomePassesRulesMap, predictedOutcomeExists, predictedOutcome, err := GetGenomeDiscreteTraitAnalysis_Rules(traitObject, genomeMap, true)
|
||||
if (err != nil) { return geneticAnalysis.PersonDiscreteTraitInfo{}, err }
|
||||
if (anyRulesExist == true){
|
||||
newPersonGenomeTraitInfo.AnyRulesExist = true
|
||||
|
||||
ruleOutcomePointsMap := ruleObject.OutcomePointsMap
|
||||
if (quantityOfRulesTested != 0){
|
||||
|
||||
for traitOutcome, pointsChange := range ruleOutcomePointsMap{
|
||||
newPersonGenomeTraitInfo.RulesAnalysisExists = true
|
||||
|
||||
traitOutcomeScoresMap[traitOutcome] += pointsChange
|
||||
newPersonGenomeTraitInfo_Rules := geneticAnalysis.PersonGenomeDiscreteTraitInfo_Rules{
|
||||
|
||||
GenomePassesRulesMap: genomePassesRulesMap,
|
||||
PredictedOutcomeExists: predictedOutcomeExists,
|
||||
PredictedOutcome: predictedOutcome,
|
||||
QuantityOfRulesTested: quantityOfRulesTested,
|
||||
QuantityOfLociKnown: quantityOfLociKnown,
|
||||
}
|
||||
|
||||
newPersonGenomeTraitInfo.RulesAnalysis = newPersonGenomeTraitInfo_Rules
|
||||
}
|
||||
}
|
||||
|
||||
traitOutcomesList := traitObject.OutcomesList
|
||||
|
||||
// We add all outcomes for which there were no points
|
||||
|
||||
for _, traitOutcome := range traitOutcomesList{
|
||||
|
||||
_, exists := traitOutcomeScoresMap[traitOutcome]
|
||||
if (exists == false){
|
||||
traitOutcomeScoresMap[traitOutcome] = 0
|
||||
}
|
||||
}
|
||||
|
||||
numberOfRulesTested := len(personPassesRulesMap)
|
||||
|
||||
newPersonGenomeTraitInfo := geneticAnalysis.PersonGenomeTraitInfo{
|
||||
NumberOfRulesTested: numberOfRulesTested,
|
||||
LocusValuesMap: genomeLocusValuesMap,
|
||||
OutcomeScoresMap: traitOutcomeScoresMap,
|
||||
GenomePassesRulesMap: personPassesRulesMap,
|
||||
}
|
||||
|
||||
newPersonTraitInfoMap[genomeIdentifier] = newPersonGenomeTraitInfo
|
||||
}
|
||||
|
||||
newPersonTraitInfoObject := geneticAnalysis.PersonTraitInfo{
|
||||
newPersonTraitInfoObject := geneticAnalysis.PersonDiscreteTraitInfo{
|
||||
TraitInfoMap: newPersonTraitInfoMap,
|
||||
}
|
||||
|
||||
|
|
@ -968,40 +953,20 @@ func GetPersonTraitAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.Gen
|
|||
|
||||
getConflictExistsBool := func()(bool, error){
|
||||
|
||||
//TODO: Check for locus value conflicts once locus values are used in neural network prediction.
|
||||
|
||||
if (len(traitRulesList) == 0){
|
||||
return false, nil
|
||||
}
|
||||
|
||||
// We check to see if the outcome scores are the same for all genomes
|
||||
// We also check each rule result
|
||||
// We check to see if the analysis results are the same for all genomes
|
||||
|
||||
firstItemReached := false
|
||||
|
||||
outcomeScoresMap := make(map[string]int)
|
||||
passesRulesMap := make(map[[3]byte]bool)
|
||||
personGenomeTraitInfoObject := geneticAnalysis.PersonGenomeDiscreteTraitInfo{}
|
||||
|
||||
for _, genomeTraitInfoObject := range newPersonTraitInfoMap{
|
||||
|
||||
currentGenomeOutcomeScoresMap := genomeTraitInfoObject.OutcomeScoresMap
|
||||
currentGenomePassesRulesMap := genomeTraitInfoObject.GenomePassesRulesMap
|
||||
|
||||
if (firstItemReached == false){
|
||||
outcomeScoresMap = currentGenomeOutcomeScoresMap
|
||||
passesRulesMap = currentGenomePassesRulesMap
|
||||
firstItemReached = true
|
||||
personGenomeTraitInfoObject = genomeTraitInfoObject
|
||||
continue
|
||||
}
|
||||
|
||||
areEqual := maps.Equal(currentGenomeOutcomeScoresMap, outcomeScoresMap)
|
||||
areEqual := reflect.DeepEqual(personGenomeTraitInfoObject, genomeTraitInfoObject)
|
||||
if (areEqual == false){
|
||||
// A conflict exists
|
||||
return true, nil
|
||||
}
|
||||
areEqual = maps.Equal(currentGenomePassesRulesMap, passesRulesMap)
|
||||
if (areEqual == false){
|
||||
// A conflict exists
|
||||
return true, nil
|
||||
}
|
||||
}
|
||||
|
|
@ -1010,7 +975,7 @@ func GetPersonTraitAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.Gen
|
|||
}
|
||||
|
||||
conflictExists, err := getConflictExistsBool()
|
||||
if (err != nil) { return emptyPersonTraitInfo, err }
|
||||
if (err != nil) { return geneticAnalysis.PersonDiscreteTraitInfo{}, err }
|
||||
|
||||
newPersonTraitInfoObject.ConflictExists = conflictExists
|
||||
|
||||
|
|
@ -1046,12 +1011,205 @@ func GetGenomePolygenicDiseaseLocusRiskInfo(locusRiskWeightsMap map[string]int,
|
|||
return riskWeight, true, oddsRatio, nil
|
||||
}
|
||||
|
||||
// We use this to generate trait predictions using a neural network
|
||||
// The alternative prediction method is to use Rules (see GetGenomeTraitAnalysis_Rules)
|
||||
//Outputs:
|
||||
// -bool: Trait Neural network analysis available (if false, we can't predict this trait using a neural network)
|
||||
// -bool: Neural network outcome is known (at least 1 locus value is known which is needed for the neural network
|
||||
// -string: The predicted outcome (Example: "Blue")
|
||||
// -int: Probability (0-100) that the outcome from neural network is true (confidence)
|
||||
// -int: Quantity of loci tested
|
||||
// -int: Quantity of phased loci
|
||||
// -error
|
||||
func GetGenomeDiscreteTraitAnalysis_NeuralNetwork(traitObject traits.Trait, genomeMap map[int64]locusValue.LocusValue, checkForAliases bool)(bool, bool, string, int, int, int, error){
|
||||
|
||||
getGenomeLocusValuesMap := func()(map[int64]locusValue.LocusValue, error){
|
||||
|
||||
if (checkForAliases == false){
|
||||
// We don't need to check for rsID aliases.
|
||||
return genomeMap, nil
|
||||
}
|
||||
|
||||
traitLociList := traitObject.LociList
|
||||
|
||||
// This map contains the locus values for the genome
|
||||
// If a locus's entry doesn't exist, its value is unknown
|
||||
// Map Structure: Locus rsID -> Locus Value
|
||||
genomeLocusValuesMap := make(map[int64]locusValue.LocusValue)
|
||||
|
||||
for _, locusRSID := range traitLociList{
|
||||
|
||||
locusBasePairKnown, _, _, _, locusValueObject, err := GetLocusValueFromGenomeMap(checkForAliases, genomeMap, locusRSID)
|
||||
if (err != nil) { return nil, err }
|
||||
if (locusBasePairKnown == false){
|
||||
continue
|
||||
}
|
||||
|
||||
genomeLocusValuesMap[locusRSID] = locusValueObject
|
||||
}
|
||||
|
||||
return genomeLocusValuesMap, nil
|
||||
}
|
||||
|
||||
genomeLocusValuesMap, err := getGenomeLocusValuesMap()
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
|
||||
traitName := traitObject.TraitName
|
||||
|
||||
neuralNetworkModelExists, traitPredictionIsPossible, predictedOutcome, predictionConfidence, quantityOfLociKnown, quantityOfPhasedLoci, err := geneticPrediction.GetNeuralNetworkTraitPredictionFromGenomeMap(traitName, genomeLocusValuesMap)
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
if (neuralNetworkModelExists == false){
|
||||
return false, false, "", 0, 0, 0, nil
|
||||
}
|
||||
if (traitPredictionIsPossible == false){
|
||||
return true, false, "", 0, 0, 0, nil
|
||||
}
|
||||
|
||||
return true, true, predictedOutcome, predictionConfidence, quantityOfLociKnown, quantityOfPhasedLoci, nil
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
// -bool: Rule-based trait prediction is available
|
||||
// -int: Quantity of trait rules tested
|
||||
// -int: Quantity of loci known
|
||||
// -map[[3]byte]bool: Passed rules map (Rule Identifier -> Genome passes rule)
|
||||
// -bool: Rule-based prediction outcome is known (at least 1 rule has been tested and there is no outcome tie)
|
||||
// -string: The predicted outcome (Example: "Tolerant")
|
||||
// -error
|
||||
func GetGenomeDiscreteTraitAnalysis_Rules(traitObject traits.Trait, genomeMap map[int64]locusValue.LocusValue, checkForAliases bool)(bool, int, int, map[[3]byte]bool, bool, string, error){
|
||||
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
if (traitIsDiscreteOrNumeric != "Discrete"){
|
||||
return false, 0, 0, nil, false, "", errors.New("GetGenomeDiscreteTraitAnalysis_Rules called with non-discrete trait.")
|
||||
}
|
||||
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
if (len(traitRulesList) == 0){
|
||||
// We can't predict this trait using rules
|
||||
// This means that neural network prediction is the only alternative potential way to predict this trait
|
||||
return false, 0, 0, nil, false, "", nil
|
||||
}
|
||||
|
||||
// This map contains the trait outcome scores for the genome
|
||||
// Map Structure: Outcome Name -> Score
|
||||
// Example: "Intolerant" -> 5
|
||||
traitOutcomeScoresMap := make(map[string]int)
|
||||
|
||||
// Map Structure: Rule Identifier -> Genome Passes rule (true if the genome passes the rule)
|
||||
personPassesRulesMap := make(map[[3]byte]bool)
|
||||
|
||||
// This map stores each known loci
|
||||
// Multiple rules can use the same loci, so we need a map to avoid duplicates
|
||||
// Map Structure: Locus RSID -> Locus is known
|
||||
lociAreKnownMap := make(map[int64]bool)
|
||||
|
||||
for _, ruleObject := range traitRulesList{
|
||||
|
||||
ruleIdentifierHex := ruleObject.RuleIdentifier
|
||||
|
||||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil) { return false, 0, 0, nil, false, "", err }
|
||||
|
||||
ruleLociList := ruleObject.LociList
|
||||
|
||||
for _, locusObject := range ruleLociList{
|
||||
|
||||
locusRSID := locusObject.LocusRSID
|
||||
|
||||
_, exists := lociAreKnownMap[locusRSID]
|
||||
if (exists == true){
|
||||
// We already know if this locus is known
|
||||
continue
|
||||
}
|
||||
locusIsKnown, _, _, _, _, err := GetLocusValueFromGenomeMap(checkForAliases, genomeMap, locusRSID)
|
||||
if (err != nil) { return false, 0, 0, nil, false, "", err }
|
||||
|
||||
lociAreKnownMap[locusRSID] = locusIsKnown
|
||||
}
|
||||
|
||||
genomePassesRuleIsKnown, genomePassesRule, err := GetGenomePassesDiscreteTraitRuleStatus(ruleLociList, genomeMap, checkForAliases)
|
||||
if (err != nil) { return false, 0, 0, nil, false, "", err }
|
||||
if (genomePassesRuleIsKnown == false){
|
||||
continue
|
||||
}
|
||||
|
||||
personPassesRulesMap[ruleIdentifier] = genomePassesRule
|
||||
|
||||
// The rule has been passed by this genome
|
||||
// We add the outcome points for the rule to the traitOutcomeScoresMap
|
||||
|
||||
ruleOutcomePointsMap := ruleObject.OutcomePointsMap
|
||||
|
||||
for traitOutcome, pointsChange := range ruleOutcomePointsMap{
|
||||
|
||||
traitOutcomeScoresMap[traitOutcome] += pointsChange
|
||||
}
|
||||
}
|
||||
|
||||
quantityOfLociKnown := 0
|
||||
|
||||
for _, locusIsKnown := range lociAreKnownMap{
|
||||
if (locusIsKnown == true){
|
||||
quantityOfLociKnown += 1
|
||||
}
|
||||
}
|
||||
|
||||
quantityOfRulesTested := len(personPassesRulesMap)
|
||||
|
||||
if (quantityOfRulesTested == 0){
|
||||
return true, 0, quantityOfLociKnown, personPassesRulesMap, false, "", nil
|
||||
}
|
||||
|
||||
// -bool: Outcome is known (will be false if there is a tie
|
||||
// -string:
|
||||
// -error
|
||||
getOutcome := func()(bool, string, error){
|
||||
|
||||
largestOutcome := ""
|
||||
largestOutcomePoints := 0
|
||||
tieExists := false
|
||||
|
||||
for outcomeName, outcomePoints := range traitOutcomeScoresMap{
|
||||
|
||||
if (outcomePoints < 1){
|
||||
// This should never happen, because outcomes points should only be increased by integers which are at least 1 or greater
|
||||
return false, "", errors.New("traitOutcomeScoresMap contains outcomePoints < 1.")
|
||||
}
|
||||
|
||||
if (outcomePoints > largestOutcomePoints){
|
||||
largestOutcome = outcomeName
|
||||
largestOutcomePoints = outcomePoints
|
||||
tieExists = false
|
||||
continue
|
||||
|
||||
} else if (outcomePoints == largestOutcomePoints){
|
||||
tieExists = true
|
||||
}
|
||||
}
|
||||
|
||||
if (tieExists == true){
|
||||
return false, "", nil
|
||||
}
|
||||
|
||||
return true, largestOutcome, nil
|
||||
}
|
||||
|
||||
outcomeIsKnown, outcomeName, err := getOutcome()
|
||||
if (err != nil) { return false, 0, 0, nil, false, "", err }
|
||||
if (outcomeIsKnown == false){
|
||||
return true, quantityOfRulesTested, quantityOfLociKnown, personPassesRulesMap, false, "", nil
|
||||
}
|
||||
|
||||
return true, quantityOfRulesTested, quantityOfLociKnown, personPassesRulesMap, true, outcomeName, nil
|
||||
}
|
||||
|
||||
// This function checks to see if a genome will pass a trait rule
|
||||
// Outputs:
|
||||
// -bool: Genome passes trait rule status is known
|
||||
// -bool: Genome passes trait rule
|
||||
// -error
|
||||
func GetGenomePassesTraitRuleStatus(ruleLociList []traits.RuleLocus, genomeMap map[int64]locusValue.LocusValue, checkForAliases bool)(bool, bool, error){
|
||||
func GetGenomePassesDiscreteTraitRuleStatus(ruleLociList []traits.RuleLocus, genomeMap map[int64]locusValue.LocusValue, checkForAliases bool)(bool, bool, error){
|
||||
|
||||
// We check to see if genome passes all rule loci
|
||||
// To pass a rule, all of the rule's loci must be passed by the provided genome
|
||||
|
|
|
|||
|
|
@ -22,14 +22,27 @@ type PersonAnalysis struct{
|
|||
OnlyIncludeSharedGenomeIdentifier [16]byte
|
||||
OnlyExcludeConflictsGenomeIdentifier [16]byte
|
||||
|
||||
// This map stores each genome's locus values
|
||||
// Only the loci that belong in the locusMetadata package are inside of this map
|
||||
// This is necessary, otherwise genetic analyses would be too large by containing each analyzed raw genome.
|
||||
// Map Structure: Genome Identifier -> Genome locus values map (rsID -> Locus Value)
|
||||
GenomesMap map[[16]byte]map[int64]locusValue.LocusValue
|
||||
|
||||
// Map Structure: Disease Name -> PersonMonogenicDiseaseInfo
|
||||
MonogenicDiseasesMap map[string]PersonMonogenicDiseaseInfo
|
||||
|
||||
// Map Structure: Disease Name -> PersonPolygenicDiseaseInfo
|
||||
PolygenicDiseasesMap map[string]PersonPolygenicDiseaseInfo
|
||||
|
||||
// These are traits which have discrete outcomes, rather than numeric outcomes
|
||||
// For example: Eye color
|
||||
// Map Structure: Trait Name -> Trait Info Object
|
||||
TraitsMap map[string]PersonTraitInfo
|
||||
DiscreteTraitsMap map[string]PersonDiscreteTraitInfo
|
||||
|
||||
// These are traits which have numeric outcomes, rather than discrete outcomes
|
||||
// For example: Height
|
||||
// Map Structure: Trait Name -> Trait Info Object
|
||||
NumericTraitsMap map[string]PersonNumericTraitInfo
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -50,15 +63,15 @@ type PersonGenomeMonogenicDiseaseInfo struct{
|
|||
PersonHasDisease bool
|
||||
|
||||
// This describes the number of variants that were tested for this disease
|
||||
NumberOfVariantsTested int
|
||||
QuantityOfVariantsTested int
|
||||
|
||||
// This describes the number of loci that were tested for this disease
|
||||
// 1 locus can have multiple potential variants
|
||||
NumberOfLociTested int
|
||||
QuantityOfLociTested int
|
||||
|
||||
// This describes the number of loci which are phased
|
||||
// This number will always be <= NumberOfLociTested
|
||||
NumberOfPhasedLoci int
|
||||
// This number will always be <= QuantityOfLociTested
|
||||
QuantityOfPhasedLoci int
|
||||
|
||||
// This describes the probability that the person will pass a disease variant
|
||||
// It is a value that represents a percentage between 0-100
|
||||
|
|
@ -94,14 +107,9 @@ type PersonPolygenicDiseaseInfo struct{
|
|||
|
||||
type PersonGenomePolygenicDiseaseInfo struct{
|
||||
|
||||
// This describes the number of loci tested for this disease
|
||||
// This should be len(LociInfoList)
|
||||
NumberOfLociTested int
|
||||
|
||||
// This map contains the locus values for the genome for this trait
|
||||
// If an locus's entry doesn't exist, its value is unknown
|
||||
// Map Structure: Locus rsID -> Locus Value
|
||||
LocusValuesMap map[int64]locusValue.LocusValue
|
||||
// This describes the quantity of loci tested for this disease
|
||||
// This should be len(LociInfoMap)
|
||||
QuantityOfLociTested int
|
||||
|
||||
// This is total risk score for this disease for the person's genome
|
||||
// This is a number between 1-10
|
||||
|
|
@ -128,34 +136,102 @@ type PersonGenomePolygenicDiseaseLocusInfo struct{
|
|||
}
|
||||
|
||||
|
||||
type PersonTraitInfo struct{
|
||||
type PersonDiscreteTraitInfo struct{
|
||||
|
||||
// This map contains the person's trait info for each genome
|
||||
// If no map entries exist, then no trait info is known
|
||||
// Map Structure: Genome Identifier -> PersonGenomeTraitInfo
|
||||
TraitInfoMap map[[16]byte]PersonGenomeTraitInfo
|
||||
// Map Structure: Genome Identifier -> PersonGenomeDiscreteTraitInfo
|
||||
TraitInfoMap map[[16]byte]PersonGenomeDiscreteTraitInfo
|
||||
|
||||
// This is true if there are multiple genomes and the results from each genome differ
|
||||
ConflictExists bool
|
||||
}
|
||||
|
||||
type PersonGenomeTraitInfo struct{
|
||||
// For a trait analysis, both analysis methods may exist in the results
|
||||
// However, the GUI will only display the results from one of the methods.
