2545 lines
94 KiB
Go
2545 lines
94 KiB
Go
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// createGeneticAnalysis provides functions to create a genetic analysis
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// These are performed on one or more genome files.
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// They produce 3 kinds of results: Monogenic Diseases, Polygenic Diseases and Traits
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// They can be performed on a Person or a Couple
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// Couple analyses provide an analysis of the prospective offspring of the couple
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package createGeneticAnalysis
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// Disclaimer: I am a novice in the ways of genetics. This package could be flawed in numerous ways.
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// TODO: We want to eventually use neural nets for both trait and polygenic disease analysis (see geneticPrediction.go)
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// These will be trained on a set of genomes and will output a probability analysis for each trait/disease
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// This is only possible once we get access to the necessary training data
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//
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// This is how offspring trait prediction could work with the neural net model:
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// Both users will share all relevant SNPS base pairs that determine the trait on their profile.
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// Each location has 4 possible outcomes, so for 1000 SNPs, there are 4^1000 possible offspring outcomes for a given couple. (this
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// is actually too high because recombination break points do not occur at each locus, see genetic linkage)
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// This is too many options for us to check all of them.
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// Seekia will create 100 offspring that would be produced from both users, and run each offspring through the neural net.
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// Each offspring would be different. The allele from each parent for each SNP would be randomly chosen.
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// The user can choose how many prospective offspring to create in the settings.
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// More offspring will take longer, but will yield a more accurate trait probability.
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// Seekia will show the the average trait result and a chart showing the trait results for all created offspring.
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// TODO: Add the ability to weight different genome files based on their reliability.
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// Some files are much more accurate because they record each location many times.
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import "seekia/resources/geneticReferences/locusMetadata"
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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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import "seekia/internal/encoding"
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import "seekia/internal/genetics/geneticAnalysis"
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import "seekia/internal/genetics/locusValue"
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import "seekia/internal/genetics/prepareRawGenomes"
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import "seekia/internal/helpers"
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import "errors"
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import mathRand "math/rand/v2"
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import "strings"
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import "slices"
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import "maps"
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func verifyBasePair(inputBasePair string)bool{
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base1, base2, delimiterFound := strings.Cut(inputBasePair, ";")
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if (delimiterFound == false){
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return false
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}
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// I = Insertion
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// D = Deletion
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validBasesList := []string{"C", "A", "T", "G", "I", "D"}
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baseIsValid := slices.Contains(validBasesList, base1)
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if (baseIsValid == false){
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return false
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}
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baseIsValid = slices.Contains(validBasesList, base2)
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if (baseIsValid == false){
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return false
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}
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return true
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}
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//Outputs:
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// -bool: Process completed (it was not stopped manually before completion)
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// -string: New Genetic analysis string (Encoded in MessagePack)
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// -error
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func CreatePersonGeneticAnalysis(genomesList []prepareRawGenomes.RawGenomeWithMetadata, updatePercentageCompleteFunction func(int)error, checkIfProcessIsStopped func()bool)(bool, string, error){
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prepareRawGenomesUpdatePercentageCompleteFunction := func(newPercentage int)error{
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newPercentageCompletion, err := helpers.ScaleNumberProportionally(true, newPercentage, 0, 100, 0, 50)
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if (err != nil){ return err }
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err = updatePercentageCompleteFunction(newPercentageCompletion)
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if (err != nil) { return err }
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return nil
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}