|
||||
// The neural network prediction is always prioritized over the rule-based prediction
|
||||
type PersonGenomeDiscreteTraitInfo struct{
|
||||
|
||||
// This should be len(GenomePassesRulesMap)
|
||||
NumberOfRulesTested int
|
||||
// This is true if it is possible to analyze this trait using a neural network
|
||||
NeuralNetworkExists bool
|
||||
|
||||
// This map contains the locus values for the genome for this trait
|
||||
// If an locus's entry doesn't exist, its value is unknown
|
||||
// Map Structure: Locus rsID -> Locus Value
|
||||
LocusValuesMap map[int64]locusValue.LocusValue
|
||||
// This is true if a neural network analysis was performed for this genome
|
||||
// This means that at least 1 locus for this trait was contained in the genome
|
||||
NeuralNetworkAnalysisExists bool
|
||||
|
||||
// This map contains the outcome scores for the genome
|
||||
// Map Structure: Outcome Name -> Score
|
||||
// Example: "Intolerant" -> 5
|
||||
OutcomeScoresMap map[string]int
|
||||
NeuralNetworkAnalysis PersonGenomeDiscreteTraitInfo_NeuralNetwork
|
||||
|
||||
// This is true if it is possible to analyze this trait using rules
|
||||
AnyRulesExist bool
|
||||
|
||||
// This is true if a rules-based analysis was performed for this genome
|
||||
// This means that all of the loci for at least 1 rule for this trait was contained in the genome
|
||||
RulesAnalysisExists bool
|
||||
|
||||
RulesAnalysis PersonGenomeDiscreteTraitInfo_Rules
|
||||
}
|
||||
|
||||
type PersonGenomeDiscreteTraitInfo_NeuralNetwork struct{
|
||||
|
||||
// The predicted outcome (Example: "Blue")
|
||||
PredictedOutcome string
|
||||
|
||||
// Probability (0-100) that the outcome from the neural network is true
|
||||
PredictionConfidence int
|
||||
|
||||
QuantityOfLociKnown int
|
||||
|
||||
QuantityOfPhasedLoci int
|
||||
}
|
||||
|
||||
type PersonGenomeDiscreteTraitInfo_Rules struct{
|
||||
|
||||
// Map Structure: Rule Identifier -> Genome Passes rule (true if the genome passes the rule)
|
||||
GenomePassesRulesMap map[[3]byte]bool
|
||||
|
||||
// This is true if there was not a tie between summed rule outcome scores
|
||||
// It is possible to have some tested rules without a known outcome
|
||||
PredictedOutcomeExists bool
|
||||
|
||||
// This is the outcome that was predicted
|
||||
// Example: "Intolerant"
|
||||
PredictedOutcome string
|
||||
|
||||
// This should be len(GenomePassesRulesMap)
|
||||
QuantityOfRulesTested int
|
||||
|
||||
// This only counts the loci which are used for rules
|
||||
// For example, loci that are only used in neural-network-based prediction are not counted
|
||||
QuantityOfLociKnown int
|
||||
}
|
||||
|
||||
|
||||
type PersonNumericTraitInfo struct{
|
||||
|
||||
// This map contains the person's trait info for each genome
|
||||
// If no map entries exist, then no trait info is known
|
||||
// Map Structure: Genome Identifier -> PersonGenomeNumericTraitInfo
|
||||
TraitInfoMap map[[16]byte]PersonGenomeNumericTraitInfo
|
||||
|
||||
// This is true if there are multiple genomes and the results from each genome differ
|
||||
ConflictExists bool
|
||||
}
|
||||
|
||||
type PersonGenomeNumericTraitInfo struct{
|
||||
|
||||
// The predicted outcome (Example: The predicted height for this person, in centimeters)
|
||||
PredictedOutcome float64
|
||||
|
||||
// This map stores the confidence ranges for the predicted value
|
||||
// If we want to know how accurate the prediction is with a X% accuracy, how far would we have to expand the
|
||||
// predicted value's range to be accurate, X% of the time?
|
||||
// For example: 50% accuracy requires a +/-5 point range, 80% accuracy requires a +-15 point range
|
||||
// Map Structure: Accuracy probability (0-100) -> Amount to add to value in both +/- directions so prediction is that accurate
|
||||
ConfidenceRangesMap map[int]float64
|
||||
|
||||
QuantityOfLociKnown int
|
||||
|
||||
QuantityOfPhasedLoci int
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -190,16 +266,21 @@ type CoupleAnalysis struct{
|
|||
// Map Structure: Disease Name -> OffspringPolygenicDiseaseInfo
|
||||
PolygenicDiseasesMap map[string]OffspringPolygenicDiseaseInfo
|
||||
|
||||
// Discrete traits are traits with discrete outcomes, such as Eye Color
|
||||
// Map Structure: Trait Name -> Trait Info Object
|
||||
TraitsMap map[string]OffspringTraitInfo
|
||||
DiscreteTraitsMap map[string]OffspringDiscreteTraitInfo
|
||||
|
||||
// Numeric traits are traits with numeric outcomes, such as Height
|
||||
// Map Structure: Trait Name -> Trait Info Object
|
||||
NumericTraitsMap map[string]OffspringNumericTraitInfo
|
||||
}
|
||||
|
||||
|
||||
type OffspringMonogenicDiseaseInfo struct{
|
||||
|
||||
// This map stores the number of variants tested in each person's genome
|
||||
// This map stores the quantity of variants tested in each person's genome
|
||||
// Map Structure: Genome Identifier -> Number of variants tested
|
||||
NumberOfVariantsTestedMap map[[16]byte]int
|
||||
QuantityOfVariantsTestedMap map[[16]byte]int
|
||||
|
||||
// This map stores the offspring disease probabilities for each genome pair.
|
||||
// A genome pair is a concatenation of two genome identifiers
|
||||
|
|
@ -215,7 +296,6 @@ type OffspringMonogenicDiseaseInfo struct{
|
|||
type OffspringGenomePairMonogenicDiseaseInfo struct{
|
||||
|
||||
// At least 1 variant's information is needed from either person to include the diseaseInfo object in the MonogenicDiseaseInfoMap
|
||||
|
||||
ProbabilityOffspringHasDiseaseIsKnown bool
|
||||
|
||||
// This is the probability that the offspring will have the disease
|
||||
|
|
@ -259,8 +339,8 @@ type OffspringPolygenicDiseaseInfo struct{
|
|||
|
||||
type OffspringGenomePairPolygenicDiseaseInfo struct{
|
||||
|
||||
// This should be len(DiseaseLociList)
|
||||
NumberOfLociTested int
|
||||
// This should be len(LociInfoMap)
|
||||
QuantityOfLociTested int
|
||||
|
||||
// A number between 1-10 representing the offspring's average risk score
|
||||
// 1 == lowest risk, 10 == highest risk
|
||||
|
|
@ -297,27 +377,110 @@ type OffspringPolygenicDiseaseLocusInfo struct{
|
|||
}
|
||||
|
||||
|
||||
type OffspringTraitInfo struct{
|
||||
type OffspringDiscreteTraitInfo struct{
|
||||
|
||||
// This map stores the trait info for each genome pair
|
||||
// Map Structure: Genome Pair Identifier -> OffspringGenomePairTraitInfo
|
||||
TraitInfoMap map[[32]byte]OffspringGenomePairTraitInfo
|
||||
TraitInfoMap map[[32]byte]OffspringGenomePairDiscreteTraitInfo
|
||||
|
||||
ConflictExists bool
|
||||
}
|
||||
|
||||
type OffspringGenomePairTraitInfo struct{
|
||||
// For a trait analysis, both analysis methods may exist in the results
|
||||
// However, the GUI will only display the results from one of the methods.
|
||||
// The neural network prediction is always prioritized over the rule-based prediction
|
||||
type OffspringGenomePairDiscreteTraitInfo struct{
|
||||
|
||||
// This should be len(TraitRulesList)
|
||||
NumberOfRulesTested int
|
||||
// This is true if it is possible to analyze this trait using a neural network
|
||||
NeuralNetworkExists bool
|
||||
|
||||
// Map Structure: Outcome Name -> Outcome Score
|
||||
// Example: "Intolerant" -> 2.5
|
||||
OffspringAverageOutcomeScoresMap map[string]float64
|
||||
// This is true if a neural network analysis was performed for this genome
|
||||
// This means that at least 1 locus for this trait was contained in both of the genomes in the pair
|
||||
NeuralNetworkAnalysisExists bool
|
||||
|
||||
NeuralNetworkAnalysis OffspringGenomePairDiscreteTraitInfo_NeuralNetwork
|
||||
|
||||
// This is true if it is possible to analyze this trait using rules
|
||||
RulesExist bool
|
||||
|
||||
// This is true if a rules-based analysis was performed for this genome
|
||||
// This means that all of the loci for at least 1 rule for this trait was contained in both of the genomes in the pair
|
||||
// Also, none of the offspring have an unknown outcome caused by an outcome score tie
|
||||
RulesAnalysisExists bool
|
||||
|
||||
RulesAnalysis OffspringGenomePairDiscreteTraitInfo_Rules
|
||||
}
|
||||
|
||||
|
||||
type OffspringGenomePairDiscreteTraitInfo_NeuralNetwork struct{
|
||||
|
||||
// Map Structure: Outcome Name -> Outcome Probability (0-100)
|
||||
// Example: "Intolerant" -> 5
|
||||
OffspringOutcomeProbabilitiesMap map[string]int
|
||||
|
||||
// Probability (0-100) that each outcome from the neural network is true
|
||||
// This is an average of the confidence for each of the calculated 100 outcome probabilities
|
||||
AverageConfidence int
|
||||
|
||||
QuantityOfLociKnown int
|
||||
|
||||
// This describes the quantity of loci from both parents that are phased
|
||||
// For example, if there are 10 loci for this trait, and one parent has 10 phased loci and the other has 5,
|
||||
// this variable will have a value of 15
|
||||
QuantityOfParentalPhasedLoci int
|
||||
}
|
||||
|
||||
type OffspringGenomePairDiscreteTraitInfo_Rules struct{
|
||||
|
||||
// Map Structure: Outcome Name -> Outcome Probability (0-100)
|
||||
// Example: "Intolerant" -> 5
|
||||
OffspringOutcomeProbabilitiesMap map[string]int
|
||||
|
||||
// Map Structure: Rule Identifier -> Offspring Probability Of Passing Rule
|
||||
// The value stores the probability that the offspring will pass the rule
|
||||
// This is a number between 0-100%
|
||||
ProbabilityOfPassingRulesMap map[[3]byte]int
|
||||
|
||||
// This should be len(ProbabilityOfPassingRulesMap)
|
||||
QuantityOfRulesTested int
|
||||
|
||||
// This only counts the loci which are used for rules
|
||||
// For example, loci that are only used in neural-network-based prediction are not counted
|
||||
QuantityOfLociKnown int
|
||||
}
|
||||
|
||||
type OffspringNumericTraitInfo struct{
|
||||
|
||||
// This map stores the trait info for each genome pair
|
||||
// Map Structure: Genome Pair Identifier -> OffspringGenomePairNumericTraitInfo
|
||||
TraitInfoMap map[[32]byte]OffspringGenomePairNumericTraitInfo
|
||||
|
||||
ConflictExists bool
|
||||
}
|
||||
|
||||
type OffspringGenomePairNumericTraitInfo struct{
|
||||
|
||||
// The average outcome for the offspring
|
||||
// For example, the average height for an offspring between these 2 people
|
||||
OffspringAverageOutcome float64
|
||||
|
||||
// This map stores the confidence ranges for the predicted value
|
||||
// If we want to know how accurate the prediction is with a X% accuracy, how far would we have to expand the
|
||||
// predicted value's range to be accurate, X% of the time?
|
||||
// For example: 50% accuracy requires a +/-5 point range, 80% accuracy requires a +-15 point range
|
||||
// Map Structure: Accuracy probability (0-100) -> Amount to add to value in both +/- directions so prediction is that accurate
|
||||
AverageConfidenceRangesMap map[int]float64
|
||||
|
||||
// This describes the quantity of loci from both parents that are phased
|
||||
// For example, if there are 10 loci for this trait, and one parent has 10 phased loci and the other has 5,
|
||||
// this variable will have a value of 15
|
||||
QuantityOfParentalPhasedLoci int
|
||||
|
||||
QuantityOfLociKnown int
|
||||
|
||||
// A list of 100 offspring outcomes for 100 prospective offspring from the genome pair
|
||||
// Example: A list of heights for 100 prospective offspring
|
||||
SampleOffspringOutcomesList []float64
|
||||
}
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -11,6 +11,7 @@ package geneticPrediction
|
|||
// We could create slower models that provide more accurate predictions
|
||||
|
||||
import "seekia/resources/geneticReferences/traits"
|
||||
import "seekia/resources/geneticPredictionModels"
|
||||
|
||||
import "seekia/internal/genetics/locusValue"
|
||||
import "seekia/internal/genetics/readBiobankData"
|
||||
|
|
@ -211,6 +212,252 @@ func DecodeBytesToNeuralNetworkObject(inputNeuralNetwork []byte)(NeuralNetwork,
|
|||
return newNeuralNetworkObject, nil
|
||||
}
|
||||
|
||||
// This map is used to store information about how accurate genetic prediction models are
|
||||
// Map Structure: Trait Outcome Info -> Trait Prediction Accuracy Info
|
||||
type TraitPredictionAccuracyInfoMap map[TraitOutcomeInfo]TraitPredictionAccuracyInfo
|
||||
|
||||
type TraitOutcomeInfo struct{
|
||||
|
||||
// This is the outcome which was found
|
||||
// Example: "Blue"
|
||||
OutcomeName string
|
||||
|
||||
// This is a value between 0-100 which describes the percentage of the loci which were tested for the input for the prediction
|
||||
PercentageOfLociTested int
|
||||
|
||||
// This is a value between 0-100 which describes the percentage of the tested loci which were phased for the input for the prediction
|
||||
PercentageOfPhasedLoci int
|
||||
}
|
||||
|
||||
type TraitPredictionAccuracyInfo struct{
|
||||
|
||||
// This contains the quantity of examples for the outcome with the specified percentageOfLociTested and percentageOfPhasedLoci
|
||||
QuantityOfExamples int
|
||||
|
||||
// This contains the quantity of predictions for the outcome with the specified percentageOfLociTested and percentageOfPhasedLoci
|
||||
// Prediction = our model predicted this outcome
|
||||
QuantityOfPredictions int
|
||||
|
||||
// This stores the probability (0-100) that our model will accurately predict this outcome for a genome which has
|
||||
// the specified percentageOfLociTested and percentageOfPhasedLoci
|
||||
// In other words: What is the probability that if you give Seekia a blue-eyed genome, it will give you a correct Blue prediction?
|
||||
// This value is only accurate is QuantityOfExamples > 0
|
||||
ProbabilityOfCorrectGenomePrediction int
|
||||
|
||||
// This stores the probability (0-100) that our model is correct if our model predicts that a genome
|
||||
// with the specified percentageOfLociTested and percentageOfPhasedLoci has this outcome
|
||||
// In other words: What is the probability that if Seekia says a genome will have blue eyes, it is correct?
|
||||
// This value is only accurate is QuantityOfPredictions > 0
|
||||
ProbabilityOfCorrectOutcomePrediction int
|
||||
}
|
||||
|
||||
func EncodeTraitPredictionAccuracyInfoMapToBytes(inputMap TraitPredictionAccuracyInfoMap)([]byte, error){
|
||||
|
||||
buffer := new(bytes.Buffer)
|
||||
|
||||
encoder := gob.NewEncoder(buffer)
|
||||
|
||||
err := encoder.Encode(inputMap)
|
||||
if (err != nil) { return nil, err }
|
||||
|
||||
inputMapBytes := buffer.Bytes()
|
||||
|
||||
return inputMapBytes, nil
|
||||
}
|
||||
|
||||
func DecodeBytesToTraitPredictionAccuracyInfoMap(inputBytes []byte)(TraitPredictionAccuracyInfoMap, error){
|
||||
|
||||
if (inputBytes == nil){
|
||||
return nil, errors.New("DecodeBytesToTraitPredictionAccuracyInfoMap called with nil inputBytes.")
|
||||
}
|
||||
|
||||
buffer := bytes.NewBuffer(inputBytes)
|
||||
|
||||
decoder := gob.NewDecoder(buffer)
|
||||
|
||||
var newTraitPredictionAccuracyInfoMap TraitPredictionAccuracyInfoMap
|
||||
|
||||
err := decoder.Decode(&newTraitPredictionAccuracyInfoMap)
|
||||
if (err != nil){ return nil, err }
|
||||
|
||||
return newTraitPredictionAccuracyInfoMap, nil
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
// -bool: Neural network model exists for this trait (trait prediction is possible for this trait)
|
||||
// -bool: Trait prediction is possible for this user (User has at least 1 known trait locus value)
|
||||
// -string: Predicted trait outcome (Example: "Blue")
|
||||
// -int: Confidence: Probability (0-100) that the prediction is accurate
|
||||
// -int: Quantity of loci known
|
||||
// -int: Quantity of phased loci
|
||||
// -error
|
||||
func GetNeuralNetworkTraitPredictionFromGenomeMap(traitName string, genomeMap map[int64]locusValue.LocusValue)(bool, bool, string, int, int, int, error){
|
||||
|
||||
traitObject, err := traits.GetTraitObject(traitName)
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
|
||||
// This is a map of rsIDs which influence this trait
|
||||
traitRSIDsList := traitObject.LociList
|
||||
|
||||
if (len(traitRSIDsList) == 0){
|
||||
// Neural network trait prediction is not possible for this trait
|
||||
return false, false, "", 0, 0, 0, nil
|
||||
}
|
||||
|
||||
predictionModelExists, predictionModelBytes := geneticPredictionModels.GetGeneticPredictionModelBytes(traitName)
|
||||
if (predictionModelExists == false){
|
||||
// Neural network trait prediction is not possible for this trait
|
||||
return false, false, "", 0, 0, 0, nil
|
||||
}
|
||||
|
||||
traitRSIDsListCopy := slices.Clone(traitRSIDsList)
|
||||
slices.Sort(traitRSIDsListCopy)
|
||||
|
||||
// In the inputLayer, each locus value is represented by 3 neurons:
|
||||
// 1. LocusExists/LocusIsPhased
|
||||
// -0 = Locus value is unknown
|
||||
// -0.5 = Locus Is known, phase is unknown
|
||||
// -1 = Locus Is Known, phase is known
|
||||
// 2. Allele1 Locus Value (Value between 0-1)
|
||||
// -0 = Value is unknown
|
||||
// 3. Allele2 Locus Value (Value between 0-1)
|
||||
// -0 = Value is unknown
|
||||
//
|
||||
neuralNetworkInput := make([]float32, 0)
|
||||
|
||||
quantityOfLociKnown := 0
|
||||
quantityOfPhasedLoci := 0
|
||||
|
||||
for _, rsID := range traitRSIDsListCopy{
|
||||
|
||||
userLocusValue, exists := genomeMap[rsID]
|
||||
if (exists == false){
|
||||
neuralNetworkInput = append(neuralNetworkInput, 0, 0, 0)
|
||||
continue
|
||||
}
|
||||
|
||||
quantityOfLociKnown += 1
|
||||
|
||||
locusAllele1 := userLocusValue.Base1Value
|
||||
locusAllele2 := userLocusValue.Base2Value
|
||||
locusIsPhased := userLocusValue.LocusIsPhased
|
||||
|
||||
getNeuron1 := func()float32{
|
||||
if (locusIsPhased == false){
|
||||
return 0.5
|
||||
}
|
||||
|
||||
quantityOfPhasedLoci += 1
|
||||
return 1
|
||||
}
|
||||
|
||||
neuron1 := getNeuron1()
|
||||
|
||||
neuron2, err := convertAlleleToNeuron(locusAllele1)
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
|
||||
neuron3, err := convertAlleleToNeuron(locusAllele2)
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
|
||||
neuralNetworkInput = append(neuralNetworkInput, neuron1, neuron2, neuron3)
|
||||
}
|
||||
|
||||
if (quantityOfLociKnown == 0){
|
||||
// We can't predict anything about this trait for this genome
|
||||
return true, false, "", 0, 0, 0, nil
|
||||
}
|
||||
|
||||
neuralNetworkObject, err := DecodeBytesToNeuralNetworkObject(predictionModelBytes)
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
|
||||
outputLayer, err := GetNeuralNetworkRawPrediction(&neuralNetworkObject, neuralNetworkInput)
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
|
||||
predictedOutcomeName, err := GetOutcomeNameFromOutputLayer(traitName, false, outputLayer)
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
|
||||
modelTraitAccuracyInfoFile, err := geneticPredictionModels.GetPredictionModelTraitAccuracyInfoBytes(traitName)
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
|
||||
modelTraitAccuracyInfoMap, err := DecodeBytesToTraitPredictionAccuracyInfoMap(modelTraitAccuracyInfoFile)
|
||||
if (err != nil) { return false, false, "", 0, 0, 0, err }
|
||||
|
||||
// We find the model trait accuracy info object that is the most similar to our predicted outcome
|
||||
|
||||
getPredictionAccuracy := func()int{
|
||||
|
||||
totalNumberOfTraitLoci := len(traitRSIDsList)
|
||||
|
||||
proportionOfLociTested := float64(quantityOfLociKnown)/float64(totalNumberOfTraitLoci)
|
||||
percentageOfLociTested := int(proportionOfLociTested * 100)
|
||||
|
||||
proportionOfPhasedLoci := float64(quantityOfPhasedLoci)/float64(totalNumberOfTraitLoci)
|
||||
percentageOfPhasedLoci := int(proportionOfPhasedLoci * 100)
|
||||
|
||||
// This is a value between 0 and 100 that represents the most likely accuracy probability for this prediction
|
||||
closestPredictionAccuracy := 0
|
||||
|
||||
// This is a value that represents the distance our closest prediction accuracy has from the current prediction
|
||||
// Consider each prediction accuracy value on an (X,Y) coordinate plane
|
||||
// X = Number of loci tested
|
||||
// Y = Number of phased loci
|
||||
closestPredictionAccuracyDistance := float64(0)
|
||||
|
||||
anyOutcomeAccuracyFound := false
|
||||
|
||||
for traitOutcomeInfo, traitPredictionAccuracyInfo := range modelTraitAccuracyInfoMap{
|
||||
|
||||
outcomeName := traitOutcomeInfo.OutcomeName
|
||||
if (outcomeName != predictedOutcomeName){
|
||||
continue
|
||||
}
|
||||
|
||||
probabilityOfCorrectOutcomePrediction := traitPredictionAccuracyInfo.ProbabilityOfCorrectOutcomePrediction
|
||||
|
||||
currentPercentageOfLociTested := traitOutcomeInfo.PercentageOfLociTested
|
||||
currentPercentageOfPhasedLoci := traitOutcomeInfo.PercentageOfPhasedLoci
|
||||
|
||||
// Distance Formula for 2 coordinates (x1, y1) and (x2, y2):
|
||||
// distance = √((x2 - x1)^2 + (y2 - y1)^2)
|
||||
|
||||
differenceInX := float64(currentPercentageOfLociTested - percentageOfLociTested)
|
||||
differenceInY := float64(currentPercentageOfPhasedLoci - percentageOfPhasedLoci)
|
||||
|
||||
distance := math.Sqrt(math.Pow(differenceInX, 2) + math.Pow(differenceInY, 2))
|
||||
|
||||
if (distance == 0){
|
||||
// We found the exact prediction accuracy
|
||||
return probabilityOfCorrectOutcomePrediction
|
||||
}
|
||||
|
||||
if (anyOutcomeAccuracyFound == false){
|
||||
closestPredictionAccuracyDistance = distance
|
||||
closestPredictionAccuracy = probabilityOfCorrectOutcomePrediction
|
||||
anyOutcomeAccuracyFound = true
|
||||
continue
|
||||
} else {
|
||||
if (distance < closestPredictionAccuracyDistance){
|
||||
closestPredictionAccuracyDistance = distance
|
||||
closestPredictionAccuracy = probabilityOfCorrectOutcomePrediction
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (anyOutcomeAccuracyFound == false){
|
||||
// This means that our model has never actually predicted this outcome
|
||||
// This shouldn't happen unless our model is really bad, or our training set has very few people with this outcome.
|
||||
// We return a 0% accuracy rating
|
||||
return 0
|
||||
}
|
||||
|
||||
return closestPredictionAccuracy
|
||||
}
|
||||
|
||||
predictionAccuracy := getPredictionAccuracy()
|
||||
|
||||
return true, true, predictedOutcomeName, predictionAccuracy, quantityOfLociKnown, quantityOfPhasedLoci, nil
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
// -int: Number of loci values that are known
|
||||
// -int: Number of loci values that are known and phased
|
||||
|
|
@ -437,9 +684,9 @@ func CreateGeneticPredictionTrainingData_OpenSNP(
|
|||
if (err != nil) { return false, nil, err }
|
||||
|
||||
// This is a list of rsIDs which influence this trait
|
||||
traitRSIDs := traitObject.LociList
|
||||
traitRSIDsList := traitObject.LociList
|
||||
|
||||
if (len(traitRSIDs) == 0){
|
||||
if (len(traitRSIDsList) == 0){
|
||||
return false, nil, errors.New("traitObject contains no rsIDs.")
|
||||
}
|
||||
|
||||
|
|
@ -457,7 +704,7 @@ func CreateGeneticPredictionTrainingData_OpenSNP(
|
|||
// -0 = Locus value is unknown
|
||||
// -0.5 = Locus Is known, phase is unknown
|
||||
// -1 = Locus Is Known, phase is known
|
||||
expectedNumberOfInputLayerRows := len(traitRSIDs) * 3
|
||||
expectedNumberOfInputLayerRows := len(traitRSIDsList) * 3
|
||||
|
||||
if (numberOfInputLayerRows != expectedNumberOfInputLayerRows){
|
||||
|
||||
|
|
@ -468,7 +715,7 @@ func CreateGeneticPredictionTrainingData_OpenSNP(
|
|||
|
||||
checkIfAnyTraitLocusValuesExist := func()bool{
|
||||
|
||||
for _, rsID := range traitRSIDs{
|
||||
for _, rsID := range traitRSIDsList{
|
||||
|
||||
_, exists := userLocusValuesMap[rsID]
|
||||
if (exists == true){
|
||||
|
|
@ -487,11 +734,9 @@ func CreateGeneticPredictionTrainingData_OpenSNP(
|
|||
}
|
||||
|
||||
// We sort rsIDs in ascending order
|
||||
// We copy list so we don't change the original
|
||||
|
||||
traitRSIDsList := slices.Clone(traitRSIDs)
|
||||
|
||||
slices.Sort(traitRSIDsList)
|
||||
traitRSIDsListCopy := slices.Clone(traitRSIDsList)
|
||||
slices.Sort(traitRSIDsListCopy)
|
||||
|
||||
// This function returns the outputLayer for all trainingDatas for this user
|
||||
// Each outputLayer represents the user's trait value (Example: "Blue" for Eye Color)
|
||||
|
|
@ -637,11 +882,11 @@ func CreateGeneticPredictionTrainingData_OpenSNP(
|
|||
|
||||
anyLocusExists := false
|
||||
|
||||
inputLayerLength := len(traitRSIDsList) * 3
|
||||
inputLayerLength := len(traitRSIDsListCopy) * 3
|
||||
|
||||
inputLayer := make([]float32, 0, inputLayerLength)
|
||||
|
||||
for _, rsID := range traitRSIDsList{
|
||||
for _, rsID := range traitRSIDsListCopy{
|
||||
|
||||
randomFloat := pseudorandomNumberGenerator.Float64()
|
||||
if (randomFloat > probabilityOfUsingLoci){
|
||||
|
|
@ -996,7 +1241,7 @@ func (inputNetwork *NeuralNetwork)buildNeuralNetwork(inputLayer *gorgonia.Node)e
|
|||
|
||||
inputLayerCopy := inputLayer
|
||||
|
||||
// We multiply weights at each layer and perform sigmoid after each multiplication
|
||||
// We multiply weights at each layer and perform ReLU (Rectification) after each multiplication
|
||||
|
||||
weights1 := inputNetwork.weights1
|
||||
|
||||
|
|
|
|||
|
|
@ -27,7 +27,6 @@ var myCacheChosenGeneticAnalysisIdentifier string
|
|||
|
||||
// We use this variable to store the analysis in memory
|
||||
// This prevents us from having to read and unmarshal the messagepack file each time we want to retrieve the analysis
|
||||
// TODO: Read attributes from the analysis into maps for faster retrieval
|
||||
var myCacheChosenGeneticAnalysis geneticAnalysis.PersonAnalysis
|
||||
|
||||
// These variables store metadata about the cache genetic analysis
|
||||
|
|
@ -36,6 +35,7 @@ var myCacheChosenGeneticAnalysis_GenomeIdentifierToUse [16]byte
|
|||
// This variable tells us if the current cache chosen genetic analysis contains multiple genomes
|
||||
var myCacheChosenGeneticAnalysis_MultipleGenomesExist bool
|
||||
|
||||
|
||||
// This function is used to retrieve the user's chosen person genetic analysis
|
||||
// The user must choose a person to link to their mate profile/identity
|
||||
// This genetic analysis is not shared on the person's profile publicly.
|
||||
|
|
@ -101,7 +101,7 @@ func GetMyChosenMateGeneticAnalysis()(bool, bool, bool, geneticAnalysis.PersonAn
|
|||
return false, false, false, emptyPersonAnalysis, [16]byte{}, false, errors.New("CheckIfPersonAnalysisIsReady returning missing genetic analysis.")
|
||||
}
|
||||
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(myGeneticAnalysisObject)
|
||||
allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(myGeneticAnalysisObject)
|
||||
if (err != nil) { return false, false, false, emptyPersonAnalysis, [16]byte{}, false, err }
|
||||
|
||||
getGenomeIdentifierToUse := func()([16]byte, error){
|
||||
|
|
|
|||
|
|
@ -6,6 +6,7 @@ package myGenomes
|
|||
|
||||
import "seekia/internal/cryptography/blake3"
|
||||
import "seekia/internal/encoding"
|
||||
import "seekia/internal/genetics/prepareRawGenomes"
|
||||
import "seekia/internal/genetics/readRawGenomes"
|
||||
import "seekia/internal/helpers"
|
||||
import "seekia/internal/localFilesystem"
|
||||
|
|
@ -106,11 +107,18 @@ func AddRawGenome(personIdentifier string, rawGenomeString string)(bool, bool, e
|
|||
|
||||
rawGenomeReader := strings.NewReader(rawGenomeString)
|
||||
|
||||
companyName, importVersion, timeFileWasGenerated, snpCount, genomeIsPhased, _, err := readRawGenomes.ReadRawGenomeFile(rawGenomeReader)
|
||||
companyName, importVersion, timeFileWasGenerated, snpCount, genomeIsPhased, rawGenomeMap, err := readRawGenomes.ReadRawGenomeFile(rawGenomeReader)
|
||||
if (err != nil){
|
||||
return false, false, nil
|
||||
}
|
||||
|
||||
genomeHasUsefulLocations, _, err := prepareRawGenomes.ConvertRawGenomeToGenomeMap(rawGenomeMap, genomeIsPhased)
|
||||
if (err != nil) { return false, false, err }
|
||||
if (genomeHasUsefulLocations == false){
|
||||
//TODO: Explain this to the user rather than just telling the user that the file is invalid
|
||||
return false, false, nil
|
||||
}
|
||||
|
||||
genomeIdentifier, err := helpers.GetNewRandomHexString(16)
|
||||
if (err != nil) { return false, false, err }
|
||||
|
||||
|
|
|
|||
|
|
@ -76,6 +76,10 @@ func CreateRawGenomeWithMetadataObject(genomeIdentifier [16]byte, rawGenomeStrin
|
|||
// -error
|
||||
func GetGenomesWithMetadataListFromRawGenomesList(inputGenomesList []RawGenomeWithMetadata, updatePercentageCompleteFunction func(int)error)([]GenomeWithMetadata, [][16]byte, bool, [16]byte, [16]byte, error){
|
||||
|
||||
if (len(inputGenomesList) == 0){
|
||||
return nil, nil, false, [16]byte{}, [16]byte{}, errors.New("GetGenomesWithMetadataListFromRawGenomesList called with empty inputGenomesList")
|
||||
}
|
||||
|
||||
// The reading of genomes will take up the first 20% of the percentage range
|
||||
// The creation of multiple genomes will take up the last 80% of the percentage range
|
||||
|
||||
|
|
@ -102,103 +106,13 @@ func GetGenomesWithMetadataListFromRawGenomesList(inputGenomesList []RawGenomeWi
|
|||
|
||||
// Now we convert rawGenomeMap to a genomeMap
|
||||
|
||||
// Map Structure: RSID -> Locus Value
|
||||
genomeMap := make(map[int64]locusValue.LocusValue)
|
||||
|
||||
// We use this list to check for alias collisions later
|
||||
allRSIDsList := make([]int64, 0)
|
||||
|
||||
for rsID, locusBasePairValue := range rawGenomeMap{
|
||||
|
||||
locusAllele2Exists := locusBasePairValue.Allele2Exists
|
||||
if (locusAllele2Exists == false){
|
||||
// This SNP contains less than 2 bases
|
||||
// We don't support reading these kinds of SNP values yet
|
||||
continue
|
||||
}
|
||||
|
||||
locusAllele1 := locusBasePairValue.Allele1
|
||||
locusAllele2 := locusBasePairValue.Allele2
|
||||
|
||||
getLocusIsPhasedBool := func()bool{
|
||||
|
||||
if (locusAllele1 == locusAllele2){
|
||||
// Locus has to be phased, because phase flip does not change value
|
||||
return true
|
||||
}
|
||||
|
||||
return genomeIsPhased
|
||||
}
|
||||
|
||||
locusIsPhased := getLocusIsPhasedBool()
|
||||
|
||||
locusValueObject := locusValue.LocusValue{
|
||||
LocusIsPhased: locusIsPhased,
|
||||
Base1Value: locusAllele1,
|
||||
Base2Value: locusAllele2,
|
||||
}
|
||||
|
||||
genomeMap[rsID] = locusValueObject
|
||||
|
||||
allRSIDsList = append(allRSIDsList, rsID)
|
||||
}
|
||||
|
||||
// Now we check for rsID aliases
|
||||
// rsID aliases are multiple rsids that refer to the same location
|
||||
// If a single genome file contained two identical rsids whose value conflicted, the company must have made an error in reporting
|
||||
|
||||
for _, rsID := range allRSIDsList{
|
||||
|
||||
rsidLocusValue, exists := genomeMap[rsID]
|
||||
if (exists == false){
|
||||
// This must have been an alias that was deleted
|
||||
continue
|
||||
}
|
||||
|
||||
aliasExists, rsidAliasesList, err := locusMetadata.GetRSIDAliases(rsID)
|
||||
if (err != nil){ return nil, nil, false, [16]byte{}, [16]byte{}, err }
|
||||
if (aliasExists == false){
|
||||
continue
|
||||
}
|
||||
|
||||
checkIfRSIDCollisionExists := func()bool{
|
||||
|
||||
for _, rsidAlias := range rsidAliasesList{
|
||||
|
||||
aliasLocusValue, exists := genomeMap[rsidAlias]
|
||||
if (exists == false){
|
||||
continue
|
||||
}
|
||||
|
||||
if (aliasLocusValue != rsidLocusValue){
|
||||
// A collision exists with an alias rsID
|
||||
// The company must be creating invalid results, or our alias list is invalid
|
||||
return true
|
||||
}
|
||||
}
|
||||
|
||||
return false
|
||||
}
|
||||
|
||||
rsidCollisionExists := checkIfRSIDCollisionExists()
|
||||
if (rsidCollisionExists == true){
|
||||
// We will delete this rsID
|
||||
// We cannot trust any of the results
|
||||
|
||||
delete(genomeMap, rsID)
|
||||
}
|
||||
|
||||
// We delete all aliases from the genome map
|
||||
// We do this to save space
|
||||
|
||||
for _, rsidAlias := range rsidAliasesList{
|
||||
delete(genomeMap, rsidAlias)
|
||||
}
|
||||
}
|
||||
|
||||
if (len(genomeMap) == 0){
|
||||
// No valid locations exist
|
||||
continue
|
||||
anyValuesExist, genomeMap, err := ConvertRawGenomeToGenomeMap(rawGenomeMap, genomeIsPhased)
|
||||
if (err != nil) { return nil, nil, false, [16]byte{}, [16]byte{}, err }
|
||||
if (anyValuesExist == false){
|
||||
// We have to make sure this never happens so the user isn't confused as to why genomes
|
||||
// that were imported were not included in the analysis
|
||||
// We make sure this doesn't happen by verifying the genome at the time of importing
|
||||
return nil, nil, false, [16]byte{}, [16]byte{}, errors.New("Genome supplied to GetGenomesWithMetadataListFromRawGenomesList has no valid locations.")
|
||||
}
|
||||
|
||||
genomeWithMetadataObject := GenomeWithMetadata{
|
||||
|
|
@ -221,9 +135,9 @@ func GetGenomesWithMetadataListFromRawGenomesList(inputGenomesList []RawGenomeWi
|
|||
err := updatePercentageCompleteFunction(20)
|
||||
if (err != nil){ return nil, nil, false, [16]byte{}, [16]byte{}, err }
|
||||
|
||||
if (len(genomesWithMetadataList) == 1){
|
||||
if (len(genomesWithMetadataList) <= 1){
|
||||
|
||||
// Only 1 genome exists.
|
||||
// <=1 genome exists.
|
||||
// No genome combining is needed.
|
||||
|
||||
err = updatePercentageCompleteFunction(100)
|
||||
|
|
@ -547,4 +461,112 @@ func GetGenomesWithMetadataListFromRawGenomesList(inputGenomesList []RawGenomeWi
|
|||
return genomesWithMetadataList, allRawGenomeIdentifiersList, true, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, nil
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
// -bool: Genome has any useful locations
|
||||
// -map[int64]locusValue.LocusValue
|
||||
// -error
|
||||
func ConvertRawGenomeToGenomeMap(rawGenomeMap map[int64]readRawGenomes.RawGenomeLocusValue, genomeIsPhased bool)(bool, map[int64]locusValue.LocusValue, error){
|
||||
|
||||
// Map Structure: RSID -> Locus Value
|
||||
genomeMap := make(map[int64]locusValue.LocusValue)
|
||||
|
||||
// We use this list to check for alias collisions later
|
||||
allRSIDsList := make([]int64, 0)
|
||||
|
||||
for rsID, locusBasePairValue := range rawGenomeMap{
|
||||
|
||||
locusAllele2Exists := locusBasePairValue.Allele2Exists
|
||||
if (locusAllele2Exists == false){
|
||||
// This SNP contains less than 2 bases
|
||||
// We don't support reading these kinds of SNP values yet
|
||||
continue
|
||||
}
|
||||
|
||||
locusAllele1 := locusBasePairValue.Allele1
|
||||
locusAllele2 := locusBasePairValue.Allele2
|
||||
|
||||
getLocusIsPhasedBool := func()bool{
|
||||
|
||||
if (locusAllele1 == locusAllele2){
|
||||
// Locus has to be phased, because phase flip does not change value
|
||||
return true
|
||||
}
|
||||
|
||||
return genomeIsPhased
|
||||
}
|
||||
|
||||
locusIsPhased := getLocusIsPhasedBool()
|
||||
|
||||
locusValueObject := locusValue.LocusValue{
|
||||
Base1Value: locusAllele1,
|
||||
Base2Value: locusAllele2,
|
||||
LocusIsPhased: locusIsPhased,
|
||||
}
|
||||
|
||||
genomeMap[rsID] = locusValueObject
|
||||
|
||||
allRSIDsList = append(allRSIDsList, rsID)
|
||||
}
|
||||
|
||||
// Now we check for rsID aliases
|
||||
// rsID aliases are multiple rsids that refer to the same location
|
||||
// If a single genome file contained two identical rsids whose value conflicted, the company must have made an error in reporting
|
||||
|
||||
for _, rsID := range allRSIDsList{
|
||||
|
||||
rsidLocusValue, exists := genomeMap[rsID]
|
||||
if (exists == false){
|
||||
// This must have been an alias that was deleted
|
||||
continue
|
||||
}
|
||||
|
||||
aliasExists, rsidAliasesList, err := locusMetadata.GetRSIDAliases(rsID)
|
||||
if (err != nil){ return false, nil, err }
|
||||
if (aliasExists == false){
|
||||
continue
|
||||
}
|
||||
|
||||
checkIfRSIDCollisionExists := func()bool{
|
||||
|
||||
for _, rsidAlias := range rsidAliasesList{
|
||||
|
||||
aliasLocusValue, exists := genomeMap[rsidAlias]
|
||||
if (exists == false){
|
||||
continue
|
||||
}
|
||||
|
||||
if (aliasLocusValue != rsidLocusValue){
|
||||
// A collision exists with an alias rsID
|
||||
// The company must be creating invalid results, or our alias list is invalid
|
||||
return true
|
||||
}
|
||||
}
|
||||
|
||||
return false
|
||||
}
|
||||
|
||||
rsidCollisionExists := checkIfRSIDCollisionExists()
|
||||
if (rsidCollisionExists == true){
|
||||
// We will delete this rsID
|
||||
// We cannot trust any of the results
|
||||
|
||||
delete(genomeMap, rsID)
|
||||
}
|
||||
|
||||
// We delete all aliases from the genome map
|
||||
// We do this to save space
|
||||
|
||||
for _, rsidAlias := range rsidAliasesList{
|
||||
|
||||
delete(genomeMap, rsidAlias)
|
||||
}
|
||||
}
|
||||
|
||||
if (len(genomeMap) == 0){
|
||||
// No valid locations exist
|
||||
return false, nil, nil
|
||||
}
|
||||
|
||||
return true, genomeMap, nil
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -47,27 +47,30 @@ func ReadCoupleGeneticAnalysisString(inputAnalysisString string)(geneticAnalysis
|
|||
// -bool: Multiple genomes exist
|
||||
// -[16]byte: OnlyExcludeConflicts GenomeIdentifier
|
||||
// -[16]byte: OnlyIncludeShared GenomeIdentifier
|
||||
// -map[[16]byte]map[int64]locusValue.LocusValue: Genomes locus values map
|
||||
// -error
|
||||
func GetMetadataFromPersonGeneticAnalysis(inputGeneticAnalysis geneticAnalysis.PersonAnalysis)([][16]byte, bool, [16]byte, [16]byte, error){
|
||||
func GetMetadataFromPersonGeneticAnalysis(inputGeneticAnalysis geneticAnalysis.PersonAnalysis)([][16]byte, bool, [16]byte, [16]byte, map[[16]byte]map[int64]locusValue.LocusValue, error){
|
||||
|
||||
analysisVersion := inputGeneticAnalysis.AnalysisVersion
|
||||
if (analysisVersion != 1){
|
||||
// This analysis must have been created by a newer version of Seekia
|
||||
// We cannot read it
|
||||
return nil, false, [16]byte{}, [16]byte{}, errors.New("Cannot read analysis: Is a newer analysis version.")
|
||||
return nil, false, [16]byte{}, [16]byte{}, nil, errors.New("Cannot read analysis: Is a newer analysis version.")
|
||||
}
|
||||
|
||||
allRawGenomeIdentifiersList := inputGeneticAnalysis.AllRawGenomeIdentifiersList
|
||||
|
||||
genomesMap := inputGeneticAnalysis.GenomesMap
|
||||
|
||||
combinedGenomesExist := inputGeneticAnalysis.CombinedGenomesExist
|
||||
if (combinedGenomesExist == false){
|
||||
return allRawGenomeIdentifiersList, false, [16]byte{}, [16]byte{}, nil
|
||||
return allRawGenomeIdentifiersList, false, [16]byte{}, [16]byte{}, genomesMap, nil
|
||||
}
|
||||
|
||||
onlyExcludeConflictsGenomeIdentifier := inputGeneticAnalysis.OnlyExcludeConflictsGenomeIdentifier
|
||||
onlyIncludeSharedGenomeIdentifier := inputGeneticAnalysis.OnlyIncludeSharedGenomeIdentifier
|
||||
|
||||
return allRawGenomeIdentifiersList, true, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, nil
|
||||
return allRawGenomeIdentifiersList, true, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, genomesMap, nil
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
|
|
@ -178,7 +181,7 @@ func GetMatchingPersonAnalysisGenomeIdentifierFromCoupleAnalysis(isPerson1 bool,
|
|||
return inputGenomeIdentifier, true, false, "", nil
|
||||
}
|
||||
|
||||
_, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := GetMetadataFromPersonGeneticAnalysis(person1AnalysisObject)
|
||||
_, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := GetMetadataFromPersonGeneticAnalysis(person1AnalysisObject)
|
||||
if (err != nil) { return [16]byte{}, false, false, "", err }
|
||||
if (multipleGenomesExist == false){
|
||||
return [16]byte{}, false, false, "", errors.New("Couple analysis says person has multiple genomes, person analysis does not.")