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genomesWithMetadataList, allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := prepareRawGenomes.GetGenomesWithMetadataListFromRawGenomesList(genomesList, prepareRawGenomesUpdatePercentageCompleteFunction)
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if (err != nil) { return false, "", err }
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newGeneticAnalysisObject := geneticAnalysis.PersonAnalysis{
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AnalysisVersion: 1,
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CombinedGenomesExist: multipleGenomesExist,
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AllRawGenomeIdentifiersList: allRawGenomeIdentifiersList,
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}
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if (multipleGenomesExist == true){
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newGeneticAnalysisObject.OnlyExcludeConflictsGenomeIdentifier = onlyExcludeConflictsGenomeIdentifier
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newGeneticAnalysisObject.OnlyIncludeSharedGenomeIdentifier = onlyIncludeSharedGenomeIdentifier
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}
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processIsStopped := checkIfProcessIsStopped()
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if (processIsStopped == true){
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return false, "", nil
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}
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monogenicDiseasesList, err := monogenicDiseases.GetMonogenicDiseaseObjectsList()
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if (err != nil) { return false, "", err }
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// Map Structure: Disease Name -> PersonMonogenicDiseaseInfo
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analysisMonogenicDiseasesMap := make(map[string]geneticAnalysis.PersonMonogenicDiseaseInfo)
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for _, monogenicDiseaseObject := range monogenicDiseasesList{
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diseaseName := monogenicDiseaseObject.DiseaseName
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personDiseaseAnalysisObject, err := getPersonMonogenicDiseaseAnalysis(genomesWithMetadataList, monogenicDiseaseObject)
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if (err != nil) { return false, "", err }
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analysisMonogenicDiseasesMap[diseaseName] = personDiseaseAnalysisObject
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}
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newGeneticAnalysisObject.MonogenicDiseasesMap = analysisMonogenicDiseasesMap
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polygenicDiseaseObjectsList, err := polygenicDiseases.GetPolygenicDiseaseObjectsList()
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if (err != nil) { return false, "", err }
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// Map Structure: Disease Name -> PersonPolygenicDiseaseInfo
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analysisPolygenicDiseasesMap := make(map[string]geneticAnalysis.PersonPolygenicDiseaseInfo)
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for _, diseaseObject := range polygenicDiseaseObjectsList{
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personDiseaseAnalysisObject, err := getPersonPolygenicDiseaseAnalysis(genomesWithMetadataList, diseaseObject)
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if (err != nil) { return false, "", err }
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diseaseName := diseaseObject.DiseaseName
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analysisPolygenicDiseasesMap[diseaseName] = personDiseaseAnalysisObject
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}
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newGeneticAnalysisObject.PolygenicDiseasesMap = analysisPolygenicDiseasesMap
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traitObjectsList, err := traits.GetTraitObjectsList()
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if (err != nil) { return false, "", err }
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// Map Structure: Trait Name -> PersonTraitInfo
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analysisTraitsMap := make(map[string]geneticAnalysis.PersonTraitInfo)
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for _, traitObject := range traitObjectsList{
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personTraitAnalysisObject, err := getPersonTraitAnalysis(genomesWithMetadataList, traitObject)
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if (err != nil) { return false, "", err }
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traitName := traitObject.TraitName
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analysisTraitsMap[traitName] = personTraitAnalysisObject
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}
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newGeneticAnalysisObject.TraitsMap = analysisTraitsMap
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analysisBytes, err := encoding.EncodeMessagePackBytes(newGeneticAnalysisObject)
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if (err != nil) { return false, "", err }
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analysisString := string(analysisBytes)
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return true, analysisString, nil
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}
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//Outputs:
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// -bool: Process completed (was not manually stopped mid-way)
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// -string: Couple genetic analysis string (encoded in MessagePack)
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// -error
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func CreateCoupleGeneticAnalysis(person1GenomesList []prepareRawGenomes.RawGenomeWithMetadata, person2GenomesList []prepareRawGenomes.RawGenomeWithMetadata, updatePercentageCompleteFunction func(int)error, checkIfProcessIsStopped func()bool)(bool, string, error){
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person1PrepareRawGenomesUpdatePercentageCompleteFunction := func(newPercentage int)error{
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newPercentageCompletion, err := helpers.ScaleNumberProportionally(true, newPercentage, 0, 100, 0, 25)
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if (err != nil){ return err }
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err = updatePercentageCompleteFunction(newPercentageCompletion)
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if (err != nil) { return err }