|
||||
|
|
@ -204,7 +207,7 @@ func GetMatchingPersonAnalysisGenomeIdentifierFromCoupleAnalysis(isPerson1 bool,
|
|||
return inputGenomeIdentifier, true, false, "", nil
|
||||
}
|
||||
|
||||
_, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := GetMetadataFromPersonGeneticAnalysis(person2AnalysisObject)
|
||||
_, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := GetMetadataFromPersonGeneticAnalysis(person2AnalysisObject)
|
||||
if (err != nil) { return [16]byte{}, false, false, "", err }
|
||||
if (multipleGenomesExist == false){
|
||||
return [16]byte{}, false, false, "", errors.New("Couple analysis says person has multiple genomes, person analysis does not.")
|
||||
|
|
@ -226,9 +229,9 @@ func GetMatchingPersonAnalysisGenomeIdentifierFromCoupleAnalysis(isPerson1 bool,
|
|||
// -bool: Person has disease
|
||||
// -int: Probability of passing a disease variant
|
||||
// -string: Probability of passing a disease variant formatted (with % suffix)
|
||||
// -int: Number of variants tested
|
||||
// -int: Number of loci tested
|
||||
// -int: Number of phased loci
|
||||
// -int: Quantity of variants tested
|
||||
// -int: Quantity of loci tested
|
||||
// -int: Quantity of phased loci
|
||||
// -bool: Conflict exists
|
||||
// -error
|
||||
func GetPersonMonogenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnalysis, diseaseName string, genomeIdentifier [16]byte)(bool, bool, int, string, int, int, int, bool, error){
|
||||
|
|
@ -250,16 +253,16 @@ func GetPersonMonogenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject genet
|
|||
conflictExists := personMonogenicDiseaseInfo.ConflictExists
|
||||
|
||||
personHasDisease := genomeMonogenicDiseaseInfo.PersonHasDisease
|
||||
numberOfVariantsTested := genomeMonogenicDiseaseInfo.NumberOfVariantsTested
|
||||
numberOfLociTested := genomeMonogenicDiseaseInfo.NumberOfLociTested
|
||||
numberOfPhasedLoci := genomeMonogenicDiseaseInfo.NumberOfPhasedLoci
|
||||
quantityOfVariantsTested := genomeMonogenicDiseaseInfo.QuantityOfVariantsTested
|
||||
quantityOfLociTested := genomeMonogenicDiseaseInfo.QuantityOfLociTested
|
||||
quantityOfPhasedLoci := genomeMonogenicDiseaseInfo.QuantityOfPhasedLoci
|
||||
probabilityOfPassingAVariant := genomeMonogenicDiseaseInfo.ProbabilityOfPassingADiseaseVariant
|
||||
|
||||
probabilityOfPassingAVariantString := helpers.ConvertIntToString(probabilityOfPassingAVariant)
|
||||
|
||||
probabilityOfPassingAVariantFormatted := probabilityOfPassingAVariantString + "%"
|
||||
|
||||
return true, personHasDisease, probabilityOfPassingAVariant, probabilityOfPassingAVariantFormatted, numberOfVariantsTested, numberOfLociTested, numberOfPhasedLoci, conflictExists, nil
|
||||
return true, personHasDisease, probabilityOfPassingAVariant, probabilityOfPassingAVariantFormatted, quantityOfVariantsTested, quantityOfLociTested, quantityOfPhasedLoci, conflictExists, nil
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -485,24 +488,23 @@ func GetOffspringMonogenicDiseaseVariantInfoFromGeneticAnalysis(coupleAnalysisOb
|
|||
// -bool: Polygenic Disease Risk Score known (any loci values exist)
|
||||
// -int: Person Disease risk score
|
||||
// -string: Person Disease risk score formatted (has "/10" suffix)
|
||||
// -map[int]locusValue.LocusValue: Person locus values map
|
||||
// -int: Number of loci tested
|
||||
// -int: Quantity of loci tested
|
||||
// -bool: Conflict exists
|
||||
// -error
|
||||
func GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnalysis, diseaseName string, genomeIdentifier [16]byte)(bool, int, string, map[int64]locusValue.LocusValue, int, bool, error){
|
||||
func GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnalysis, diseaseName string, genomeIdentifier [16]byte)(bool, int, string, int, bool, error){
|
||||
|
||||
personPolygenicDiseasesMap := personAnalysisObject.PolygenicDiseasesMap
|
||||
|
||||
personPolygenicDiseaseInfo, exists := personPolygenicDiseasesMap[diseaseName]
|
||||
if (exists == false){
|
||||
return false, 0, "", nil, 0, false, nil
|
||||
return false, 0, "", 0, false, nil
|
||||
}
|
||||
|
||||
personPolygenicDiseaseInfoMap := personPolygenicDiseaseInfo.PolygenicDiseaseInfoMap
|
||||
|
||||
genomePolygenicDiseaseInfo, exists := personPolygenicDiseaseInfoMap[genomeIdentifier]
|
||||
if (exists == false){
|
||||
return false, 0, "", nil, 0, false, nil
|
||||
return false, 0, "", 0, false, nil
|
||||
}
|
||||
|
||||
conflictExists := personPolygenicDiseaseInfo.ConflictExists
|
||||
|
|
@ -513,11 +515,9 @@ func GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject genet
|
|||
|
||||
personDiseaseRiskScoreFormatted := personDiseaseRiskScoreString + "/10"
|
||||
|
||||
personLocusValuesMap := genomePolygenicDiseaseInfo.LocusValuesMap
|
||||
quantityOfLociTested := genomePolygenicDiseaseInfo.QuantityOfLociTested
|
||||
|
||||
numberOfLociTested := genomePolygenicDiseaseInfo.NumberOfLociTested
|
||||
|
||||
return true, personDiseaseRiskScore, personDiseaseRiskScoreFormatted, personLocusValuesMap, numberOfLociTested, conflictExists, nil
|
||||
return true, personDiseaseRiskScore, personDiseaseRiskScoreFormatted, quantityOfLociTested, conflictExists, nil
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -526,7 +526,7 @@ func GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject genet
|
|||
// -int: Offspring average disease risk score
|
||||
// -string: Offspring Disease average risk score formatted (has "/10" suffix)
|
||||
// -[]int: Sample Offspring Risk Scores List
|
||||
// -int: Number of loci tested
|
||||
// -int: Quantity of loci tested
|
||||
// -bool: Conflict exists
|
||||
// -error
|
||||
func GetOffspringPolygenicDiseaseInfoFromGeneticAnalysis(coupleAnalysisObject geneticAnalysis.CoupleAnalysis, diseaseName string, genomePairIdentifier [32]byte)(bool, int, string, []int, int, bool, error){
|
||||
|
|
@ -547,7 +547,7 @@ func GetOffspringPolygenicDiseaseInfoFromGeneticAnalysis(coupleAnalysisObject ge
|
|||
|
||||
conflictExists := couplePolygenicDiseaseInfo.ConflictExists
|
||||
|
||||
numberOfLociTested := genomePairPolygenicDiseaseInfo.NumberOfLociTested
|
||||
quantityOfLociTested := genomePairPolygenicDiseaseInfo.QuantityOfLociTested
|
||||
|
||||
offspringAverageRiskScore := genomePairPolygenicDiseaseInfo.OffspringAverageRiskScore
|
||||
|
||||
|
|
@ -557,7 +557,7 @@ func GetOffspringPolygenicDiseaseInfoFromGeneticAnalysis(coupleAnalysisObject ge
|
|||
|
||||
sampleOffspringRiskScoresList := genomePairPolygenicDiseaseInfo.SampleOffspringRiskScoresList
|
||||
|
||||
return true, offspringAverageRiskScore, offspringAverageRiskScoreFormatted, sampleOffspringRiskScoresList, numberOfLociTested, conflictExists, nil
|
||||
return true, offspringAverageRiskScore, offspringAverageRiskScoreFormatted, sampleOffspringRiskScoresList, quantityOfLociTested, conflictExists, nil
|
||||
}
|
||||
|
||||
//Outputs:
|
||||
|
|
@ -673,71 +673,169 @@ func GetOffspringPolygenicDiseaseLocusInfoFromGeneticAnalysis(coupleAnalysisObje
|
|||
}
|
||||
|
||||
//Outputs:
|
||||
// -map[int64]locusValue.LocusValue (rsID -> Base pair) (missing rsIDs represent unknown values)
|
||||
// -bool: Neural network exists
|
||||
// -bool: Any neural network analysis exists
|
||||
// -string: Neural network predicted outcome
|
||||
// -int: Prediction confidence
|
||||
// -int: Quantity of loci known (Neural network)
|
||||
// -int: Quantity of phased loci (Neural network)
|
||||
// -bool: Any trait rules exist (Rule-based analysis is possible)
|
||||
// -bool: Any Trait Rule known/tested
|
||||
// -map[string]int: Trait outcomes scores map (Outcome -> Number of points)
|
||||
// -int: Number of rules tested
|
||||
// -bool: Conflict exists
|
||||
// -map[[3]byte]bool: Rule Identifier -> Person passes rule
|
||||
// -bool: Predicted outcome exists
|
||||
// -string: Predicted outcome
|
||||
// -int: Quantity of rules tested
|
||||
// -int: Quantity Of Loci Known (Rules)
|
||||
// -bool: Conflict exists (between any of these results for each genome)
|
||||
// -error
|
||||
func GetPersonTraitInfoFromGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnalysis, traitName string, genomeIdentifier [16]byte)(map[int64]locusValue.LocusValue, bool, map[string]int, int, bool, error){
|
||||
func GetPersonDiscreteTraitInfoFromGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnalysis, traitName string, genomeIdentifier [16]byte)(bool, bool, string, int, int, int, bool, bool, map[[3]byte]bool, bool, string, int, int, bool, error){
|
||||
|
||||
personTraitsMap := personAnalysisObject.TraitsMap
|
||||
personTraitsMap := personAnalysisObject.DiscreteTraitsMap
|
||||
|
||||
personTraitInfoObject, exists := personTraitsMap[traitName]
|
||||
if (exists == false){
|
||||
emptyMap := make(map[int64]locusValue.LocusValue)
|
||||
return emptyMap, false, nil, 0, false, nil
|
||||
return false, false, "", 0, 0, 0, false, false, nil, false, "", 0, 0, false, errors.New("Person trait analysis is missing trait: " + traitName)
|
||||
}
|
||||
|
||||
personTraitInfoMap := personTraitInfoObject.TraitInfoMap
|
||||
conflictExists := personTraitInfoObject.ConflictExists
|
||||
|
||||
personGenomeTraitInfoObject, exists := personTraitInfoMap[genomeIdentifier]
|
||||
if (exists == false){
|
||||
emptyMap := make(map[int64]locusValue.LocusValue)
|
||||
return emptyMap, false, nil, 0, false, nil
|
||||
return false, false, "", 0, 0, 0, false, false, nil, false, "", 0, 0, false, errors.New("personTraitInfoMap in Person analysis is missing map for genome identifier.")
|
||||
}
|
||||
|
||||
conflictExists := personTraitInfoObject.ConflictExists
|
||||
neuralNetworkExists := personGenomeTraitInfoObject.NeuralNetworkExists
|
||||
neuralNetworkAnalysisExists := personGenomeTraitInfoObject.NeuralNetworkAnalysisExists
|
||||
|
||||
genomeNumberOfRulesTested := personGenomeTraitInfoObject.NumberOfRulesTested
|
||||
getNeuralNetworkAnalysisInfo := func()(string, int, int, int){
|
||||
|
||||
genomeLocusValuesMap := personGenomeTraitInfoObject.LocusValuesMap
|
||||
if (neuralNetworkExists == false || neuralNetworkAnalysisExists == false){
|
||||
return "", 0, 0, 0
|
||||
}
|
||||
|
||||
genomeOutcomeScoresMap := personGenomeTraitInfoObject.OutcomeScoresMap
|
||||
neuralNetworkAnalysis := personGenomeTraitInfoObject.NeuralNetworkAnalysis
|
||||
|
||||
return genomeLocusValuesMap, true, genomeOutcomeScoresMap, genomeNumberOfRulesTested, conflictExists, nil
|
||||
predictedOutcome := neuralNetworkAnalysis.PredictedOutcome
|
||||
predictionConfidence := neuralNetworkAnalysis.PredictionConfidence
|
||||
quantityOfLociKnown := neuralNetworkAnalysis.QuantityOfLociKnown
|
||||
quantityOfPhasedLoci := neuralNetworkAnalysis.QuantityOfPhasedLoci
|
||||
|
||||
return predictedOutcome, predictionConfidence, quantityOfLociKnown, quantityOfPhasedLoci
|
||||
}
|
||||
|
||||
neuralNetworkPredictedOutcome, neuralNetworkPredictionConfidence, quantityOfLociKnown_NeuralNetwork, quantityOfPhasedLoci_NeuralNetwork :=
|
||||
getNeuralNetworkAnalysisInfo()
|
||||
|
||||
anyRulesExist := personGenomeTraitInfoObject.AnyRulesExist
|
||||
rulesAnalysisExists := personGenomeTraitInfoObject.RulesAnalysisExists
|
||||
|
||||
getTraitAnalysisInfo := func()(map[[3]byte]bool, bool, string, int, int){
|
||||
|
||||
if (anyRulesExist == false || rulesAnalysisExists == false){
|
||||
return nil, false, "", 0, 0
|
||||
}
|
||||
|
||||
rulesAnalysisObject := personGenomeTraitInfoObject.RulesAnalysis
|
||||
|
||||
genomePassesRulesMap := rulesAnalysisObject.GenomePassesRulesMap
|
||||
|
||||
predictedOutcomeExists := rulesAnalysisObject.PredictedOutcomeExists
|
||||
|
||||
predictedOutcome := rulesAnalysisObject.PredictedOutcome
|
||||
|
||||
quantityOfRulesTested := rulesAnalysisObject.QuantityOfRulesTested
|
||||
|
||||
quantityOfLociKnown := rulesAnalysisObject.QuantityOfLociKnown
|
||||
|
||||
return genomePassesRulesMap, predictedOutcomeExists, predictedOutcome, quantityOfRulesTested, quantityOfLociKnown
|
||||
}
|
||||
|
||||
genomePassesRulesMap, rulesPredictedOutcomeExists, rulesPredictedOutcome, quantityOfRulesTested, quantityOfLociKnown_Rules := getTraitAnalysisInfo()
|
||||
|
||||
return neuralNetworkExists, neuralNetworkAnalysisExists, neuralNetworkPredictedOutcome, neuralNetworkPredictionConfidence, quantityOfLociKnown_NeuralNetwork, quantityOfPhasedLoci_NeuralNetwork, anyRulesExist, rulesAnalysisExists, genomePassesRulesMap, rulesPredictedOutcomeExists, rulesPredictedOutcome, quantityOfRulesTested, quantityOfLociKnown_Rules, conflictExists, nil
|
||||
}
|
||||
|
||||
|
||||
|
||||
//Outputs:
|
||||
// -bool: Trait Outcome Scores known
|
||||
// -map[string]float64: Trait average outcome scores map (OutcomeName -> AverageScore)
|
||||
// -int: Number of rules tested
|
||||
// -bool: Conflict exists
|
||||
// -bool: Neural network exists
|
||||
// -bool: Neural network analysis exists
|
||||
// -map[string]int: Offspring outcome probabilities map for neural network prediction
|
||||
// -Map Structure: Outcome name -> Probability of outcome (0-100)
|
||||
// -int: Average confidence (for neural network prediction)
|
||||
// -int: Quantity of loci known (for neural network)
|
||||
// -int: Quantity of Parental phased loci
|
||||
// -bool: Any Rules exist
|
||||
// -bool: Rules analysis exists
|
||||
// -map[string]int: Offspring outcome probabilities map for rules-based prediction
|
||||
// -Map Structure: Outcome name -> Probability of outcome (0-100)
|
||||
// -map[[3]byte]int: Offspring probability of passing rules map
|
||||
// -Map Structure: Rule Identifier -> Probability of passing rule (0-100)
|
||||
// -int: Quantity of rules tested
|
||||
// -int: Quantity of loci known (For Rules)
|
||||
// -bool: Conflict exists (Between this genome pair and other genome pairs)
|
||||
// -error
|
||||
func GetOffspringTraitInfoFromGeneticAnalysis(coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, genomePairIdentifier [32]byte)(bool, map[string]float64, int, bool, error){
|
||||
func GetOffspringDiscreteTraitInfoFromGeneticAnalysis(coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, genomePairIdentifier [32]byte)(bool, bool, map[string]int, int, int, int, bool, bool, map[string]int, map[[3]byte]int, int, int, bool, error){
|
||||
|
||||
offspringTraitsMap := coupleAnalysisObject.TraitsMap
|
||||
offspringTraitsMap := coupleAnalysisObject.DiscreteTraitsMap
|
||||
|
||||
traitInfoObject, exists := offspringTraitsMap[traitName]
|
||||
if (exists == false){
|
||||
return false, nil, 0, false, nil
|
||||
return false, false, nil, 0, 0, 0, false, false, nil, nil, 0, 0, false, errors.New("offspringTraitsMap missing trait when reading couple genetic analysis: " + traitName)
|
||||
}
|
||||
|
||||
traitInfoMap := traitInfoObject.TraitInfoMap
|
||||
conflictExists := traitInfoObject.ConflictExists
|
||||
|
||||
genomePairTraitInfoObject, exists := traitInfoMap[genomePairIdentifier]
|
||||
if (exists == false){
|
||||
return false, nil, 0, false, nil
|
||||
return false, false, nil, 0, 0, 0, false, false, nil, nil, 0, 0, false, errors.New("traitInfoMap missing trait info for genome pair when reading from genetic analysis.")
|
||||
}
|
||||
|
||||
conflictExists := traitInfoObject.ConflictExists
|
||||
neuralNetworkExists := genomePairTraitInfoObject.NeuralNetworkExists
|
||||
|
||||
numberOfRulesTested := genomePairTraitInfoObject.NumberOfRulesTested
|
||||
offspringAverageOutcomeScoresMap := genomePairTraitInfoObject.OffspringAverageOutcomeScoresMap
|
||||
neuralNetworkAnalysisExists := genomePairTraitInfoObject.NeuralNetworkAnalysisExists
|
||||
|
||||
return true, offspringAverageOutcomeScoresMap, numberOfRulesTested, conflictExists, nil
|
||||
getGenomePairTraitNeuralNetworkAnalysisInfo := func()(map[string]int, int, int, int){
|
||||
|
||||
if (neuralNetworkExists == false || neuralNetworkAnalysisExists == false){
|
||||
return nil, 0, 0, 0
|
||||
}
|
||||
|
||||
genomePairTraitNeuralNetworkInfo := genomePairTraitInfoObject.NeuralNetworkAnalysis
|
||||
|
||||
offspringOutcomeProbabilitiesMap := genomePairTraitNeuralNetworkInfo.OffspringOutcomeProbabilitiesMap
|
||||
averageConfidence := genomePairTraitNeuralNetworkInfo.AverageConfidence
|
||||
quantityOfLociKnown := genomePairTraitNeuralNetworkInfo.QuantityOfLociKnown
|
||||
quantityOfParentalPhasedLoci := genomePairTraitNeuralNetworkInfo.QuantityOfParentalPhasedLoci
|
||||
|
||||
return offspringOutcomeProbabilitiesMap, averageConfidence, quantityOfLociKnown, quantityOfParentalPhasedLoci
|
||||
}
|
||||
|
||||
offspringOutcomeProbabilitiesMap_NeuralNetwork, averageConfidence_NeuralNetwork, quantityOfLociKnown_NeuralNetwork, quantityOfParentalPhasedLoci_NeuralNetwork := getGenomePairTraitNeuralNetworkAnalysisInfo()
|
||||
|
||||
anyRulesExist := genomePairTraitInfoObject.RulesExist
|
||||
|
||||
rulesAnalysisExists := genomePairTraitInfoObject.RulesAnalysisExists
|
||||
|
||||
getGenomePairTraitRulesAnalysisInfo := func()(map[string]int, map[[3]byte]int, int, int){
|
||||
|
||||
if (anyRulesExist == false || rulesAnalysisExists == false){
|
||||
return nil, nil, 0, 0
|
||||
}
|
||||
|
||||
genomePairTraitInfo_Rules := genomePairTraitInfoObject.RulesAnalysis
|
||||
|
||||
offspringOutcomeProbabilitiesMap := genomePairTraitInfo_Rules.OffspringOutcomeProbabilitiesMap
|
||||
probabilityOfPassingRulesMap := genomePairTraitInfo_Rules.ProbabilityOfPassingRulesMap
|
||||
quantityOfRulesTested := genomePairTraitInfo_Rules.QuantityOfRulesTested
|
||||
quantityOfLociKnown := genomePairTraitInfo_Rules.QuantityOfLociKnown
|
||||
|
||||
return offspringOutcomeProbabilitiesMap, probabilityOfPassingRulesMap, quantityOfRulesTested, quantityOfLociKnown
|
||||
}
|
||||
|
||||
offspringOutcomeProbabilitiesMap_Rules, probabilityOfPassingRulesMap, quantityOfRulesTested, quantityOfLociKnown_Rules := getGenomePairTraitRulesAnalysisInfo()
|
||||
|
||||
return neuralNetworkExists, neuralNetworkAnalysisExists, offspringOutcomeProbabilitiesMap_NeuralNetwork, averageConfidence_NeuralNetwork, quantityOfLociKnown_NeuralNetwork, quantityOfParentalPhasedLoci_NeuralNetwork, anyRulesExist, rulesAnalysisExists, offspringOutcomeProbabilitiesMap_Rules, probabilityOfPassingRulesMap, quantityOfRulesTested, quantityOfLociKnown_Rules, conflictExists, nil
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -745,24 +843,17 @@ func GetOffspringTraitInfoFromGeneticAnalysis(coupleAnalysisObject geneticAnalys
|
|||
// -bool: Rule status is known (we know if the rule is passed or not)
|
||||
// -bool: Genome passes rule
|
||||
// -error
|
||||
func GetPersonTraitRuleInfoFromGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnalysis, traitName string, ruleIdentifier [3]byte, genomeIdentifier [16]byte)(bool, bool, error){
|
||||
func GetPersonDiscreteTraitRuleInfoFromGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnalysis, traitName string, ruleIdentifier [3]byte, genomeIdentifier [16]byte)(bool, bool, error){
|
||||
|
||||
personTraitsMap := personAnalysisObject.TraitsMap
|
||||
|
||||
traitInfoObject, exists := personTraitsMap[traitName]
|
||||
if (exists == false){
|
||||
_, _, _, _, _, _, anyRulesExist, rulesAnalysisExists, genomePassesRulesMap, _, _, _, _, _, err := GetPersonDiscreteTraitInfoFromGeneticAnalysis(personAnalysisObject, traitName, genomeIdentifier)
|
||||
if (err != nil) { return false, false, err }
|
||||
if (anyRulesExist == false){
|
||||
return false, false, errors.New("GetPersonTraitRuleInfoFromGeneticAnalysis called when no trait rules exist.")
|
||||
}
|
||||
if (rulesAnalysisExists == false){
|
||||
return false, false, nil
|
||||
}
|
||||
|
||||
personTraitInfoMap := traitInfoObject.TraitInfoMap
|
||||
|
||||
genomeTraitInfoObject, exists := personTraitInfoMap[genomeIdentifier]
|
||||
if (exists == false){
|
||||
return false, false, nil
|
||||
}
|
||||
|
||||
genomePassesRulesMap := genomeTraitInfoObject.GenomePassesRulesMap
|
||||
|
||||
genomePassesRule, statusIsKnown := genomePassesRulesMap[ruleIdentifier]
|
||||
if (statusIsKnown == false){
|
||||
return false, false, nil
|
||||
|
|
@ -777,24 +868,17 @@ func GetPersonTraitRuleInfoFromGeneticAnalysis(personAnalysisObject geneticAnaly
|
|||
// -int: Offspring probability of passing rule (0 - 100)
|
||||
// -string: Offspring probability of passing rule formatted (with % suffix)
|
||||
// -error
|
||||
func GetOffspringTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, ruleIdentifier [3]byte, genomePairIdentifier [32]byte)(bool, int, string, error){
|
||||
func GetOffspringDiscreteTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject geneticAnalysis.CoupleAnalysis, traitName string, ruleIdentifier [3]byte, genomePairIdentifier [32]byte)(bool, int, string, error){
|
||||
|
||||
offspringTraitsMap := coupleAnalysisObject.TraitsMap
|
||||
|
||||
offspringTraitInfo, exists := offspringTraitsMap[traitName]
|
||||
if (exists == false){
|
||||
_, _, _, _, _, _, anyRulesExist, rulesAnalysisExists, _, offspringProbabilityOfPassingRulesMap, _, _, _, err := GetOffspringDiscreteTraitInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, genomePairIdentifier)
|
||||
if (err != nil) { return false, 0, "", err }
|
||||
if (anyRulesExist == false){
|
||||
return false, 0, "", errors.New("GetOffspringTraitRuleInfoFromGeneticAnalysis called for trait which has no rules: " + traitName)
|
||||
}
|
||||
if (rulesAnalysisExists == false){
|
||||
return false, 0, "", nil
|
||||
}
|
||||
|
||||
offspringTraitInfoMap := offspringTraitInfo.TraitInfoMap
|
||||
|
||||
offspringTraitInfoObject, exists := offspringTraitInfoMap[genomePairIdentifier]
|
||||
if (exists == false){
|
||||
return false, 0, "", nil
|
||||
}
|
||||
|
||||
offspringProbabilityOfPassingRulesMap := offspringTraitInfoObject.ProbabilityOfPassingRulesMap
|
||||
|
||||
offspringProbabilityOfPassingRule, exists := offspringProbabilityOfPassingRulesMap[ruleIdentifier]
|
||||
if (exists == false){
|
||||
return false, 0, "", nil
|
||||
|
|
@ -812,7 +896,7 @@ func GetOffspringTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject geneticAn
|
|||
//TODO: Perform sanity checks on data
|
||||
func VerifyPersonGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnalysis)error{
|
||||
|
||||
allRawGenomeIdentifiersList, personHasMultipleGenomes, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := GetMetadataFromPersonGeneticAnalysis(personAnalysisObject)
|
||||
allRawGenomeIdentifiersList, personHasMultipleGenomes, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, _, err := GetMetadataFromPersonGeneticAnalysis(personAnalysisObject)
|
||||
if (err != nil) { return err }
|
||||
|
||||
allGenomeIdentifiersList := allRawGenomeIdentifiersList
|
||||
|
|
@ -859,7 +943,7 @@ func VerifyPersonGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnal
|
|||
|
||||
for _, genomeIdentifier := range allGenomeIdentifiersList{
|
||||
|
||||
_, _, _, _, _, _, err := GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject, diseaseName, genomeIdentifier)
|
||||
_, _, _, _, _, err := GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(personAnalysisObject, diseaseName, genomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
}
|
||||
|
||||
|
|
@ -886,27 +970,31 @@ func VerifyPersonGeneticAnalysis(personAnalysisObject geneticAnalysis.PersonAnal
|
|||
for _, traitObject := range traitObjectsList{
|
||||
|
||||
traitName := traitObject.TraitName
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
|
||||
for _, genomeIdentifier := range allGenomeIdentifiersList{
|
||||
|
||||
_, _, _, _, _, err := GetPersonTraitInfoFromGeneticAnalysis(personAnalysisObject, traitName, genomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
}
|
||||
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
for _, traitRuleObject := range traitRulesList{
|
||||
|
||||
ruleIdentifierHex := traitRuleObject.RuleIdentifier
|
||||
|
||||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil) { return err }
|
||||
if (traitIsDiscreteOrNumeric == "Discrete"){
|
||||
|
||||
for _, genomeIdentifier := range allGenomeIdentifiersList{
|
||||
|
||||
_, _, err := GetPersonTraitRuleInfoFromGeneticAnalysis(personAnalysisObject, traitName, ruleIdentifier, genomeIdentifier)
|
||||
_, _, _, _, _, _, _, _, _, _, _, _, _, _, err := GetPersonDiscreteTraitInfoFromGeneticAnalysis(personAnalysisObject, traitName, genomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
}
|
||||
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
for _, traitRuleObject := range traitRulesList{
|
||||
|
||||
ruleIdentifierHex := traitRuleObject.RuleIdentifier
|
||||
|
||||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil) { return err }
|
||||
|
||||
for _, genomeIdentifier := range allGenomeIdentifiersList{
|
||||
|
||||
_, _, err := GetPersonDiscreteTraitRuleInfoFromGeneticAnalysis(personAnalysisObject, traitName, ruleIdentifier, genomeIdentifier)
|
||||
if (err != nil) { return err }
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -998,27 +1086,31 @@ func VerifyCoupleGeneticAnalysis(coupleAnalysisObject geneticAnalysis.CoupleAnal
|
|||
for _, traitObject := range traitObjectsList{
|
||||
|
||||
traitName := traitObject.TraitName
|
||||
traitIsDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
|
||||
for _, genomePairIdentifier := range allGenomePairIdentifiersList{
|
||||
|
||||
_, _, _, _, err := GetOffspringTraitInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, genomePairIdentifier)
|
||||
if (err != nil) { return err }
|
||||
}
|
||||
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
for _, traitRuleObject := range traitRulesList{
|
||||
|
||||
ruleIdentifierHex := traitRuleObject.RuleIdentifier
|
||||
|
||||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil) { return err }
|
||||
if (traitIsDiscreteOrNumeric == "Discrete"){
|
||||
|
||||
for _, genomePairIdentifier := range allGenomePairIdentifiersList{
|
||||
|
||||
_, _, _, err := GetOffspringTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, ruleIdentifier, genomePairIdentifier)
|
||||
_, _, _, _, _, _, _, _, _, _, _, _, _, err := GetOffspringDiscreteTraitInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, genomePairIdentifier)
|
||||
if (err != nil) { return err }
|
||||
}
|
||||
|
||||
traitRulesList := traitObject.RulesList
|
||||
|
||||
for _, traitRuleObject := range traitRulesList{
|
||||
|
||||
ruleIdentifierHex := traitRuleObject.RuleIdentifier
|
||||
|
||||
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
||||
if (err != nil) { return err }
|
||||
|
||||
for _, genomePairIdentifier := range allGenomePairIdentifiersList{
|
||||
|
||||
_, _, _, err := GetOffspringDiscreteTraitRuleInfoFromGeneticAnalysis(coupleAnalysisObject, traitName, ruleIdentifier, genomePairIdentifier)
|
||||
if (err != nil) { return err }
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -128,41 +128,44 @@ func ReadRawGenomeFile(fileReader io.Reader) (string, int, int64, int64, bool, m
|
|||
}
|
||||
|
||||
getMonthObject := func()(time.Month, error){
|
||||
if (monthString == "01"){
|
||||
return time.January, nil
|
||||
}
|
||||
if (monthString == "02"){
|
||||
return time.February, nil
|
||||
}
|
||||
if (monthString == "03"){
|
||||
return time.March, nil
|
||||
}
|
||||
if (monthString == "04"){
|
||||
return time.April, nil
|
||||
}
|
||||
if (monthString == "05"){
|
||||
return time.May, nil
|
||||
}
|
||||
if (monthString == "06"){
|
||||
return time.June, nil
|
||||
}
|
||||
if (monthString == "07"){
|
||||
return time.July, nil
|
||||
}
|
||||
if (monthString == "08"){
|
||||
return time.August, nil
|
||||
}
|
||||
if (monthString == "09"){
|
||||
return time.September, nil
|
||||
}
|
||||
if (monthString == "10"){
|
||||
return time.October, nil
|
||||
}
|
||||
if (monthString == "11"){
|
||||
return time.November, nil
|
||||
}
|
||||
if (monthString == "12"){
|
||||
return time.December, nil
|
||||
|
||||
switch monthString{
|
||||
case "01":{
|
||||
return time.January, nil
|
||||
}
|
||||
case "02":{
|
||||
return time.February, nil
|
||||
}
|
||||
case "03":{
|
||||
return time.March, nil
|
||||
}
|
||||
case "04":{
|
||||
return time.April, nil
|
||||
}
|
||||
case "05":{
|
||||
return time.May, nil
|
||||
}
|
||||
case "06":{
|
||||
return time.June, nil
|
||||
}
|
||||
case "07":{
|
||||
return time.July, nil
|
||||
}
|
||||
case "08":{
|
||||
return time.August, nil
|
||||
}
|
||||
case "09":{
|
||||
return time.September, nil
|
||||
}
|
||||
case "10":{
|
||||
return time.October, nil
|
||||
}
|
||||
case "11":{
|
||||
return time.November, nil
|
||||
}
|
||||
case "12":{
|
||||
return time.December, nil
|
||||
}
|
||||
}
|
||||
return time.January, errors.New("Malformed AncestryDNA genome file: Invalid month: " + monthString)
|
||||
}
|
||||
|
|
@ -438,15 +441,22 @@ func ReadRawGenomeFile(fileReader io.Reader) (string, int, int64, int64, bool, m
|
|||
snpIdentifier := rowSlice[0]
|
||||
snpValueRaw := rowSlice[3]
|
||||
|
||||
if (snpValueRaw[0] != byte('-')){
|
||||
// Locus value is not "--"
|
||||
// Locus value exists
|
||||
numberOfLoci += 1
|
||||
if (len(snpValueRaw) < 2){
|
||||
return "", 0, 0, 0, false, nil, errors.New("Malformed 23andMe genome data: Invalid SNP row snp value: " + fileLineString)
|
||||
}
|
||||
|
||||
if (snpValueRaw[0] == '-'){
|
||||
// Locus value is "--"
|
||||
// Locus value does not exist
|
||||
continue
|
||||
}
|
||||
|
||||
numberOfLoci += 1
|
||||
|
||||
//Outputs:
|
||||
// -bool: rsID found
|
||||
// -int64: rsID value
|
||||
// -error
|
||||
getRSIDIdentifier := func()(bool, int64, error){
|
||||
|
||||
isRSID, rsidInt64 := readRSIDString(snpIdentifier)
|
||||
|
|
@ -481,75 +491,50 @@ func ReadRawGenomeFile(fileReader io.Reader) (string, int, int64, int64, bool, m
|
|||
continue
|
||||
}
|
||||
|
||||
// This will return either a base pair or a single base
|
||||
// Base pair can be "--"
|
||||
getLocusValueString := func()(string, error){
|
||||
getLocusBasesList := func()([]rune, error){
|
||||
|
||||
// This value has a control character suffix
|
||||
// Final index is always a control character
|
||||
// We remove the control character suffix
|
||||
locusBasesList := make([]rune, 0)
|
||||
|
||||
if (len(snpValueRaw) == 2){
|
||||
finalIndex := len(snpValueRaw) - 1
|
||||
|
||||
singleBase := string(snpValueRaw[0])
|
||||
return singleBase, nil
|
||||
}
|
||||
for index, character := range snpValueRaw{
|
||||
|
||||
if (len(snpValueRaw) == 3){
|
||||
baseIsValid := verifyBase(string(character))
|
||||
if (baseIsValid == false){
|
||||
|
||||
basePair := snpValueRaw[:2]
|
||||
return basePair, nil
|
||||
}
|
||||
if (index == finalIndex){
|
||||
// The final index of snpValueRaw is sometimes a control character
|
||||
|
||||
return "", errors.New("Malformed 23andMe genome file: Invalid SNP value: " + snpValueRaw)
|
||||
}
|
||||
return locusBasesList, nil
|
||||
}
|
||||
|
||||
basesString, err := getLocusValueString()
|
||||
if (err != nil) { return "", 0, 0, 0, false, nil, err }
|
||||
|
||||
if (basesString == "--"){
|
||||
// No data exists, skip.
|
||||
continue
|
||||
}
|
||||
|
||||
for _, baseRune := range basesString{
|
||||
|
||||
baseIsValid := verifyBase(string(baseRune))
|
||||
if (baseIsValid == false){
|
||||
return "", 0, 0, 0, false, nil, errors.New("Malformed 23andMe genome file: Invalid SNP base: " + string(baseRune))
|
||||
}
|
||||
}
|
||||
|
||||
getMapEntryValue := func()RawGenomeLocusValue{
|
||||
|
||||
if (len(basesString) == 1){
|
||||
|
||||
locusValueObject := RawGenomeLocusValue{
|
||||
|
||||
Allele1: basesString,
|
||||
Allele2Exists: false,
|
||||
Allele2: "",
|
||||
return nil, errors.New("Malformed 23andMe genome file: Invalid SNP base: " + string(character))
|
||||
}
|
||||
|
||||
return locusValueObject
|
||||
locusBasesList = append(locusBasesList, character)
|
||||
}
|
||||
|
||||
baseAString := string(basesString[0])
|
||||
baseBString := string(basesString[1])
|
||||
|
||||
locusValueObject := RawGenomeLocusValue{
|
||||
|
||||
Allele1: baseAString,
|
||||
Allele2Exists: true,
|
||||
Allele2: baseBString,
|
||||
}
|
||||
|
||||
return locusValueObject
|
||||
return locusBasesList, nil
|
||||
}
|
||||
|
||||
mapEntryValue := getMapEntryValue()
|
||||
locusBasesList, err := getLocusBasesList()
|
||||
if (err != nil){ return "", 0, 0, 0, false, nil, err }
|
||||
|
||||
genomeMap[locusRSID] = mapEntryValue
|
||||
allele1 := string(locusBasesList[0])
|
||||
|
||||
locusValueObject := RawGenomeLocusValue{
|
||||
Allele1: allele1,
|
||||
}
|
||||
|
||||
if (len(locusBasesList) > 1){
|
||||
|
||||
allele2 := string(locusBasesList[1])
|
||||
|
||||
locusValueObject.Allele2Exists = true
|
||||
locusValueObject.Allele2 = allele2
|
||||
}
|
||||
|
||||
genomeMap[locusRSID] = locusValueObject
|
||||
}
|
||||
|
||||
return "23andMe", 1, fileTimeUnix, numberOfLoci, false, genomeMap, nil
|
||||
|
|
|
|||
Binary file not shown.
Binary file not shown.
Binary file not shown.
|
|
@ -769,6 +769,14 @@ func GetAnyProfileAttributeIncludingCalculated(attributeName string, getProfileA
|
|||
return false, profileVersion, "", nil
|
||||
}
|
||||
|
||||
_, _, _, _, myGenomesMap, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(myGeneticAnalysisObject)
|
||||
if (err != nil) { return false, 0, "", err }
|
||||
|
||||
myGenomeLocusValuesMap, exists := myGenomesMap[myGenomeIdentifier]
|
||||
if (exists == false){
|
||||
return false, 0, "", errors.New("GetMyChosenMateGeneticAnalysis returning genetic analysis which has GenomesMap which is missing my genome identifier.")
|
||||
}
|
||||
|
||||
polygenicDiseaseObjectsList, err := polygenicDiseases.GetPolygenicDiseaseObjectsList()
|
||||
if (err != nil) { return false, 0, "", err }
|
||||
|
||||
|
|
@ -780,12 +788,8 @@ func GetAnyProfileAttributeIncludingCalculated(attributeName string, getProfileA
|
|||
|
||||
for _, diseaseObject := range polygenicDiseaseObjectsList{
|
||||
|
||||
diseaseName := diseaseObject.DiseaseName
|
||||
diseaseLociList := diseaseObject.LociList
|
||||
|
||||
_, _, _, myDiseaseLocusValuesMap, _, _, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(myGeneticAnalysisObject, diseaseName, myGenomeIdentifier)
|
||||
if (err != nil) { return false, 0, "", err }
|
||||
|
||||
// Map Structure: rsID -> Locus Value
|
||||
userDiseaseLocusValuesMap := make(map[int64]locusValue.LocusValue)
|
||||
|
||||
|
|
@ -818,7 +822,7 @@ func GetAnyProfileAttributeIncludingCalculated(attributeName string, getProfileA
|
|||
userDiseaseLocusValuesMap[locusRSID] = newLocusValue
|
||||
}
|
||||
|
||||
anyLocusValuesTested, offspringAverageRiskScore, _, err := createCoupleGeneticAnalysis.GetOffspringPolygenicDiseaseInfo_Fast(diseaseLociList, myDiseaseLocusValuesMap, userDiseaseLocusValuesMap)
|
||||
anyLocusValuesTested, offspringAverageRiskScore, _, err := createCoupleGeneticAnalysis.GetOffspringPolygenicDiseaseInfo_Fast(diseaseLociList, myGenomeLocusValuesMap, userDiseaseLocusValuesMap)
|
||||
if (err != nil) { return false, 0, "", err }
|
||||
if (anyLocusValuesTested == false){
|
||||
continue
|
||||
|
|
@ -1399,9 +1403,14 @@ func GetAnyProfileAttributeIncludingCalculated(attributeName string, getProfileA
|
|||
|
||||
traitName := getTraitName()
|
||||
|
||||
myTraitLociMap, _, _, _, _, err := readGeneticAnalysis.GetPersonTraitInfoFromGeneticAnalysis(myGeneticAnalysisObject, traitName, myGenomeIdentifier)
|
||||
_, _, _, _, myGenomesMap, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(myGeneticAnalysisObject)
|
||||
if (err != nil) { return false, 0, "", err }
|
||||
|
||||
myGenomeLocusValuesMap, exists := myGenomesMap[myGenomeIdentifier]
|
||||
if (exists == false){
|
||||
return false, 0, "", errors.New("GetMyChosenMateGeneticAnalysis returning genetic analysis with a GenomesMap which is missing my genome identifier.")