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return nil
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}
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person1GenomesWithMetadataList, allPerson1RawGenomeIdentifiersList, person1HasMultipleGenomes, person1OnlyExcludeConflictsGenomeIdentifier, person1OnlyIncludeSharedGenomeIdentifier, err := prepareRawGenomes.GetGenomesWithMetadataListFromRawGenomesList(person1GenomesList, person1PrepareRawGenomesUpdatePercentageCompleteFunction)
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if (err != nil) { return false, "", err }
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processIsStopped := checkIfProcessIsStopped()
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if (processIsStopped == true){
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return false, "", nil
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}
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person2PrepareRawGenomesUpdatePercentageCompleteFunction := func(newPercentage int)error{
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newPercentageCompletion, err := helpers.ScaleNumberProportionally(true, newPercentage, 0, 100, 25, 50)
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if (err != nil){ return err }
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err = updatePercentageCompleteFunction(newPercentageCompletion)
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if (err != nil) { return err }
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return nil
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}
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person2GenomesWithMetadataList, allPerson2RawGenomeIdentifiersList, person2HasMultipleGenomes, person2OnlyExcludeConflictsGenomeIdentifier, person2OnlyIncludeSharedGenomeIdentifier, err := prepareRawGenomes.GetGenomesWithMetadataListFromRawGenomesList(person2GenomesList, person2PrepareRawGenomesUpdatePercentageCompleteFunction)
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if (err != nil) { return false, "", err }
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processIsStopped = checkIfProcessIsStopped()
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if (processIsStopped == true){
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return false, "", nil
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}
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// The analysis will analyze either 1 or 2 genome pairs
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// The gui will display the results from each pair
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//Outputs:
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// -[16]byte: Pair 1 Person 1 Genome Identifier
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// -[16]byte: Pair 1 Person 2 Genome Identifier
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// -bool: Second pair exists
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// -[16]byte: Pair 2 Person 1 Genome Identifier
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// -[16]byte: Pair 2 Person 2 Genome Identifier
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// -error
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getGenomePairsToAnalyze := func()([16]byte, [16]byte, bool, [16]byte, [16]byte, error){
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if (person1HasMultipleGenomes == true && person2HasMultipleGenomes == true){
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return person1OnlyExcludeConflictsGenomeIdentifier, person2OnlyExcludeConflictsGenomeIdentifier, true, person1OnlyIncludeSharedGenomeIdentifier, person2OnlyIncludeSharedGenomeIdentifier, nil
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}
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if (person1HasMultipleGenomes == true && person2HasMultipleGenomes == false){
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person2GenomeIdentifier := allPerson2RawGenomeIdentifiersList[0]
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return person1OnlyExcludeConflictsGenomeIdentifier, person2GenomeIdentifier, true, person1OnlyIncludeSharedGenomeIdentifier, person2GenomeIdentifier, nil
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}
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if (person1HasMultipleGenomes == false && person2HasMultipleGenomes == true){
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person1GenomeIdentifier := allPerson1RawGenomeIdentifiersList[0]
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return person1GenomeIdentifier, person2OnlyExcludeConflictsGenomeIdentifier, true, person1GenomeIdentifier, person2OnlyIncludeSharedGenomeIdentifier, nil
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}
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//person1HasMultipleGenomes == false && person2HasMultipleGenomes == false
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person1GenomeIdentifier := allPerson1RawGenomeIdentifiersList[0]
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person2GenomeIdentifier := allPerson2RawGenomeIdentifiersList[0]
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return person1GenomeIdentifier, person2GenomeIdentifier, false, [16]byte{}, [16]byte{}, nil
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}
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pair1Person1GenomeIdentifier, pair1Person2GenomeIdentifier, genomePair2Exists, pair2Person1GenomeIdentifier, pair2Person2GenomeIdentifier, err := getGenomePairsToAnalyze()
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if (err != nil){ return false, "", err }
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newCoupleAnalysis := geneticAnalysis.CoupleAnalysis{
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AnalysisVersion: 1,
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Pair1Person1GenomeIdentifier: pair1Person1GenomeIdentifier,
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Pair1Person2GenomeIdentifier: pair1Person2GenomeIdentifier,
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SecondPairExists: genomePair2Exists,
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Person1HasMultipleGenomes: person1HasMultipleGenomes,
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Person2HasMultipleGenomes: person2HasMultipleGenomes,
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}
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if (genomePair2Exists == true){
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// At least 1 of the people have multiple genomes
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newCoupleAnalysis.Pair2Person1GenomeIdentifier = pair2Person1GenomeIdentifier
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newCoupleAnalysis.Pair2Person2GenomeIdentifier = pair2Person2GenomeIdentifier