|
||||
}
|
||||
|
||||
traitObject, err := traits.GetTraitObject(traitName)
|
||||
if (err != nil) { return false, 0, "", err }
|
||||
|
||||
|
|
@ -1415,7 +1424,7 @@ func GetAnyProfileAttributeIncludingCalculated(attributeName string, getProfileA
|
|||
|
||||
for _, rsID := range traitLociList{
|
||||
|
||||
myLocusValue, myLocusValueExists := myTraitLociMap[rsID]
|
||||
myLocusValue, myLocusValueExists := myGenomeLocusValuesMap[rsID]
|
||||
if (myLocusValueExists == false){
|
||||
continue
|
||||
}
|
||||
|
|
|
|||
|
|
@ -150,6 +150,14 @@ func UpdateMyExportedProfile(myProfileType string, networkType byte)error{
|
|||
return errors.New("UpdateMyExportedProfile called when profile genetic analysis is not ready.")
|
||||
}
|
||||
|
||||
_, _, _, _, myGenomesMap, err := readGeneticAnalysis.GetMetadataFromPersonGeneticAnalysis(myGeneticAnalysisObject)
|
||||
if (err != nil) { return err }
|
||||
|
||||
myGenomeLocusValuesMap, exists := myGenomesMap[genomeIdentifierToShare]
|
||||
if (exists == false){
|
||||
return errors.New("GetMyChosenMateGeneticAnalysis returning genetic analysis which has GenomesMap which is missing my genome identifier.")
|
||||
}
|
||||
|
||||
monogenicDiseaseNamesList, err := monogenicDiseases.GetMonogenicDiseaseNamesList()
|
||||
if (err != nil) { return err }
|
||||
|
||||
|
|
@ -205,19 +213,24 @@ func UpdateMyExportedProfile(myProfileType string, networkType byte)error{
|
|||
continue
|
||||
}
|
||||
|
||||
_, _, _, myDiseaseLocusValuesMap, _, _, err := readGeneticAnalysis.GetPersonPolygenicDiseaseInfoFromGeneticAnalysis(myGeneticAnalysisObject, diseaseName, genomeIdentifierToShare)
|
||||
if (err != nil) { return err }
|
||||
lociList := diseaseObject.LociList
|
||||
|
||||
for rsID, locusValueObject := range myDiseaseLocusValuesMap{
|
||||
for _, locusObject := range lociList{
|
||||
|
||||
rsIDString := helpers.ConvertInt64ToString(rsID)
|
||||
locusRSID := locusObject.LocusRSID
|
||||
|
||||
locusBase1 := locusValueObject.Base1Value
|
||||
locusBase2 := locusValueObject.Base2Value
|
||||
locusValueObject, exists := myGenomeLocusValuesMap[locusRSID]
|
||||
if (exists == true){
|
||||
|
||||
basePairValue := locusBase1 + ";" + locusBase2
|
||||
rsIDString := helpers.ConvertInt64ToString(locusRSID)
|
||||
|
||||
profileMap["LocusValue_rs" + rsIDString] = basePairValue
|
||||
locusBase1 := locusValueObject.Base1Value
|
||||
locusBase2 := locusValueObject.Base2Value
|
||||
|
||||
basePairValue := locusBase1 + ";" + locusBase2
|
||||
|
||||
profileMap["LocusValue_rs" + rsIDString] = basePairValue
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
|
@ -239,19 +252,22 @@ func UpdateMyExportedProfile(myProfileType string, networkType byte)error{
|
|||
continue
|
||||
}
|
||||
|
||||
myTraitLocusValuesMap, _, _, _, _, err := readGeneticAnalysis.GetPersonTraitInfoFromGeneticAnalysis(myGeneticAnalysisObject, traitName, genomeIdentifierToShare)
|
||||
if (err != nil) { return err }
|
||||
lociList := traitObject.LociList
|
||||
|
||||
for rsID, locusValueObject := range myTraitLocusValuesMap{
|
||||
for _, rsID := range lociList{
|
||||
|
||||
rsIDString := helpers.ConvertInt64ToString(rsID)
|
||||
locusValueObject, exists := myGenomeLocusValuesMap[rsID]
|
||||
if (exists == true){
|
||||
|
||||
locusBase1 := locusValueObject.Base1Value
|
||||
locusBase2 := locusValueObject.Base2Value
|
||||
rsIDString := helpers.ConvertInt64ToString(rsID)
|
||||
|
||||
basePairValue := locusBase1 + ";" + locusBase2
|
||||
locusBase1 := locusValueObject.Base1Value
|
||||
locusBase2 := locusValueObject.Base2Value
|
||||
|
||||
profileMap["LocusValue_rs" + rsIDString] = basePairValue
|
||||
basePairValue := locusBase1 + ";" + locusBase2
|
||||
|
||||
profileMap["LocusValue_rs" + rsIDString] = basePairValue
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
58
resources/geneticPredictionModels/geneticPredictionModels.go
Normal file
58
resources/geneticPredictionModels/geneticPredictionModels.go
Normal file
|
|
@ -0,0 +1,58 @@
|
|||
// geneticPredictionModels contains genetic prediction neural network models for predicting genetic traits
|
||||
// These are .gob encoded files of []float32 weights
|
||||
// This package also contains prediction accuracy information for each model
|
||||
// Prediction accuracy models describe information about how accurate the predictions made by the models are
|
||||
// All of the files in this package are created by the Create Genetic Models utility.
|
||||
// This utility is located in /utilities/createGeneticModels/createGeneticModels.go
|
||||
|
||||
package geneticPredictionModels
|
||||
|
||||
import _ "embed"
|
||||
|
||||
import "errors"
|
||||
|
||||
//Outputs:
|
||||
// -bool: Model exists
|
||||
// -[]byte
|
||||
func GetGeneticPredictionModelBytes(traitName string)(bool, []byte){
|
||||
|
||||
switch traitName{
|
||||
|
||||
case "Eye Color":{
|
||||
return true, predictionModel_EyeColor
|
||||
}
|
||||
case "Lactose Tolerance":{
|
||||
return true, predictionModel_LactoseTolerance
|
||||
}
|
||||
}
|
||||
|
||||
return false, nil
|
||||
}
|
||||
|
||||
//go:embed predictionModels/EyeColorModel.gob
|
||||
var predictionModel_EyeColor []byte
|
||||
|
||||
//go:embed predictionModels/LactoseToleranceModel.gob
|
||||
var predictionModel_LactoseTolerance []byte
|
||||
|
||||
// The files returned by this function are .gob encoded geneticPrediction.TraitPredictionAccuracyInfoMap objects
|
||||
func GetPredictionModelTraitAccuracyInfoBytes(traitName string)([]byte, error){
|
||||
|
||||
switch traitName{
|
||||
case "Eye Color":{
|
||||
return predictionAccuracy_EyeColor, nil
|
||||
}
|
||||
case "Lactose Tolerance":{
|
||||
return predictionAccuracy_LactoseTolerance, nil
|
||||
}
|
||||
}
|
||||
|
||||
return nil, errors.New("GetPredictionModelTraitAccuracyInfoFile called with unknown traitName: " + traitName)
|
||||
}
|
||||
|
||||
//go:embed predictionModelAccuracies/EyeColorModelAccuracy.gob
|
||||
var predictionAccuracy_EyeColor []byte
|
||||
|
||||
//go:embed predictionModelAccuracies/LactoseToleranceModelAccuracy.gob
|
||||
var predictionAccuracy_LactoseTolerance []byte
|
||||
|
||||
|
|
@ -0,0 +1,48 @@
|
|||
package geneticPredictionModels_test
|
||||
|
||||
import "seekia/resources/geneticPredictionModels"
|
||||
|
||||
import "testing"
|
||||
|
||||
import "seekia/internal/genetics/geneticPrediction"
|
||||
|
||||
|
||||
func TestGeneticPredictionModels(t *testing.T){
|
||||
|
||||
traitNamesList := []string{"Eye Color", "Lactose Tolerance"}
|
||||
|
||||
for _, traitName := range traitNamesList{
|
||||
|
||||
modelFound, modelBytes := geneticPredictionModels.GetGeneticPredictionModelBytes(traitName)
|
||||
if (modelFound == false){
|
||||
t.Fatalf("GetGeneticPredictionModelBytes failed to find model for trait: " + traitName)
|
||||
}
|
||||
|
||||
_, err := geneticPrediction.DecodeBytesToNeuralNetworkObject(modelBytes)
|
||||
if (err != nil){
|
||||
t.Fatalf("DecodeBytesToNeuralNetworkObject failed: " + err.Error())
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
func TestGeneticPredictionModelAccuracies(t *testing.T){
|
||||
|
||||
traitNamesList := []string{"Eye Color", "Lactose Tolerance"}
|
||||
|
||||
for _, traitName := range traitNamesList{
|
||||
|
||||
accuracyInfoBytes, err := geneticPredictionModels.GetPredictionModelTraitAccuracyInfoBytes(traitName)
|
||||
if (err != nil){
|
||||
t.Fatalf("GetGeneticPredictionModelBytes failed: " + err.Error())
|
||||
}
|
||||
|
||||
_, err = geneticPrediction.DecodeBytesToTraitPredictionAccuracyInfoMap(accuracyInfoBytes)
|
||||
if (err != nil){
|
||||
t.Fatalf("DecodeBytesToTraitPredictionAccuracyInfoMap failed: " + err.Error())
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
|
|
@ -309,10 +309,13 @@ func TestGeneticReferences(t *testing.T){
|
|||
|
||||
traitName := traitObject.TraitName
|
||||
traitDescription := traitObject.TraitDescription
|
||||
traitDiscreteOrNumeric := traitObject.DiscreteOrNumeric
|
||||
traitLocusReferencesMap := traitObject.LocusReferencesMap
|
||||
traitLociList := traitObject.LociList
|
||||
traitLociList_Rules := traitObject.LociList_Rules
|
||||
traitRulesList := traitObject.RulesList
|
||||
traitOutcomesList := traitObject.OutcomesList
|
||||
traitReferencesMap := traitObject.References
|
||||
traitReferencesMap := traitObject.ReferencesMap
|
||||
|
||||
if (traitName == ""){
|
||||
t.Fatalf("Empty trait name exists.")
|
||||
|
|
@ -326,6 +329,9 @@ func TestGeneticReferences(t *testing.T){
|
|||
if (traitDescription == ""){
|
||||
t.Fatalf("Empty trait description exists for trait: " + traitName)
|
||||
}
|
||||
if (traitDiscreteOrNumeric != "Discrete" && traitDiscreteOrNumeric != "Numeric"){
|
||||
t.Fatalf("Invalid DiscreteOrNumeric for trait: " + traitDiscreteOrNumeric)
|
||||
}
|
||||
if (len(traitOutcomesList) != 0){
|
||||
|
||||
if (len(traitOutcomesList) < 2){
|
||||
|
|
@ -349,18 +355,41 @@ func TestGeneticReferences(t *testing.T){
|
|||
t.Fatalf("Invalid references exist for trait: " + traitName)
|
||||
}
|
||||
|
||||
if (len(traitLocusReferencesMap) == 0){
|
||||
t.Fatalf("No trait locus references exist for trait: " + traitName)
|
||||
}
|
||||
|
||||
for locusRSID, locusReferences := range traitLocusReferencesMap{
|
||||
|
||||
allRSIDsMap[locusRSID] = struct{}{}
|
||||
|
||||
if (locusReferences == nil){
|
||||
t.Fatalf("A trait locus has no references map: " + traitName)
|
||||
}
|
||||
if (len(locusReferences) == 0){
|
||||
t.Fatalf("A trait locus has no references: " + traitName)
|
||||
}
|
||||
|
||||
locusExists := slices.Contains(traitLociList, locusRSID)
|
||||
if (locusExists == false){
|
||||
t.Fatalf("traitLocusReferencesMap contains rsID which does not exist in traitLociList")
|
||||
}
|
||||
}
|
||||
|
||||
if (len(traitLociList) == 0){
|
||||
t.Fatalf("No trait loci exist for trait: " + traitName)
|
||||
}
|
||||
|
||||
for _, locusRSID := range traitLociList{
|
||||
allRSIDsMap[locusRSID] = struct{}{}
|
||||
for _, rsID := range traitLociList{
|
||||
allRSIDsMap[rsID] = struct{}{}
|
||||
}
|
||||
|
||||
containsDuplicates, duplicateLocus := helpers.CheckIfListContainsDuplicates(traitLociList)
|
||||
if (containsDuplicates == true){
|
||||
duplicateLocusString := helpers.ConvertInt64ToString(duplicateLocus)
|
||||
t.Fatalf("traitLociList contains duplicates for trait: " + traitName + ". RSID: " + duplicateLocusString)
|
||||
for _, rsID := range traitLociList_Rules{
|
||||
|
||||
locusExists := slices.Contains(traitLociList, rsID)
|
||||
if (locusExists == false){
|
||||
t.Fatalf("traitLociList_Rules contains locus not present in traitLociList")
|
||||
}
|
||||
}
|
||||
|
||||
if (len(traitRulesList) == 0){
|
||||
|
|
@ -373,7 +402,7 @@ func TestGeneticReferences(t *testing.T){
|
|||
ruleIdentifier := ruleObject.RuleIdentifier
|
||||
ruleLociList := ruleObject.LociList
|
||||
ruleOutcomePointsMap := ruleObject.OutcomePointsMap
|
||||
ruleReferences := ruleObject.References
|
||||
ruleReferencesMap := ruleObject.ReferencesMap
|
||||
|
||||
identifierIsValid := verifyIdentifier(ruleIdentifier)
|
||||
if (identifierIsValid == false){
|
||||
|
|
@ -413,11 +442,21 @@ func TestGeneticReferences(t *testing.T){
|
|||
t.Fatalf("Trait rule Locus identifier is invalid: " + locusIdentifier)
|
||||
}
|
||||
|
||||
listContainsItem := slices.Contains(traitLociList, locusRSID)
|
||||
if (listContainsItem == false){
|
||||
_, mapContainsItem := traitLocusReferencesMap[locusRSID]
|
||||
if (mapContainsItem == false){
|
||||
t.Fatalf("Rule locus contains rsid which is not contained within LocusReferencesMap.")
|
||||
}
|
||||
|
||||
sliceContainsItem := slices.Contains(traitLociList, locusRSID)
|
||||
if (sliceContainsItem == false){
|
||||
t.Fatalf("Rule locus contains rsid which is not contained within traitLociList.")
|
||||
}
|
||||
|
||||
sliceContainsItem = slices.Contains(traitLociList_Rules, locusRSID)
|
||||
if (sliceContainsItem == false){
|
||||
t.Fatalf("Rule locus contains rsid which is not contained within traitLociList_Rules.")
|
||||
}
|
||||
|
||||
if (len(locusBasePairsList) == 0){
|
||||
t.Fatalf("Trait rule locus base pairs list is empty: " + locusIdentifier)
|
||||
}
|
||||
|
|
@ -430,7 +469,7 @@ func TestGeneticReferences(t *testing.T){
|
|||
}
|
||||
}
|
||||
|
||||
referencesAreValid := verifyReferencesMap(ruleReferences)
|
||||
referencesAreValid := verifyReferencesMap(ruleReferencesMap)
|
||||
if (referencesAreValid == false){
|
||||
t.Fatalf("Invalid references map for trait rule locus: " + ruleIdentifier)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -8,9 +8,8 @@ package polygenicDiseases
|
|||
// Polygenic disease probabilities are less accurate, because individual base pair changes only cause comparatively small changes in the disease risk.
|
||||
// Polygenic diseases are also more influenced by environmental factors, further decreasing risk accuracy.
|
||||
|
||||
//TODO: Eventually we want to use neural networks for both polygenic disease and trait prediction.
|
||||
// This package is currently a temporary, less accurate solution until we get access to the necessary training data.
|
||||
// It may still be worth keeping this method in place for polygenic diseases and using neural networks in tandem.
|
||||
//TODO: Eventually we want to use neural networks for polygenic disease prediction.
|
||||
// This package is currently a less accurate solution until we get access to the necessary training data.
|
||||
|
||||
import "errors"
|
||||
|
||||
|
|
|
|||
|
|
@ -1,14 +1,20 @@
|
|||
package traits
|
||||
|
||||
import "seekia/internal/helpers"
|
||||
|
||||
import "maps"
|
||||
|
||||
func getEyeColorTraitObject()Trait{
|
||||
|
||||
eyeColorLociList := []int64{
|
||||
// Map Structure: rsID -> References Map
|
||||
locusReferencesMap := make(map[int64]map[string]string)
|
||||
|
||||
//TODO: Add more SNPs.
|
||||
referencesMap_List1 := make(map[string]string)
|
||||
referencesMap_List1["SNPedia.com - Eye Color"] = "https://www.snpedia.com/index.php/Eye_color"
|
||||
|
||||
// These SNPs are taken from https://www.snpedia.com/index.php/Eye_color
|
||||
// These SNPs are taken from https://www.snpedia.com/index.php/Eye_color
|
||||
|
||||
lociList_1 := []int64{
|
||||
2733832,
|
||||
1800401,
|
||||
1800407,
|
||||
|
|
@ -51,16 +57,39 @@ func getEyeColorTraitObject()Trait{
|
|||
989869,
|
||||
4778138,
|
||||
12906280,
|
||||
}
|
||||
|
||||
// These SNPs are taken from https://pubmed.ncbi.nlm.nih.gov/20546537/
|
||||
for _, rsID := range lociList_1{
|
||||
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List1)
|
||||
}
|
||||
|
||||
referencesMap_List2 := make(map[string]string)
|
||||
referencesMap_List2["Genome-wide association studies of pigmentation and skin cancer: a review and meta-analysis"] = "https://pubmed.ncbi.nlm.nih.gov/20546537/"
|
||||
|
||||
// These SNPs are taken from https://pubmed.ncbi.nlm.nih.gov/20546537/
|
||||
|
||||
lociList_2 := []int64{
|
||||
12203592,
|
||||
1408799,
|
||||
1126809,
|
||||
12896399,
|
||||
7495174,
|
||||
1667394,
|
||||
}
|
||||
|
||||
// These SNPs are taken from https://pubmed.ncbi.nlm.nih.gov/33692100/
|
||||
for _, rsID := range lociList_2{
|
||||
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List2)
|
||||
}
|
||||
|
||||
|
||||
referencesMap_List3 := make(map[string]string)
|
||||
referencesMap_List3["Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color."] = "https://pubmed.ncbi.nlm.nih.gov/33692100/"
|
||||
|
||||
// These SNPs are taken from https://pubmed.ncbi.nlm.nih.gov/33692100/
|
||||
|
||||
lociList_3 := []int64{
|
||||
6693258,
|
||||
351385,
|
||||
2385028,
|
||||
|
|
@ -115,6 +144,12 @@ func getEyeColorTraitObject()Trait{
|
|||
// 5957354,
|
||||
}
|
||||
|
||||
for _, rsID := range lociList_3{
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List3)
|
||||
}
|
||||
|
||||
eyeColorLociList := helpers.GetListOfMapKeys(locusReferencesMap)
|
||||
|
||||
referencesMap := make(map[string]string)
|
||||
referencesMap["SNPedia.com - Eye Color"] = "https://www.snpedia.com/index.php/Eye_color"
|
||||
referencesMap["Genome-wide association studies of pigmentation and skin cancer: a review and meta-analysis"] = "https://pubmed.ncbi.nlm.nih.gov/20546537/"
|
||||
|
|
@ -123,10 +158,13 @@ func getEyeColorTraitObject()Trait{
|
|||
eyeColorObject := Trait{
|
||||
TraitName: "Eye Color",
|
||||
TraitDescription: "The color of a person's eyes.",
|
||||
DiscreteOrNumeric: "Discrete",
|
||||
LocusReferencesMap: locusReferencesMap,
|
||||
LociList: eyeColorLociList,
|
||||
LociList_Rules: []int64{},
|
||||
RulesList: []TraitRule{},
|
||||
OutcomesList: []string{"Blue", "Green", "Hazel", "Brown"},
|
||||
References: referencesMap,
|
||||
ReferencesMap: referencesMap,
|
||||
}
|
||||
|
||||
return eyeColorObject
|
||||
|
|
|
|||
|
|
@ -1,9 +1,19 @@
|
|||
package traits
|
||||
|
||||
import "seekia/internal/helpers"
|
||||
|
||||
import "maps"
|
||||
|
||||
func getFacialStructureTraitObject()Trait{
|
||||
|
||||
facialStructureLociList := []int64{
|
||||
// Map Structure: rsID -> References Map
|
||||
locusReferencesMap := make(map[int64]map[string]string)
|
||||
|
||||
referencesMap_List1 := make(map[string]string)
|
||||
referencesMap_List1["SNPedia.com - Appearance"] = "https://www.snpedia.com/index.php/Appearance"
|
||||
referencesMap_List1["A Genome-Wide Association Study Identifies Five Loci Influencing Facial Morphology in Europeans"] = "https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002932"
|
||||
|
||||
lociList_1 := []int64{
|
||||
|
||||
//TODO: Add more SNPs.