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if (person1HasMultipleGenomes == true){
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newCoupleAnalysis.Person1OnlyExcludeConflictsGenomeIdentifier = person1OnlyExcludeConflictsGenomeIdentifier
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newCoupleAnalysis.Person1OnlyIncludeSharedGenomeIdentifier = person1OnlyIncludeSharedGenomeIdentifier
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}
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if (person2HasMultipleGenomes == true){
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newCoupleAnalysis.Person2OnlyExcludeConflictsGenomeIdentifier = person2OnlyExcludeConflictsGenomeIdentifier
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newCoupleAnalysis.Person2OnlyIncludeSharedGenomeIdentifier = person2OnlyIncludeSharedGenomeIdentifier
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}
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}
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// We compute and add monogenic disease probabilities
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monogenicDiseasesList, err := monogenicDiseases.GetMonogenicDiseaseObjectsList()
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if (err != nil) { return false, "", err }
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// Map Structure: Disease Name -> OffspringMonogenicDiseaseInfo
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offspringMonogenicDiseasesMap := make(map[string]geneticAnalysis.OffspringMonogenicDiseaseInfo)
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for _, diseaseObject := range monogenicDiseasesList{
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diseaseName := diseaseObject.DiseaseName
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variantsList := diseaseObject.VariantsList
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diseaseIsDominantOrRecessive := diseaseObject.DominantOrRecessive
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person1DiseaseAnalysisObject, err := getPersonMonogenicDiseaseAnalysis(person1GenomesWithMetadataList, diseaseObject)
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if (err != nil) { return false, "", err }
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person2DiseaseAnalysisObject, err := getPersonMonogenicDiseaseAnalysis(person2GenomesWithMetadataList, diseaseObject)
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if (err != nil) { return false, "", err }
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// This map stores the number of variants tested in each person's genome
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// Map Structure: Genome Identifier -> Number of variants tested
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numberOfVariantsTestedMap := make(map[[16]byte]int)
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// This map stores the offspring disease probabilities for each genome pair.
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// A genome pair is a concatenation of two genome identifiers
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// If a map entry doesn't exist, the probabilities are unknown for that genome pair
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// Map Structure: Genome Pair Identifier -> OffspringMonogenicDiseaseProbabilities
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offspringMonogenicDiseaseInfoMap := make(map[[32]byte]geneticAnalysis.OffspringGenomePairMonogenicDiseaseInfo)
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// This will calculate the probability of monogenic disease for the offspring from the two specified genomes
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// It also calculates the probabilities for each monogenic disease variant for the offspring
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// It then adds the genome pair disease information to the offspringMonogenicDiseaseInfoMap and numberOfVariantsTestedMap
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addGenomePairInfoToDiseaseMaps := func(person1GenomeIdentifier [16]byte, person2GenomeIdentifier [16]byte)error{
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//Outputs:
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// -bool: Probability is known
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// -int: Probability of passing a disease variant (value between 0 and 100)
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// -int: Number of variants tested
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getPersonWillPassDiseaseVariantProbability := func(personDiseaseAnalysisObject geneticAnalysis.PersonMonogenicDiseaseInfo, genomeIdentifier [16]byte)(bool, int, int){
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personDiseaseInfoMap := personDiseaseAnalysisObject.MonogenicDiseaseInfoMap
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personGenomeDiseaseInfoObject, exists := personDiseaseInfoMap[genomeIdentifier]
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if (exists == false){
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return false, 0, 0
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}
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personGenomeProbabilityOfPassingADiseaseVariant := personGenomeDiseaseInfoObject.ProbabilityOfPassingADiseaseVariant
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personGenomeNumberOfVariantsTested := personGenomeDiseaseInfoObject.NumberOfVariantsTested
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return true, personGenomeProbabilityOfPassingADiseaseVariant, personGenomeNumberOfVariantsTested
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}
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person1ProbabilityIsKnown, person1WillPassVariantProbability, person1NumberOfVariantsTested := getPersonWillPassDiseaseVariantProbability(person1DiseaseAnalysisObject, person1GenomeIdentifier)
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person2ProbabilityIsKnown, person2WillPassVariantProbability, person2NumberOfVariantsTested := getPersonWillPassDiseaseVariantProbability(person2DiseaseAnalysisObject, person2GenomeIdentifier)
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offspringHasDiseaseProbabilityIsKnown, percentageProbabilityOffspringHasDisease, offspringHasAVariantProbabilityIsKnown, percentageProbabilityOffspringHasVariant, err := GetOffspringMonogenicDiseaseProbabilities(diseaseIsDominantOrRecessive, person1ProbabilityIsKnown, person1WillPassVariantProbability, person2ProbabilityIsKnown, person2WillPassVariantProbability)
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if (err != nil) { return err }
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// Now we calculate the probabilities for individual variants
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offspringVariantsInfoMap := make(map[[3]byte]geneticAnalysis.OffspringMonogenicDiseaseVariantInfo)