|
||||
|
||||
|
|
@ -112,6 +122,13 @@ func getFacialStructureTraitObject()Trait{
|
|||
397723,
|
||||
}
|
||||
|
||||
for _, rsID := range lociList_1{
|
||||
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List1)
|
||||
}
|
||||
|
||||
facialStructureLociList := helpers.GetListOfMapKeys(locusReferencesMap)
|
||||
|
||||
referencesMap := make(map[string]string)
|
||||
referencesMap["SNPedia.com - Appearance"] = "https://www.snpedia.com/index.php/Appearance"
|
||||
referencesMap["A Genome-Wide Association Study Identifies Five Loci Influencing Facial Morphology in Europeans"] = "https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002932"
|
||||
|
|
@ -119,10 +136,13 @@ func getFacialStructureTraitObject()Trait{
|
|||
facialStructureObject := Trait{
|
||||
TraitName: "Facial Structure",
|
||||
TraitDescription: "The structure of a person's face.",
|
||||
DiscreteOrNumeric: "Discrete",
|
||||
LocusReferencesMap: locusReferencesMap,
|
||||
LociList: facialStructureLociList,
|
||||
LociList_Rules: []int64{},
|
||||
RulesList: []TraitRule{},
|
||||
OutcomesList: []string{},
|
||||
References: referencesMap,
|
||||
ReferencesMap: referencesMap,
|
||||
}
|
||||
|
||||
return facialStructureObject
|
||||
|
|
|
|||
|
|
@ -3,10 +3,20 @@ package traits
|
|||
// Hair color is influenced by thousands of genes
|
||||
// We only have a few listed here
|
||||
|
||||
import "seekia/internal/helpers"
|
||||
|
||||
import "maps"
|
||||
|
||||
func getHairColorTraitObject()Trait{
|
||||
|
||||
hairColorLociList := []int64{
|
||||
// Map Structure: rsID -> References Map
|
||||
locusReferencesMap := make(map[int64]map[string]string)
|
||||
|
||||
referencesMap_List1 := make(map[string]string)
|
||||
referencesMap_List1["SNPedia.com - Appearance"] = "https://www.snpedia.com/index.php/Appearance"
|
||||
referencesMap_List1["Genome-wide association studies of pigmentation and skin cancer: a review and meta-analysis"] = "https://pubmed.ncbi.nlm.nih.gov/20546537/"
|
||||
|
||||
lociList_1 := []int64{
|
||||
|
||||
//These loci were taken from https://pubmed.ncbi.nlm.nih.gov/20546537/
|
||||
|
||||
|
|
@ -32,6 +42,13 @@ func getHairColorTraitObject()Trait{
|
|||
1805008,
|
||||
}
|
||||
|
||||
for _, rsID := range lociList_1{
|
||||
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List1)
|
||||
}
|
||||
|
||||
hairColorLociList := helpers.GetListOfMapKeys(locusReferencesMap)
|
||||
|
||||
referencesMap := make(map[string]string)
|
||||
referencesMap["SNPedia.com - Appearance"] = "https://www.snpedia.com/index.php/Appearance"
|
||||
referencesMap["Genome-wide association studies of pigmentation and skin cancer: a review and meta-analysis"] = "https://pubmed.ncbi.nlm.nih.gov/20546537/"
|
||||
|
|
@ -39,10 +56,13 @@ func getHairColorTraitObject()Trait{
|
|||
hairColorObject := Trait{
|
||||
TraitName: "Hair Color",
|
||||
TraitDescription: "The color of a person's hair.",
|
||||
DiscreteOrNumeric: "Discrete",
|
||||
LocusReferencesMap: locusReferencesMap,
|
||||
LociList: hairColorLociList,
|
||||
LociList_Rules: []int64{},
|
||||
RulesList: []TraitRule{},
|
||||
OutcomesList: []string{},
|
||||
References: referencesMap,
|
||||
ReferencesMap: referencesMap,
|
||||
}
|
||||
|
||||
return hairColorObject
|
||||
|
|
|
|||
|
|
@ -1,11 +1,53 @@
|
|||
package traits
|
||||
|
||||
import "seekia/internal/helpers"
|
||||
|
||||
import "maps"
|
||||
|
||||
func getHairTextureTraitObject()Trait{
|
||||
|
||||
rule1_ReferencesMap := make(map[string]string)
|
||||
rule1_ReferencesMap["SNPedia.com - rs7349332"] = "https://www.snpedia.com/index.php/Rs7349332"
|
||||
// Map Structure: rsID -> References Map
|
||||
locusReferencesMap := make(map[int64]map[string]string)
|
||||
|
||||
referencesMap_List1 := make(map[string]string)
|
||||
referencesMap_List1["SNPedia.com - rs7349332"] = "https://www.snpedia.com/index.php/Rs7349332"
|
||||
|
||||
lociList_1 := []int64{
|
||||
7349332,
|
||||
}
|
||||
|
||||
for _, rsID := range lociList_1{
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List1)
|
||||
}
|
||||
|
||||
|
||||
referencesMap_List2 := make(map[string]string)
|
||||
referencesMap_List2["SNPedia.com - rs11803731"] = "https://www.snpedia.com/index.php/Rs11803731"
|
||||
|
||||
lociList_2 := []int64{
|
||||
11803731,
|
||||
}
|
||||
|
||||
for _, rsID := range lociList_2{
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List2)
|
||||
}
|
||||
|
||||
|
||||
referencesMap_List3 := make(map[string]string)
|
||||
referencesMap_List3["SNPedia.com - rs17646946"] = "https://www.snpedia.com/index.php/Rs17646946"
|
||||
|
||||
lociList_3 := []int64{
|
||||
17646946,
|
||||
}
|
||||
|
||||
for _, rsID := range lociList_3{
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List3)
|
||||
}
|
||||
|
||||
|
||||
|
||||
referencesMap_rs7349332 := make(map[string]string)
|
||||
referencesMap_rs7349332["SNPedia.com - rs7349332"] = "https://www.snpedia.com/index.php/Rs7349332"
|
||||
|
||||
rule1_Locus1Object := RuleLocus{
|
||||
|
||||
|
|
@ -22,12 +64,10 @@ func getHairTextureTraitObject()Trait{
|
|||
RuleIdentifier: "fde405",
|
||||
LociList: rule1_LociList,
|
||||
OutcomePointsMap: rule1_OutcomePointsMap,
|
||||
References: rule1_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs7349332),
|
||||
}
|
||||
|
||||
//TODO: Make sure this is true, that a heterozygote has a higher likelihood of curly hair
|
||||
rule2_ReferencesMap := make(map[string]string)
|
||||
rule2_ReferencesMap["SNPedia.com - rs7349332"] = "https://www.snpedia.com/index.php/Rs7349332"
|
||||
|
||||
rule2_Locus1Object := RuleLocus{
|
||||
|
||||
|
|
@ -44,12 +84,9 @@ func getHairTextureTraitObject()Trait{
|
|||
RuleIdentifier: "6bd1da",
|
||||
LociList: rule2_LociList,
|
||||
OutcomePointsMap: rule2_OutcomePointsMap,
|
||||
References: rule2_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs7349332),
|
||||
}
|
||||
|
||||
rule3_ReferencesMap := make(map[string]string)
|
||||
rule3_ReferencesMap["SNPedia.com - rs7349332"] = "https://www.snpedia.com/index.php/Rs7349332"
|
||||
|
||||
rule3_Locus1Object := RuleLocus{
|
||||
|
||||
LocusIdentifier: "c6760e",
|
||||
|
|
@ -65,11 +102,13 @@ func getHairTextureTraitObject()Trait{
|
|||
RuleIdentifier: "32e377",
|
||||
LociList: rule3_LociList,
|
||||
OutcomePointsMap: rule3_OutcomePointsMap,
|
||||
References: rule3_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs7349332),
|
||||
}
|
||||
|
||||
rule4_ReferencesMap := make(map[string]string)
|
||||
rule4_ReferencesMap["SNPedia.com - rs11803731"] = "https://www.snpedia.com/index.php/Rs11803731"
|
||||
|
||||
|
||||
referencesMap_rs11803731 := make(map[string]string)
|
||||
referencesMap_rs11803731["SNPedia.com - rs11803731"] = "https://www.snpedia.com/index.php/Rs11803731"
|
||||
|
||||
rule4_Locus1Object := RuleLocus{
|
||||
|
||||
|
|
@ -86,12 +125,10 @@ func getHairTextureTraitObject()Trait{
|
|||
RuleIdentifier: "34e6d2",
|
||||
LociList: rule4_LociList,
|
||||
OutcomePointsMap: rule4_OutcomePointsMap,
|
||||
References: rule4_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs11803731),
|
||||
}
|
||||
|
||||
//TODO: Make sure this is true, that a heterozygote has a higher likelihood of curly hair
|
||||
rule5_ReferencesMap := make(map[string]string)
|
||||
rule5_ReferencesMap["SNPedia.com - rs11803731"] = "https://www.snpedia.com/index.php/Rs11803731"
|
||||
|
||||
rule5_Locus1Object := RuleLocus{
|
||||
|
||||
|
|
@ -108,12 +145,9 @@ func getHairTextureTraitObject()Trait{
|
|||
RuleIdentifier: "cf6cb5",
|
||||
LociList: rule5_LociList,
|
||||
OutcomePointsMap: rule5_OutcomePointsMap,
|
||||
References: rule5_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs11803731),
|
||||
}
|
||||
|
||||
rule6_ReferencesMap := make(map[string]string)
|
||||
rule6_ReferencesMap["SNPedia.com - rs11803731"] = "https://www.snpedia.com/index.php/Rs11803731"
|
||||
|
||||
rule6_Locus1Object := RuleLocus{
|
||||
|
||||
LocusIdentifier: "f554b5",
|
||||
|
|
@ -129,11 +163,11 @@ func getHairTextureTraitObject()Trait{
|
|||
RuleIdentifier: "2ba65b",
|
||||
LociList: rule6_LociList,
|
||||
OutcomePointsMap: rule6_OutcomePointsMap,
|
||||
References: rule6_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs11803731),
|
||||
}
|
||||
|
||||
rule7_ReferencesMap := make(map[string]string)
|
||||
rule7_ReferencesMap["SNPedia.com - rs17646946"] = "https://www.snpedia.com/index.php/Rs17646946"
|
||||
referencesMap_rs17646946 := make(map[string]string)
|
||||
referencesMap_rs17646946["SNPedia.com - rs17646946"] = "https://www.snpedia.com/index.php/Rs17646946"
|
||||
|
||||
rule7_Locus1Object := RuleLocus{
|
||||
|
||||
|
|
@ -150,12 +184,9 @@ func getHairTextureTraitObject()Trait{
|
|||
RuleIdentifier: "ae3274",
|
||||
LociList: rule7_LociList,
|
||||
OutcomePointsMap: rule7_OutcomePointsMap,
|
||||
References: rule7_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs17646946),
|
||||
}
|
||||
|
||||
rule8_ReferencesMap := make(map[string]string)
|
||||
rule8_ReferencesMap["SNPedia.com - rs17646946"] = "https://www.snpedia.com/index.php/Rs17646946"
|
||||
|
||||
rule8_Locus1Object := RuleLocus{
|
||||
|
||||
LocusIdentifier: "f1144a",
|
||||
|
|
@ -171,12 +202,9 @@ func getHairTextureTraitObject()Trait{
|
|||
RuleIdentifier: "a546bf",
|
||||
LociList: rule8_LociList,
|
||||
OutcomePointsMap: rule8_OutcomePointsMap,
|
||||
References: rule8_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs17646946),
|
||||
}
|
||||
|
||||
rule9_ReferencesMap := make(map[string]string)
|
||||
rule9_ReferencesMap["SNPedia.com - rs17646946"] = "https://www.snpedia.com/index.php/Rs17646946"
|
||||
|
||||
rule9_Locus1Object := RuleLocus{
|
||||
|
||||
LocusIdentifier: "468bb3",
|
||||
|
|
@ -192,26 +220,32 @@ func getHairTextureTraitObject()Trait{
|
|||
RuleIdentifier: "b8dc0a",
|
||||
LociList: rule9_LociList,
|
||||
OutcomePointsMap: rule9_OutcomePointsMap,
|
||||
References: rule9_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs17646946),
|
||||
}
|
||||
|
||||
hairTextureRulesList := []TraitRule{rule1_Object, rule2_Object, rule3_Object, rule4_Object, rule5_Object, rule6_Object, rule7_Object, rule8_Object, rule9_Object}
|
||||
|
||||
hairTextureLociList := []int64{17646946, 11803731, 7349332}
|
||||
|
||||
lociList_Rules := []int64{7349332, 11803731, 17646946}
|
||||
|
||||
referencesMap := make(map[string]string)
|
||||
referencesMap["SNPedia.com - Hair Curliness"] = "https://www.snpedia.com/index.php/Hair_curliness"
|
||||
|
||||
outcomesList := []string{"Straight", "Curly"}
|
||||
|
||||
hairTextureLociList := helpers.GetListOfMapKeys(locusReferencesMap)
|
||||
|
||||
hairTextureObject := Trait{
|
||||
|
||||
TraitName: "Hair Texture",
|
||||
TraitDescription: "The texture of a person's head hair.",
|
||||
DiscreteOrNumeric: "Discrete",
|
||||
LocusReferencesMap: locusReferencesMap,
|
||||
LociList: hairTextureLociList,
|
||||
LociList_Rules: lociList_Rules,
|
||||
RulesList: hairTextureRulesList,
|
||||
OutcomesList: outcomesList,
|
||||
References: referencesMap,
|
||||
ReferencesMap: referencesMap,
|
||||
}
|
||||
|
||||
return hairTextureObject
|
||||
|
|
|
|||
|
|
@ -1,11 +1,30 @@
|
|||
package traits
|
||||
|
||||
import "seekia/internal/helpers"
|
||||
|
||||
import "maps"
|
||||
|
||||
|
||||
func getLactoseToleranceTraitObject()Trait{
|
||||
|
||||
rule1_ReferencesMap := make(map[string]string)
|
||||
rule1_ReferencesMap["SNPedia.com - rs182549"] = "https://www.snpedia.com/index.php/Rs182549"
|
||||
// Map Structure: rsID -> References Map
|
||||
locusReferencesMap := make(map[int64]map[string]string)
|
||||
|
||||
referencesMap_1 := make(map[string]string)
|
||||
referencesMap_1["SNPedia.com - rs182549"] = "https://www.snpedia.com/index.php/Rs182549"
|
||||
|
||||
locusReferencesMap[182549] = referencesMap_1
|
||||
|
||||
|
||||
referencesMap_2 := make(map[string]string)
|
||||
referencesMap_2["SNPedia.com - rs4988235"] = "https://www.snpedia.com/index.php/Rs4988235"
|
||||
|
||||
locusReferencesMap[4988235] = referencesMap_2
|
||||
|
||||
|
||||
|
||||
referencesMap_rs182549 := make(map[string]string)
|
||||
referencesMap_rs182549["SNPedia.com - rs182549"] = "https://www.snpedia.com/index.php/Rs182549"
|
||||
|
||||
rule1_Locus1Object := RuleLocus{
|
||||
|
||||
|
|
@ -22,12 +41,9 @@ func getLactoseToleranceTraitObject()Trait{
|
|||
RuleIdentifier: "f4e02c",
|
||||
LociList: rule1_LociList,
|
||||
OutcomePointsMap: rule1_OutcomePointsMap,
|
||||
References: rule1_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs182549),
|
||||
}
|
||||
|
||||
rule2_ReferencesMap := make(map[string]string)
|
||||
rule2_ReferencesMap["SNPedia.com - rs182549"] = "https://www.snpedia.com/index.php/Rs182549"
|
||||
|
||||
rule2_Locus1Object := RuleLocus{
|
||||
|
||||
LocusIdentifier: "a7feff",
|
||||
|
|
@ -43,11 +59,11 @@ func getLactoseToleranceTraitObject()Trait{
|
|||
RuleIdentifier: "cc3df0",
|
||||
LociList: rule2_LociList,
|
||||
OutcomePointsMap: rule2_OutcomePointsMap,
|
||||
References: rule2_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs182549),
|
||||
}
|
||||
|
||||
rule3_ReferencesMap := make(map[string]string)
|
||||
rule3_ReferencesMap["SNPedia.com - rs4988235"] = "https://www.snpedia.com/index.php/Rs4988235"
|
||||
referencesMap_rs4988235 := make(map[string]string)
|
||||
referencesMap_rs4988235["SNPedia.com - rs4988235"] = "https://www.snpedia.com/index.php/Rs4988235"
|
||||
|
||||
rule3_Locus1Object := RuleLocus{
|
||||
|
||||
|
|
@ -64,12 +80,9 @@ func getLactoseToleranceTraitObject()Trait{
|
|||
RuleIdentifier: "8170ee",
|
||||
LociList: rule3_LociList,
|
||||
OutcomePointsMap: rule3_OutcomePointsMap,
|
||||
References: rule3_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs4988235),
|
||||
}
|
||||
|
||||
rule4_ReferencesMap := make(map[string]string)
|
||||
rule4_ReferencesMap["SNPedia.com - rs4988235"] = "https://www.snpedia.com/index.php/Rs4988235"
|
||||
|
||||
rule4_Locus1Object := RuleLocus{
|
||||
|
||||
LocusIdentifier: "176dde",
|
||||
|
|
@ -85,12 +98,9 @@ func getLactoseToleranceTraitObject()Trait{
|
|||
RuleIdentifier: "52425f",
|
||||
LociList: rule4_LociList,
|
||||
OutcomePointsMap: rule4_OutcomePointsMap,
|
||||
References: rule4_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs4988235),
|
||||
}
|
||||
|
||||
rule5_ReferencesMap := make(map[string]string)
|
||||
rule5_ReferencesMap["SNPedia.com - rs4988235"] = "https://www.snpedia.com/index.php/Rs4988235"
|
||||
|
||||
rule5_Locus1Object := RuleLocus{
|
||||
|
||||
LocusIdentifier: "164acb",
|
||||
|
|
@ -106,25 +116,31 @@ func getLactoseToleranceTraitObject()Trait{
|
|||
RuleIdentifier: "4b5c35",
|
||||
LociList: rule5_LociList,
|
||||
OutcomePointsMap: rule5_OutcomePointsMap,
|
||||
References: rule5_ReferencesMap,
|
||||
ReferencesMap: maps.Clone(referencesMap_rs4988235),
|
||||
}
|
||||
|
||||
lactoseToleranceRulesList := []TraitRule{rule1_Object, rule2_Object, rule3_Object, rule4_Object, rule5_Object}
|
||||
|
||||
lactoseToleranceLociList := []int64{4988235, 182549}
|
||||
|
||||
referencesMap := make(map[string]string)
|
||||
referencesMap["SNPedia.com - Lactose Intolerance"] = "https://www.snpedia.com/index.php/Lactose_intolerance"
|
||||
|
||||
outcomesList := []string{"Tolerant", "Intolerant"}
|
||||
|
||||
lactoseToleranceLociList := helpers.GetListOfMapKeys(locusReferencesMap)
|
||||
|
||||
lociList_Rules := []int64{182549, 4988235}
|
||||
|
||||
lactoseToleranceObject := Trait{
|
||||
TraitName: "Lactose Tolerance",
|
||||
TraitDescription: "The ability to tolerate lactose.",
|
||||
DiscreteOrNumeric: "Discrete",
|
||||
LocusReferencesMap: locusReferencesMap,
|
||||
LociList: lactoseToleranceLociList,
|
||||
LociList_Rules: lociList_Rules,
|
||||
RulesList: lactoseToleranceRulesList,
|
||||
OutcomesList: outcomesList,
|
||||
References: referencesMap,
|
||||
ReferencesMap: referencesMap,
|
||||
}
|
||||
|
||||
return lactoseToleranceObject
|
||||
|
|
|
|||
|
|
@ -1,10 +1,18 @@
|
|||
package traits
|
||||
|
||||
import "seekia/internal/helpers"
|
||||
|
||||
import "maps"
|
||||
|
||||
func getSkinColorTraitObject()Trait{
|
||||
|
||||
skinColorLociList := []int64{
|
||||
// Map Structure: rsID -> References Map
|
||||
locusReferencesMap := make(map[int64]map[string]string)
|
||||
|
||||
referencesMap_List1 := make(map[string]string)
|
||||
referencesMap_List1["SNPedia.com - Appearance"] = "https://www.snpedia.com/index.php/Appearance"
|
||||
|
||||
lociList_1 := []int64{
|
||||
|
||||
//TODO: Add more SNPs.