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for _, variantObject := range variantsList{
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variantIdentifierHex := variantObject.VariantIdentifier
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variantIdentifier, err := encoding.DecodeHexStringTo3ByteArray(variantIdentifierHex)
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if (err != nil) { return err }
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//Outputs:
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// -bool: Probability is known
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// -float64: Probability that person will pass variant to offspring (between 0 and 1)
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// -error
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getPersonWillPassVariantProbability := func(personDiseaseAnalysisObject geneticAnalysis.PersonMonogenicDiseaseInfo, personGenomeIdentifier [16]byte)(bool, float64, error){
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personDiseaseInfoMap := personDiseaseAnalysisObject.MonogenicDiseaseInfoMap
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personGenomeDiseaseInfoObject, exists := personDiseaseInfoMap[personGenomeIdentifier]
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if (exists == false){
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return false, 0, nil
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}
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personGenomeDiseaseVariantsMap := personGenomeDiseaseInfoObject.VariantsInfoMap
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personVariantInfoObject, exists := personGenomeDiseaseVariantsMap[variantIdentifier]
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if (exists == false){
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// The genome does not have information about this variant
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return false, 0, nil
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}
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base1HasVariant := personVariantInfoObject.Base1HasVariant
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base2HasVariant := personVariantInfoObject.Base2HasVariant
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if (base1HasVariant == true && base2HasVariant == true){
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return true, 1, nil
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}
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if (base1HasVariant == true && base2HasVariant == false){
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return true, 0.5, nil
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}
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if (base1HasVariant == false && base2HasVariant == true){
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return true, 0.5, nil
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}
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// Neither base has a variant
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return true, 0, nil
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}
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person1VariantProbabilityIsKnown, person1WillPassVariantProbability, err := getPersonWillPassVariantProbability(person1DiseaseAnalysisObject, person1GenomeIdentifier)
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if (err != nil) { return err }
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person2VariantProbabilityIsKnown, person2WillPassVariantProbability, err := getPersonWillPassVariantProbability(person2DiseaseAnalysisObject, person2GenomeIdentifier)
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if (err != nil) { return err }
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if (person1VariantProbabilityIsKnown == false && person2VariantProbabilityIsKnown == false){
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continue
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}
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// Outputs:
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// -float64: Best Case Person 1 will pass variant probability (0-1)
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// -float64: Worst Case Person 1 will pass variant probability (0-1)
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// -float64: Best Case Person 2 will pass variant probability (0-1)
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// -float64: Worst Case Person 2 will pass variant probability (0-1)
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getBestAndWorstCaseProbabilities := func()(float64, float64, float64, float64){
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if (person1VariantProbabilityIsKnown == true && person2VariantProbabilityIsKnown == false){
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return person1WillPassVariantProbability, person1WillPassVariantProbability, float64(0), float64(1)
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}
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if (person1VariantProbabilityIsKnown == false && person2VariantProbabilityIsKnown == true){
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return float64(0), float64(1), person2WillPassVariantProbability, person2WillPassVariantProbability
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}
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// Both people's probabilities are known
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return person1WillPassVariantProbability, person1WillPassVariantProbability, person2WillPassVariantProbability, person2WillPassVariantProbability
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}
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bestCasePerson1WillPassVariantProbability, worstCasePerson1WillPassVariantProbability, bestCasePerson2WillPassVariantProbability, worstCasePerson2WillPassVariantProbability := getBestAndWorstCaseProbabilities()
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//Outputs:
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// -int: Percentage Probability of 0 mutations
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// -int: Percentage Probability of 1 mutation
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// -int: Percentage Probability of 2 mutations
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// -error
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getOffspringVariantMutationProbabilities := func(person1WillPassVariantProbability float64, person2WillPassVariantProbability float64)(int, int, int, error){
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// This is the probability that neither person will pass the variant
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// P = P(!A) * P(!B)
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probabilityOf0Mutations := (1 - person1WillPassVariantProbability) * (1 - person2WillPassVariantProbability)
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// This is the probability that either person will pass the variant, but not both
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// P(A XOR B) = P(A) + P(B) - (2 * P(A and B))
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probabilityOf1Mutation := person1WillPassVariantProbability + person2WillPassVariantProbability - (2 * person1WillPassVariantProbability * person2WillPassVariantProbability)
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// This is the probability that both people will pass the variant
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// P(A and B) = P(A) * P(B)
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probabilityOf2Mutations := person1WillPassVariantProbability * person2WillPassVariantProbability
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percentageProbabilityOf0Mutations, err := helpers.FloorFloat64ToInt(probabilityOf0Mutations * 100)
|
|
if (err != nil) { return 0, 0, 0, err }
|
|
percentageProbabilityOf1Mutation, err := helpers.FloorFloat64ToInt(probabilityOf1Mutation * 100)
|
|
if (err != nil) { return 0, 0, 0, err }
|
|
percentageProbabilityOf2Mutations, err := helpers.FloorFloat64ToInt(probabilityOf2Mutations * 100)
|
|
if (err != nil) { return 0, 0, 0, err }
|
|
|
|
return percentageProbabilityOf0Mutations, percentageProbabilityOf1Mutation, percentageProbabilityOf2Mutations, nil
|
|
}
|
|
|
|
bestCase0MutationsProbability, bestCase1MutationProbability, bestCase2MutationsProbability, err := getOffspringVariantMutationProbabilities(bestCasePerson1WillPassVariantProbability, bestCasePerson2WillPassVariantProbability)
|
|
if (err != nil) { return err }
|
|
|
|
worstCase0MutationsProbability, worstCase1MutationProbability, worstCase2MutationsProbability, err := getOffspringVariantMutationProbabilities(worstCasePerson1WillPassVariantProbability, worstCasePerson2WillPassVariantProbability)
|
|
if (err != nil) { return err }
|
|
|
|
// We have to figure out which 1-mutation-probability is lower
|
|
// The best case probabilities can actually result in a higher probability for 1 mutation
|
|
// than the worst case probabilities
|
|
// This is because in a worst-case-scenario, the probability of 1 mutation might be 0 because
|
|
// the probability of 2 mutations is 100
|
|
// This is not needed for the 0 and 2 mutation probabilities because TODO
|
|
|
|
lowerBound1MutationProbability := min(bestCase1MutationProbability, worstCase1MutationProbability)
|
|
upperBound1MutationProbability := max(bestCase1MutationProbability, worstCase1MutationProbability)
|
|
|
|
newOffspringMonogenicDiseaseVariantInfoObject := geneticAnalysis.OffspringMonogenicDiseaseVariantInfo{
|
|
|
|
ProbabilityOf0MutationsLowerBound: worstCase0MutationsProbability,
|
|
ProbabilityOf0MutationsUpperBound: bestCase0MutationsProbability,
|
|
|
|
ProbabilityOf1MutationLowerBound: lowerBound1MutationProbability,
|
|
ProbabilityOf1MutationUpperBound: upperBound1MutationProbability,
|
|
|
|
ProbabilityOf2MutationsLowerBound: bestCase2MutationsProbability,
|
|
ProbabilityOf2MutationsUpperBound: worstCase2MutationsProbability,
|
|
}
|
|
|
|
offspringVariantsInfoMap[variantIdentifier] = newOffspringMonogenicDiseaseVariantInfoObject
|
|
}
|
|
|
|
if (person1ProbabilityIsKnown == false && person2ProbabilityIsKnown == false && len(offspringVariantsInfoMap) == 0){
|
|
// We have no information about this genome pair's disease risk
|
|
// We don't add this genome pair's disease info to the diseaseInfoMap
|
|
return nil
|
|
}
|
|
|
|
numberOfVariantsTestedMap[person1GenomeIdentifier] = person1NumberOfVariantsTested
|
|
numberOfVariantsTestedMap[person2GenomeIdentifier] = person2NumberOfVariantsTested
|
|
|
|
newOffspringGenomePairMonogenicDiseaseInfoObject := geneticAnalysis.OffspringGenomePairMonogenicDiseaseInfo{
|
|
ProbabilityOffspringHasDiseaseIsKnown: offspringHasDiseaseProbabilityIsKnown,
|
|
ProbabilityOffspringHasDisease: percentageProbabilityOffspringHasDisease,
|
|
ProbabilityOffspringHasVariantIsKnown: offspringHasAVariantProbabilityIsKnown,
|
|
ProbabilityOffspringHasVariant: percentageProbabilityOffspringHasVariant,
|
|
VariantsInfoMap: offspringVariantsInfoMap,
|
|
}
|
|
|
|
genomePairIdentifier := helpers.JoinTwo16ByteArrays(person1GenomeIdentifier, person2GenomeIdentifier)
|
|
|
|
offspringMonogenicDiseaseInfoMap[genomePairIdentifier] = newOffspringGenomePairMonogenicDiseaseInfoObject
|
|
|
|
return nil
|
|
}
|
|
|
|
err = addGenomePairInfoToDiseaseMaps(pair1Person1GenomeIdentifier, pair1Person2GenomeIdentifier)
|
|
if (err != nil) { return false, "", err }
|
|
|
|
if (genomePair2Exists == true){
|
|
|
|
err := addGenomePairInfoToDiseaseMaps(pair2Person1GenomeIdentifier, pair2Person2GenomeIdentifier)
|
|
if (err != nil) { return false, "", err }
|
|
}
|
|
|
|
newOffspringMonogenicDiseaseInfoObject := geneticAnalysis.OffspringMonogenicDiseaseInfo{
|
|
NumberOfVariantsTestedMap: numberOfVariantsTestedMap,
|
|
MonogenicDiseaseInfoMap: offspringMonogenicDiseaseInfoMap,
|
|
}
|
|
|
|
// Now we check for conflicts in monogenic disease results
|
|
|
|
// For couples, a conflict is when either genome pair has differing results for any disease probability/variant probability
|
|
// This is different from a person having conflicts within their different genomes
|
|
// Each genome pair only uses 1 genome from each person.
|
|
|
|
if (len(offspringMonogenicDiseaseInfoMap) >= 2){
|
|
|
|
// Conflicts are only possible if two genome pairs with information about this disease exist
|
|
|
|
checkIfConflictExists := func()(bool, error){
|
|
|
|
probabilityOffspringHasDiseaseIsKnown := false
|
|
probabilityOffspringHasDisease := 0
|
|
probabilityOffspringHasVariantIsKnown := false
|
|
probabilityOffspringHasVariant := 0
|
|
|
|
offspringVariantsInfoMap := make(map[[3]byte]geneticAnalysis.OffspringMonogenicDiseaseVariantInfo)
|
|
|
|
firstItemReached := false
|
|
|
|
for _, offspringMonogenicDiseaseInfoObject := range offspringMonogenicDiseaseInfoMap{
|
|
|
|
currentProbabilityOffspringHasDiseaseIsKnown := offspringMonogenicDiseaseInfoObject.ProbabilityOffspringHasDiseaseIsKnown
|
|
currentProbabilityOffspringHasDisease := offspringMonogenicDiseaseInfoObject.ProbabilityOffspringHasDisease
|
|
currentProbabilityOffspringHasVariantIsKnown := offspringMonogenicDiseaseInfoObject.ProbabilityOffspringHasVariantIsKnown
|
|
currentProbabilityOffspringHasVariant := offspringMonogenicDiseaseInfoObject.ProbabilityOffspringHasVariant
|
|
|
|
currentOffspringVariantsInfoMap := offspringMonogenicDiseaseInfoObject.VariantsInfoMap
|
|
|
|
if (firstItemReached == false){
|
|
probabilityOffspringHasDiseaseIsKnown = currentProbabilityOffspringHasDiseaseIsKnown
|
|
probabilityOffspringHasDisease = currentProbabilityOffspringHasDisease