|
||||
|
||||
|
|
@ -14,12 +22,32 @@ func getSkinColorTraitObject()Trait{
|
|||
26722,
|
||||
1426654,
|
||||
642742,
|
||||
}
|
||||
|
||||
for _, rsID := range lociList_1{
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List1)
|
||||
}
|
||||
|
||||
referencesMap_List2 := make(map[string]string)
|
||||
referencesMap_List2["Genome-wide association studies of pigmentation and skin cancer: a review and meta-analysis"] = "https://pubmed.ncbi.nlm.nih.gov/20546537/"
|
||||
|
||||
lociList_2 := []int64{
|
||||
|
||||
// These SNPs are from https://pubmed.ncbi.nlm.nih.gov/20546537/
|
||||
16891982,
|
||||
12203592,
|
||||
1042602,
|
||||
1834640,
|
||||
}
|
||||
|
||||
for _, rsID := range lociList_2{
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List2)
|
||||
}
|
||||
|
||||
referencesMap_List3 := make(map[string]string)
|
||||
referencesMap_List3["Meta-analysis and prioritization of human skin pigmentation-associated GWAS-SNPs using ENCODE data-based web-tools"] = "https://link.springer.com/article/10.1007/s00403-019-01891-3"
|
||||
|
||||
lociList_3 := []int64{
|
||||
|
||||
// These SNPs are from https://link.springer.com/article/10.1007/s00403-019-01891-3
|
||||
7182710,
|
||||
|
|
@ -33,18 +61,28 @@ func getSkinColorTraitObject()Trait{
|
|||
3212368,
|
||||
}
|
||||
|
||||
for _, rsID := range lociList_3{
|
||||
locusReferencesMap[rsID] = maps.Clone(referencesMap_List3)
|
||||
}
|
||||
|
||||
|
||||
referencesMap := make(map[string]string)
|
||||
referencesMap["SNPedia.com - Appearance"] = "https://www.snpedia.com/index.php/Appearance"
|
||||
referencesMap["Genome-wide association studies of pigmentation and skin cancer: a review and meta-analysis"] = "https://pubmed.ncbi.nlm.nih.gov/20546537/"
|
||||
referencesMap["Meta-analysis and prioritization of human skin pigmentation-associated GWAS-SNPs using ENCODE data-based web-tools"] = "https://link.springer.com/article/10.1007/s00403-019-01891-3"
|
||||
|
||||
lociList := helpers.GetListOfMapKeys(locusReferencesMap)
|
||||
|
||||
skinColorObject := Trait{
|
||||
TraitName: "Skin Color",
|
||||
TraitDescription: "The color of a person's skin.",
|
||||
LociList: skinColorLociList,
|
||||
DiscreteOrNumeric: "Discrete",
|
||||
LocusReferencesMap: locusReferencesMap,
|
||||
LociList: lociList,
|
||||
LociList_Rules: []int64{},
|
||||
RulesList: []TraitRule{},
|
||||
OutcomesList: []string{},
|
||||
References: referencesMap,
|
||||
ReferencesMap: referencesMap,
|
||||
}
|
||||
|
||||
return skinColorObject
|
||||
|
|
|
|||
|
|
@ -3,30 +3,51 @@
|
|||
|
||||
package traits
|
||||
|
||||
// TODO: We want to eventually use neural nets for both trait and polygenic disease analysis
|
||||
// These will be trained on a set of genomes and will output a probability analysis for each trait
|
||||
// This is only possible once we get access to the necessary training data
|
||||
//
|
||||
// See geneticPrediction.go for a non-working attempt to predict traits with neural nets
|
||||
|
||||
import "errors"
|
||||
|
||||
type RuleLocus struct{
|
||||
type Trait struct{
|
||||
|
||||
// 3 byte hex encoded string
|
||||
LocusIdentifier string
|
||||
// Example: "Eye Color"
|
||||
TraitName string
|
||||
|
||||
// RSID that represents this locus
|
||||
// If multiple RSIDs represent the same locus, use the first rsid for the locus in the locusMetadata package
|
||||
LocusRSID int64
|
||||
TraitDescription string
|
||||
|
||||
// List of base pair values that this RSID must fulfill to pass the rule
|
||||
// As long as the value matches any base pair value in the list, the genome has passed this rule locus
|
||||
// The genome must pass every rule locus within a rule to pass the rule
|
||||
BasePairsList []string
|
||||
// This describes if the trait is discrete or numeric
|
||||
// Discrete traits have a set of outcomes (Example: Eye Color: Blue, Green...)
|
||||
// Numeric traits have a numeric outcome (Example: Height)
|
||||
// The value of this variable is either "Discrete" or "Numeric"
|
||||
DiscreteOrNumeric string
|
||||
|
||||
// This is a list of rsIDs which are known to have an effect on this trait
|
||||
// These loci may not have any associated rules
|
||||
// We use these loci to predict trait outcomes with neural networks.
|
||||
// We also use these loci to calculate Racial Similarity.
|
||||
// Map Structure: rsID -> (map[ReferenceName]Reference Link)
|
||||
LocusReferencesMap map[int64]map[string]string
|
||||
|
||||
// This is a list of all loci used to predict this trait
|
||||
// If a neural network exists, all of these will be used as input into the network for prediction
|
||||
LociList []int64
|
||||
|
||||
// This is a list of all loci used to predict this trait using rules
|
||||
// It is sometimes a subset of LociList
|
||||
LociList_Rules []int64
|
||||
|
||||
// This list can be empty if no rules exist
|
||||
// An empty list means we are relying on LociList and neural networks for trait prediction.
|
||||
RulesList []TraitRule
|
||||
|
||||
// List of outcomes
|
||||
// Example: "Lactose Intolerant", "Lactore Tolerant"
|
||||
// This list can be empty if outcomes are not text descriptions (Example: Facial structure)
|
||||
// If the trait is Numeric, or their or no rules nor a neural network, then this list will be empty.
|
||||
OutcomesList []string
|
||||
|
||||
// This map contains scientific resources about this trait
|
||||
// Map structure: Reference name -> Reference link
|
||||
ReferencesMap map[string]string
|
||||
}
|
||||
|
||||
|
||||
type TraitRule struct{
|
||||
|
||||
// 3 byte identifier encoded hex
|
||||
|
|
@ -44,36 +65,26 @@ type TraitRule struct{
|
|||
OutcomePointsMap map[string]int
|
||||
|
||||
// Map structure: Reference name -> Reference link
|
||||
References map[string]string
|
||||
ReferencesMap map[string]string
|
||||
}
|
||||
|
||||
|
||||
type Trait struct{
|
||||
type RuleLocus struct{
|
||||
|
||||
TraitName string
|
||||
// 3 byte hex encoded string
|
||||
LocusIdentifier string
|
||||
|
||||
TraitDescription string
|
||||
// RSID that represents this locus
|
||||
// If multiple RSIDs represent the same locus, use the first rsid for the locus in the locusMetadata package
|
||||
LocusRSID int64
|
||||
|
||||
// This is a list of rsIDs which are known to have an effect on this trait
|
||||
// These loci may not have any associated rules
|
||||
// We use these loci to calculate Racial Similarity.
|
||||
// We will also use neural networks to predict trait outcome scores using these loci
|
||||
LociList []int64
|
||||
|
||||
// This list can be empty if no rules exist
|
||||
// An empty list means we are relying on LociList and neural networks for trait prediction.
|
||||
RulesList []TraitRule
|
||||
|
||||
// List of outcomes
|
||||
// Example: "Lactose Intolerant", "Lactore Tolerant"
|
||||
// This list can be empty if outcomes are not text descriptions (Example: Facial structure)
|
||||
// If there are no outcomes, then no rules can exist
|
||||
OutcomesList []string
|
||||
|
||||
// Map structure: Reference name -> Reference link
|
||||
References map[string]string
|
||||
// List of base pair values that this RSID must fulfill to pass the rule
|
||||
// As long as the value matches any base pair value in the list, the genome has passed this rule locus
|
||||
// The genome must pass every rule locus within a rule to pass the rule
|
||||
BasePairsList []string
|
||||
}
|
||||
|
||||
|
||||
var traitNamesList []string
|
||||
var traitObjectsList []Trait
|
||||
|
||||
|
|
|
|||
1
utilities/createGeneticModels/.gitignore
vendored
1
utilities/createGeneticModels/.gitignore
vendored
|
|
@ -1,3 +1,4 @@
|
|||
OpenSNPDataArchiveFolderpath.txt
|
||||
TrainingData
|
||||
TrainedModels
|
||||
ModelAccuracies
|
||||
|
|
@ -3,6 +3,7 @@
|
|||
// These are neural networks which predict traits such as eye color from raw genome files
|
||||
// The OpenSNP.org dataset is used, and more datasets will be added in the future.
|
||||
// You must download the dataset and extract it. The instructions are described in the utility.
|
||||
// The trained models are saved in the /resources/geneticPredictionModels package for use in the Seekia app.
|
||||
|
||||
package main
|
||||
|
||||
|
|
@ -1136,10 +1137,16 @@ func setStartAndMonitorTrainModelPage(window fyne.Window, traitName string, prev
|
|||
_, err := localFilesystem.CreateFolder("./TrainedModels")
|
||||
if (err != nil) { return false, err }
|
||||
|
||||
|
||||
trainingSetFilepathsList, _, err := getTrainingAndTestingDataFilepathLists(traitName)
|
||||
if (err != nil) { return false, err }
|
||||
|
||||
// Now we deterministically randomize the order of the trainingSetFilepathsList
|
||||
pseudorandomNumberGenerator := mathRand.New(mathRand.NewPCG(1, 2))
|
||||
|
||||
pseudorandomNumberGenerator.Shuffle(len(trainingSetFilepathsList), func(i int, j int){
|
||||
trainingSetFilepathsList[i], trainingSetFilepathsList[j] = trainingSetFilepathsList[j], trainingSetFilepathsList[i]
|
||||
})
|
||||
|
||||
// We create a new neural network object to train
|
||||
neuralNetworkObject, err := geneticPrediction.GetNewUntrainedNeuralNetworkObject(traitName)
|
||||
if (err != nil) { return false, err }
|
||||
|
|
@ -1277,7 +1284,8 @@ func setTestModelsPage(window fyne.Window, previousPage func()){
|
|||
description2 := getLabelCentered("This will test each neural network using user training data examples.")
|
||||
description3 := getLabelCentered("The testing data is not used to train the models.")
|
||||
description4 := getLabelCentered("The results of the testing will be displayed at the end.")
|
||||
description5 := getLabelCentered("You must select a trait model to test.")
|
||||
description5 := getLabelCentered("The results will also be saved in the ModelAccuracies folder.")
|
||||
description6 := getLabelCentered("You must select a trait model to test.")
|
||||
|
||||
traitNamesList := []string{"Eye Color", "Lactose Tolerance"}
|
||||
|
||||
|
|
@ -1301,50 +1309,12 @@ func setTestModelsPage(window fyne.Window, previousPage func()){
|
|||
|
||||
traitNameSelectorCentered := getWidgetCentered(traitNameSelector)
|
||||
|
||||
page := container.NewVBox(title, backButton, widget.NewSeparator(), description1, description2, description3, description4, description5, widget.NewSeparator(), traitNameSelectorCentered, widget.NewSeparator(), beginTestingButton)
|
||||
page := container.NewVBox(title, backButton, widget.NewSeparator(), description1, description2, description3, description4, description5, description6, widget.NewSeparator(), traitNameSelectorCentered, widget.NewSeparator(), beginTestingButton)
|
||||
|
||||
window.SetContent(page)
|
||||
}
|
||||
|
||||
|
||||
type TraitOutcomeInfo struct{
|
||||
|
||||
// This is the outcome which was found
|
||||
// Example: "Blue"
|
||||
OutcomeName string
|
||||
|
||||
// This is a value between 0-100 which describes the percentage of the loci which were tested for the input for the prediction
|
||||
PercentageOfLociTested int
|
||||
|
||||
// This is a value between 0-100 which describes the percentage of the tested loci which were phased for the input for the prediction
|
||||
PercentageOfPhasedLoci int
|
||||
}
|
||||
|
||||
type TraitPredictionAccuracyInfo struct{
|
||||
|
||||
// This contains the quantity of examples for the outcome with the specified percentageOfLociTested and percentageOfPhasedLoci
|
||||
QuantityOfExamples int
|
||||
|
||||
// This contains the quantity of predictions for the outcome with the specified percentageOfLociTested and percentageOfPhasedLoci
|
||||
// Prediction = our model predicted this outcome
|
||||
QuantityOfPredictions int
|
||||
|
||||
// This stores the probability (0-100) that our model will accurately predict this outcome for a genome which has
|
||||
// the specified percentageOfLociTested and percentageOfPhasedLoci
|
||||
// In other words: What is the probability that if you give Seekia a blue-eyed genome, it will give you a correct Blue prediction?
|
||||
// This value is only accurate is QuantityOfExamples > 0
|
||||
ProbabilityOfCorrectGenomePrediction int
|
||||
|
||||
// This stores the probability (0-100) that our model is correct if our model predicts that a genome
|
||||
// with the specified percentageOfLociTested and percentageOfPhasedLoci has this outcome
|
||||
// In other words: What is the probability that if Seekia says a genome will have blue eyes, it is correct?
|
||||
// This value is only accurate is QuantityOfPredictions > 0
|
||||
ProbabilityOfCorrectOutcomePrediction int
|
||||
}
|
||||
|
||||
// Map Structure: Trait Outcome Info -> Trait Prediction Accuracy Info
|
||||
type TraitAccuracyInfoMap map[TraitOutcomeInfo]TraitPredictionAccuracyInfo
|
||||
|
||||
func setStartAndMonitorTestModelPage(window fyne.Window, traitName string, previousPage func()){
|
||||
|
||||
title := getBoldLabelCentered("Testing Model")
|
||||
|
|
@ -1386,9 +1356,9 @@ func setStartAndMonitorTestModelPage(window fyne.Window, traitName string, previ
|
|||
|
||||
//Outputs:
|
||||
// -bool: Process completed (true == was not stopped mid-way)
|
||||
// -TraitAccuracyInfoMap
|
||||
// -geneticPrediction.TraitPredictionAccuracyInfoMap
|
||||
// -error
|
||||
testModel := func()(bool, TraitAccuracyInfoMap, error){
|
||||
testModel := func()(bool, geneticPrediction.TraitPredictionAccuracyInfoMap, error){
|
||||
|
||||
type TraitAccuracyStatisticsValue struct{
|
||||
|
||||
|
|
@ -1408,7 +1378,7 @@ func setStartAndMonitorTestModelPage(window fyne.Window, traitName string, previ
|
|||
|
||||
// We use this map to count up the information about predictions
|
||||
// We use information from this map to construct the final accuracy information map
|
||||
traitPredictionInfoMap := make(map[TraitOutcomeInfo]TraitAccuracyStatisticsValue)
|
||||
traitPredictionInfoMap := make(map[geneticPrediction.TraitOutcomeInfo]TraitAccuracyStatisticsValue)
|
||||
|
||||
|
||||
_, testingSetFilepathsList, err := getTrainingAndTestingDataFilepathLists(traitName)
|
||||
|
|
@ -1494,7 +1464,7 @@ func setStartAndMonitorTestModelPage(window fyne.Window, traitName string, previ
|
|||
{
|
||||
// We first add the information to the map for the correct outcome
|
||||
|
||||
newTraitOutcomeInfo_CorrectOutcome := TraitOutcomeInfo{
|
||||
newTraitOutcomeInfo_CorrectOutcome := geneticPrediction.TraitOutcomeInfo{
|
||||
|
||||
OutcomeName: correctOutcomeName,
|
||||
PercentageOfLociTested: percentageOfLociTested,
|
||||
|
|
@ -1525,7 +1495,7 @@ func setStartAndMonitorTestModelPage(window fyne.Window, traitName string, previ
|
|||
{
|
||||
// We now add the information to the map for the predicted outcome
|
||||
|
||||
newTraitOutcomeInfo_PredictedOutcome := TraitOutcomeInfo{
|
||||
newTraitOutcomeInfo_PredictedOutcome := geneticPrediction.TraitOutcomeInfo{
|
||||
|
||||
OutcomeName: predictedOutcomeName,
|
||||
PercentageOfLociTested: percentageOfLociTested,
|
||||
|
|
@ -1566,7 +1536,7 @@ func setStartAndMonitorTestModelPage(window fyne.Window, traitName string, previ
|
|||
// Now we construct the TraitAccuracyInfoMap
|
||||
|
||||
// This map stores the accuracy for each outcome
|
||||
traitAccuracyInfoMap := make(map[TraitOutcomeInfo]TraitPredictionAccuracyInfo)
|
||||
traitPredictionAccuracyInfoMap := make(map[geneticPrediction.TraitOutcomeInfo]geneticPrediction.TraitPredictionAccuracyInfo)
|
||||
|
||||
for traitAccuracyData, value := range traitPredictionInfoMap{
|
||||
|
||||
|
|
@ -1583,7 +1553,7 @@ func setStartAndMonitorTestModelPage(window fyne.Window, traitName string, previ
|
|||
return false, nil, errors.New("traitPredictionInfoMap contains quantityOfCorrectOutcomePredictions > quantityOfPredictions")
|
||||
}
|
||||
|
||||
newTraitPredictionAccuracyInfo := TraitPredictionAccuracyInfo{
|
||||
newTraitPredictionAccuracyInfo := geneticPrediction.TraitPredictionAccuracyInfo{
|
||||
QuantityOfExamples: quantityOfExamples,
|
||||
QuantityOfPredictions: quantityOfPredictions,
|
||||
}
|
||||
|
|
@ -1604,17 +1574,30 @@ func setStartAndMonitorTestModelPage(window fyne.Window, traitName string, previ
|
|||
newTraitPredictionAccuracyInfo.ProbabilityOfCorrectOutcomePrediction = percentageOfCorrectOutcomePredictions
|
||||
}
|
||||
|
||||
traitAccuracyInfoMap[traitAccuracyData] = newTraitPredictionAccuracyInfo
|
||||
traitPredictionAccuracyInfoMap[traitAccuracyData] = newTraitPredictionAccuracyInfo
|
||||
}
|
||||
|
||||
// Testing is complete.
|
||||
|
||||
// We save the info map as a file in the ModelAccuracies folder
|
||||
|
||||
fileBytes, err := geneticPrediction.EncodeTraitPredictionAccuracyInfoMapToBytes(traitPredictionAccuracyInfoMap)
|
||||
if (err != nil) { return false, nil, err }
|
||||
|
||||
_, err = localFilesystem.CreateFolder("./ModelAccuracies")
|
||||
if (err != nil) { return false, nil, err }
|
||||
|
||||
modelAccuracyFilename := traitNameWithoutWhitespaces + "ModelAccuracy.gob"
|
||||
|
||||
err = localFilesystem.CreateOrOverwriteFile(fileBytes, "./ModelAccuracies/", modelAccuracyFilename)
|
||||
if (err != nil) { return false, nil, err }
|
||||
|
||||
progressPercentageBinding.Set(1)
|
||||
|
||||
return true, traitAccuracyInfoMap, nil
|
||||
return true, traitPredictionAccuracyInfoMap, nil
|
||||
}
|
||||
|
||||
processIsComplete, traitAccuracyInfoMap, err := testModel()
|
||||
processIsComplete, traitPredictionAccuracyInfoMap, err := testModel()
|
||||
if (err != nil){
|
||||
setErrorEncounteredPage(window, err, previousPage)
|
||||
return
|
||||
|
|
@ -1624,14 +1607,14 @@ func setStartAndMonitorTestModelPage(window fyne.Window, traitName string, previ
|
|||
return
|
||||
}
|
||||
|
||||
setViewModelTestingTraitResultsPage(window, traitName, traitAccuracyInfoMap, previousPage)
|
||||
setViewModelTestingTraitResultsPage(window, traitName, traitPredictionAccuracyInfoMap, previousPage)
|
||||
}
|
||||
|
||||
go testModelFunction()
|
||||
}
|
||||
|
||||
// This is a page to view the details of testing for a specific trait's model
|
||||
func setViewModelTestingTraitResultsPage(window fyne.Window, traitName string, traitAccuracyInfoMap TraitAccuracyInfoMap, exitPage func()){
|
||||
func setViewModelTestingTraitResultsPage(window fyne.Window, traitName string, traitAccuracyInfoMap geneticPrediction.TraitPredictionAccuracyInfoMap, exitPage func()){
|
||||
|
||||
title := getBoldLabelCentered("Trait Prediction Accuracy Details")
|
||||
|
||||
|
|
@ -1661,14 +1644,10 @@ func setViewModelTestingTraitResultsPage(window fyne.Window, traitName string, t
|
|||
predictionAccuracyTitle3 := getItalicLabelCentered("Prediction Accuracy")
|
||||
knownLociLabel_67to100 := getItalicLabelCentered("67-100% Known Loci")
|
||||
|
||||
emptyLabel2 := widget.NewLabel("")
|
||||
emptyLabel3 := widget.NewLabel("")
|
||||
|
||||
outcomeNameColumn := container.NewVBox(outcomeNameTitle, emptyLabel1, widget.NewSeparator())
|
||||
predictionAccuracyColumn_0to33 := container.NewVBox(predictionAccuracyTitle1, knownLociLabel_0to33, widget.NewSeparator())
|
||||
predictionAccuracyColumn_34to66 := container.NewVBox(predictionAccuracyTitle2, knownLociLabel_34to66, widget.NewSeparator())
|
||||
predictionAccuracyColumn_67to100 := container.NewVBox(predictionAccuracyTitle3, knownLociLabel_67to100, widget.NewSeparator())
|
||||
viewTraitAccuracyDetailsColumn := container.NewVBox(emptyLabel2, emptyLabel3, widget.NewSeparator())
|
||||
|
||||
traitObject, err := traits.GetTraitObject(traitName)
|
||||
if (err != nil) { return nil, err }
|
||||
|
|
@ -1777,7 +1756,7 @@ func setViewModelTestingTraitResultsPage(window fyne.Window, traitName string, t
|
|||
predictionAccuracyColumn_67to100.Add(widget.NewSeparator())
|
||||
}
|
||||
|
||||
resultsGrid := container.NewHBox(layout.NewSpacer(), outcomeNameColumn, predictionAccuracyColumn_0to33, predictionAccuracyColumn_34to66, predictionAccuracyColumn_67to100, viewTraitAccuracyDetailsColumn, layout.NewSpacer())
|
||||
resultsGrid := container.NewHBox(layout.NewSpacer(), outcomeNameColumn, predictionAccuracyColumn_0to33, predictionAccuracyColumn_34to66, predictionAccuracyColumn_67to100, layout.NewSpacer())
|
||||
|
||||
return resultsGrid, nil
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in a new issue