|
|
probabilityOffspringHasVariantIsKnown = currentProbabilityOffspringHasVariantIsKnown
|
|
probabilityOffspringHasVariant = currentProbabilityOffspringHasVariant
|
|
|
|
offspringVariantsInfoMap = currentOffspringVariantsInfoMap
|
|
|
|
firstItemReached = true
|
|
continue
|
|
}
|
|
if (currentProbabilityOffspringHasDiseaseIsKnown != probabilityOffspringHasDiseaseIsKnown){
|
|
return true, nil
|
|
}
|
|
if (currentProbabilityOffspringHasDisease != probabilityOffspringHasDisease){
|
|
return true, nil
|
|
}
|
|
if (currentProbabilityOffspringHasVariantIsKnown != probabilityOffspringHasVariantIsKnown){
|
|
return true, nil
|
|
}
|
|
if (currentProbabilityOffspringHasVariant != probabilityOffspringHasVariant){
|
|
return true, nil
|
|
}
|
|
areEqual := maps.Equal(currentOffspringVariantsInfoMap, offspringVariantsInfoMap)
|
|
if (areEqual == false){
|
|
return true, nil
|
|
}
|
|
}
|
|
|
|
return false, nil
|
|
}
|
|
|
|
conflictExists, err := checkIfConflictExists()
|
|
if (err != nil) { return false, "", err }
|
|
|
|
newOffspringMonogenicDiseaseInfoObject.ConflictExists = conflictExists
|
|
}
|
|
|
|
offspringMonogenicDiseasesMap[diseaseName] = newOffspringMonogenicDiseaseInfoObject
|
|
}
|
|
|
|
newCoupleAnalysis.MonogenicDiseasesMap = offspringMonogenicDiseasesMap
|
|
|
|
// Step 2: Polygenic Diseases
|
|
|
|
polygenicDiseaseObjectsList, err := polygenicDiseases.GetPolygenicDiseaseObjectsList()
|
|
if (err != nil){ return false, "", err }
|
|
|
|
// Map Structure: Disease Name -> OffspringPolygenicDiseaseInfo
|
|
offspringPolygenicDiseasesMap := make(map[string]geneticAnalysis.OffspringPolygenicDiseaseInfo)
|
|
|
|
for _, diseaseObject := range polygenicDiseaseObjectsList{
|
|
|
|
diseaseName := diseaseObject.DiseaseName
|
|
diseaseLociList := diseaseObject.LociList
|
|
|
|
person1DiseaseAnalysisObject, err := getPersonPolygenicDiseaseAnalysis(person1GenomesWithMetadataList, diseaseObject)
|
|
if (err != nil) { return false, "", err }
|
|
|
|
person2DiseaseAnalysisObject, err := 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)
|
|
|
|
// This will calculate the disease info for the offspring from the two specified genomes to the diseases map
|
|
// It then adds the pair entry to the offspringPolygenicDiseaseInfoMap
|
|
addGenomePairDiseaseInfoToDiseaseMap := func(person1GenomeIdentifier [16]byte, person2GenomeIdentifier [16]byte)error{
|
|
|
|
summedRiskWeights := 0
|
|
minimumPossibleRiskWeightSum := 0
|
|
maximumPossibleRiskWeightSum := 0
|
|
|
|
// Map Structure: Locus Identifier -> OffspringPolygenicDiseaseLocusInfo
|
|
offspringDiseaseLociInfoMap := make(map[[3]byte]geneticAnalysis.OffspringPolygenicDiseaseLocusInfo)
|
|
|
|
for _, locusObject := range diseaseLociList{
|
|
|
|
locusIdentifierHex := locusObject.LocusIdentifier
|
|
|
|
locusIdentifier, err := encoding.DecodeHexStringTo3ByteArray(locusIdentifierHex)
|
|
if (err != nil) { return err }
|
|
|
|
locusRiskWeightsMap := locusObject.RiskWeightsMap
|
|
locusOddsRatiosMap := locusObject.OddsRatiosMap
|
|
|
|
//Outputs:
|
|
// -bool: Locus value exists
|
|
// -string: Base1 Value
|
|
// -string: Base2 Value
|
|
// -error
|
|
getPersonGenomeLocusValues := func(personGenomeIdentifier [16]byte, personDiseaseAnalysisObject geneticAnalysis.PersonPolygenicDiseaseInfo)(bool, string, string, 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
|
|
}
|
|
|
|
personGenomeLociMap := personGenomeDiseaseInfoObject.LociInfoMap
|
|
|
|
personGenomeLocusInfoObject, exists := personGenomeLociMap[locusIdentifier]
|
|
if (exists == false){
|
|
// This person's genome doesn't have information about this locus
|
|
return false, "", "", nil
|
|
}
|
|
|
|
locusBase1 := personGenomeLocusInfoObject.LocusBase1
|
|
locusBase2 := personGenomeLocusInfoObject.LocusBase2
|
|
|
|
return true, locusBase1, locusBase2, nil
|
|
}
|
|
|
|
person1LocusBasePairKnown, person1LocusBase1, person1LocusBase2, err := getPersonGenomeLocusValues(person1GenomeIdentifier, person1DiseaseAnalysisObject)
|
|
if (err != nil) { return err }
|
|
if (person1LocusBasePairKnown == false){
|
|
// Offspring's disease info for this locus on this genome pair is unknown
|
|
continue
|
|
}
|
|
|
|
person2LocusBasePairKnown, person2LocusBase1, person2LocusBase2, err := getPersonGenomeLocusValues(person2GenomeIdentifier, person2DiseaseAnalysisObject)
|
|
if (err != nil) { return err }
|
|
if (person2LocusBasePairKnown == false){
|
|
// Offspring's disease info for this locus on this genome pair is unknown
|
|
continue
|
|
}
|
|
|
|
offspringAverageRiskWeight, offspringOddsRatioIsKnown, offspringAverageOddsRatio, averageUnknownOddsRatiosWeightSum, err := GetOffspringPolygenicDiseaseLocusInfo(locusRiskWeightsMap, locusOddsRatiosMap, person1LocusBase1, person1LocusBase2, person2LocusBase1, person2LocusBase2)
|
|
if (err != nil) { return err }
|
|
|
|
newOffspringPolygenicDiseaseLocusInfo := geneticAnalysis.OffspringPolygenicDiseaseLocusInfo{
|
|
OffspringRiskWeight: offspringAverageRiskWeight,
|
|
OffspringUnknownOddsRatiosWeightSum: averageUnknownOddsRatiosWeightSum,
|
|
}
|
|
|
|
if (offspringOddsRatioIsKnown == true){
|
|
|
|
newOffspringPolygenicDiseaseLocusInfo.OffspringOddsRatioIsKnown = true
|
|
newOffspringPolygenicDiseaseLocusInfo.OffspringOddsRatio = offspringAverageOddsRatio
|
|
}
|
|
|
|
offspringDiseaseLociInfoMap[locusIdentifier] = newOffspringPolygenicDiseaseLocusInfo
|
|
|
|
// Now we add risk weight info for this locus
|
|
|
|
locusMinimumRiskWeight := locusObject.MinimumRiskWeight
|
|
locusMaximumRiskWeight := locusObject.MaximumRiskWeight
|
|
|
|
minimumPossibleRiskWeightSum += locusMinimumRiskWeight
|
|
maximumPossibleRiskWeightSum += locusMaximumRiskWeight
|
|
|
|
summedRiskWeights += offspringAverageRiskWeight
|
|
}
|
|
|
|
numberOfLociTested := len(offspringDiseaseLociInfoMap)
|
|
|
|
if (numberOfLociTested == 0){
|
|
// We have no information about this genome pair's disease risk
|
|
// We don't add this genome pair's disease info to the diseaseInfoMap
|
|
return nil
|
|
}
|
|
|
|
genomePairDiseaseRiskScore, err := helpers.ScaleNumberProportionally(true, summedRiskWeights, minimumPossibleRiskWeightSum, maximumPossibleRiskWeightSum, 0, 10)
|
|
if (err != nil) { return err }
|
|
|
|
newOffspringGenomePairPolygenicDiseaseInfo := geneticAnalysis.OffspringGenomePairPolygenicDiseaseInfo{
|
|
|
|
NumberOfLociTested: numberOfLociTested,
|
|
OffspringRiskScore: genomePairDiseaseRiskScore,
|
|
LociInfoMap: offspringDiseaseLociInfoMap,
|
|
}
|
|
|
|
genomePairIdentifier := helpers.JoinTwo16ByteArrays(person1GenomeIdentifier, person2GenomeIdentifier)
|
|
|
|
offspringPolygenicDiseaseInfoMap[genomePairIdentifier] = newOffspringGenomePairPolygenicDiseaseInfo
|
|
|
|
return nil
|
|
}
|
|
|
|
err = addGenomePairDiseaseInfoToDiseaseMap(pair1Person1GenomeIdentifier, pair1Person2GenomeIdentifier)
|
|
if (err != nil) { return false, "", err }
|
|
|
|
if (genomePair2Exists == true){
|
|
|
|
err := addGenomePairDiseaseInfoToDiseaseMap(pair2Person1GenomeIdentifier, pair2Person2GenomeIdentifier)
|
|
if (err != nil) { return false, "", err }
|
|
}
|
|
|
|
newOffspringPolygenicDiseaseInfoObject := geneticAnalysis.OffspringPolygenicDiseaseInfo{
|
|
PolygenicDiseaseInfoMap: offspringPolygenicDiseaseInfoMap,
|
|
}
|
|
|
|
if (len(offspringPolygenicDiseaseInfoMap) >= 2){
|
|
|
|
// We check for conflicts
|
|
// Conflicts are only possible if two genome pairs with disease info for this disease exist
|
|
|
|
checkIfConflictExists := func()(bool, error){
|
|
|
|
numberOfLociTested := 0
|
|
offspringRiskScore := 0
|
|
offspringLociInfoMap := make(map[[3]byte]geneticAnalysis.OffspringPolygenicDiseaseLocusInfo)
|
|
|
|
firstItemReached := false
|
|
|
|
for _, genomePairDiseaseInfoObject := range offspringPolygenicDiseaseInfoMap{
|
|
|
|
genomePairNumberOfLociTested := genomePairDiseaseInfoObject.NumberOfLociTested
|
|
genomePairOffspringRiskScore := genomePairDiseaseInfoObject.OffspringRiskScore
|
|
genomePairLociInfoMap := genomePairDiseaseInfoObject.LociInfoMap
|
|
|
|
if (firstItemReached == false){
|
|
numberOfLociTested = genomePairNumberOfLociTested
|
|
offspringRiskScore = genomePairOffspringRiskScore
|
|
offspringLociInfoMap = genomePairLociInfoMap
|
|
firstItemReached = true
|
|
continue
|
|
}
|
|
if (numberOfLociTested != genomePairNumberOfLociTested){
|
|
return true, nil
|
|
}
|
|
if (offspringRiskScore != genomePairOffspringRiskScore){
|
|
return true, nil
|
|
}
|
|
areEqual := maps.Equal(offspringLociInfoMap, genomePairLociInfoMap)
|
|
if (areEqual == false){
|
|
// A conflict exists
|
|
return true, nil
|
|
}
|
|
}
|
|
|
|
return false, nil
|
|
}
|
|
|
|
conflictExists, err := checkIfConflictExists()
|
|
if (err != nil) { return false, "", err }
|
|
|
|
newOffspringPolygenicDiseaseInfoObject.ConflictExists = conflictExists
|
|
}
|
|
|
|
offspringPolygenicDiseasesMap[diseaseName] = newOffspringPolygenicDiseaseInfoObject
|
|
}
|
|
|
|
newCoupleAnalysis.PolygenicDiseasesMap = offspringPolygenicDiseasesMap
|
|
|
|
// Step 3: Traits
|
|
|
|
traitObjectsList, err := traits.GetTraitObjectsList()
|
|
if (err != nil) { return false, "", err }
|
|
|
|
// Map Structure: Trait Name -> Trait Info Object
|
|
offspringTraitsMap := make(map[string]geneticAnalysis.OffspringTraitInfo)
|
|
|
|
for _, traitObject := range traitObjectsList{
|
|
|
|
traitName := traitObject.TraitName
|
|
|
|
person1TraitAnalysisObject, err := getPersonTraitAnalysis(person1GenomesWithMetadataList, traitObject)
|
|
if (err != nil) { return false, "", err }
|
|
|
|
person2TraitAnalysisObject, err := getPersonTraitAnalysis(person2GenomesWithMetadataList, traitObject)
|
|
if (err != nil) { return false, "", err }
|
|
|
|
// 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{
|
|
|
|
person1TraitInfoMap := person1TraitAnalysisObject.TraitInfoMap
|
|
person2TraitInfoMap := person2TraitAnalysisObject.TraitInfoMap
|
|
|
|
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
|
|
}
|
|
|
|
person1LocusValuesMap := person1GenomeTraitInfoObject.LocusValuesMap
|
|
person2LocusValuesMap := person2GenomeTraitInfoObject.LocusValuesMap
|
|
|
|
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
|
|
}
|
|
|
|
newOffspringGenomePairTraitInfoObject := geneticAnalysis.OffspringGenomePairTraitInfo{
|
|
NumberOfRulesTested: numberOfRulesTested,
|
|
OffspringAverageOutcomeScoresMap: offspringAverageOutcomeScoresMap,
|
|
ProbabilityOfPassingRulesMap: offspringProbabilityOfPassingRulesMap,
|
|
}
|
|
|
|
genomePairIdentifier := helpers.JoinTwo16ByteArrays(person1GenomeIdentifier, person2GenomeIdentifier)
|
|
|
|
offspringTraitInfoMap[genomePairIdentifier] = newOffspringGenomePairTraitInfoObject
|
|
|
|
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
|
|
}
|
|
}
|
|
|
|
return false, nil
|
|
}
|
|
|
|
conflictExists, err := checkIfConflictExists()
|
|
if (err != nil) { return false, "", err }
|
|
|
|
newOffspringTraitInfoObject.ConflictExists = conflictExists
|
|
}
|
|
|
|
offspringTraitsMap[traitName] = newOffspringTraitInfoObject
|
|
}
|
|
|
|
newCoupleAnalysis.TraitsMap = offspringTraitsMap
|
|
|
|
analysisBytes, err := encoding.EncodeMessagePackBytes(newCoupleAnalysis)
|
|
if (err != nil) { return false, "", err }
|
|
|
|
analysisString := string(analysisBytes)
|
|
|
|
return true, analysisString, nil
|
|
}
|
|
|
|
// This function will return a list of 100 prospective offspring genomes
|
|
// 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
|
|
//Outputs:
|
|
// -bool: Any locus value exists between both users
|
|
// -[]map[int64]locusValue.LocusValue
|
|
// -error
|
|
func getProspectiveOffspringGenomesList(lociList []int64, person1LociMap map[int64]locusValue.LocusValue, person2LociMap map[int64]locusValue.LocusValue)(bool, []map[int64]locusValue.LocusValue, error){
|
|
|
|
// -We use randomness to generate the offspring genomes
|
|
// -We want the results to be the same for each pair of people each time, so we have to seed our randomness generator
|
|
// -This is necessary so that two people's analysis results do not change every time
|
|
// -Instead, the same 2 people will produce the exact same result every time
|
|
pseudorandomNumberGenerator := mathRand.New(mathRand.NewPCG(1, 2))
|
|
|
|
//Outputs:
|
|
// -[]int64: A list of random breakpoints for this chromosome that are statistically accurate
|
|
// -error
|
|
getRandomChromosomeBreakpoints := func(chromosome int)([]int64, error){
|
|
|
|
getChromosomeLength := func()(int64, error){
|
|
|
|
// Approximate number of base pairs in each chromosome taken from: https://www.ncbi.nlm.nih.gov/books/NBK557784/
|
|
|
|
switch chromosome{
|
|
|
|
case 1:{
|
|
return 249000000, nil
|
|
}
|
|
case 2:{
|
|
return 243000000, nil
|
|
}
|
|
case 3:{
|
|
return 200000000, nil
|
|
}
|
|
case 4:{
|
|
return 192000000, nil
|
|
}
|
|
case 5:{
|
|
return 181000000, nil
|
|
}
|
|
case 6:{
|
|
return 170000000, nil
|
|
}
|
|
case 7:{
|
|
return 158000000, nil
|
|
}
|
|
case 8:{
|
|
return 146000000, nil
|
|
}
|
|
case 9:{
|
|
return 140000000, nil
|
|
}
|
|
case 10:{
|
|
return 135000000, nil
|
|
}
|
|
case 11:{
|
|
return 135000000, nil
|
|
}
|
|
case 12:{
|
|
return 132000000, nil
|
|
}
|
|
case 13:{
|
|
return 114000000, nil
|
|
}
|
|
case 14:{
|
|
return 106000000, nil
|
|
}
|
|
case 15:{
|
|
return 100000000, nil
|
|
}
|
|
case 16:{
|
|
return 89000000, nil
|
|
}
|
|
case 17:{
|
|
return 79000000, nil
|
|
}
|
|
case 18:{
|
|
return 76000000, nil
|
|
}
|
|
case 19:{
|
|
return 64000000, nil
|
|
}
|
|
case 20:{
|
|
return 62000000, nil
|
|
}
|
|
case 21:{
|
|
return 47000000, nil
|
|
}
|
|
case 22:{
|
|
return 50000000, nil
|
|
}
|
|
}
|
|
|
|
chromosomeString := helpers.ConvertIntToString(chromosome)
|
|
return 0, errors.New("getRandomChromosomeBreakpoints called with invalid chromosome: " + chromosomeString)
|
|
}
|
|
|
|
chromosomeLength, err := getChromosomeLength()
|
|
if (err != nil) { return nil, err }
|
|
|
|
listOfRandomBreakpoints := make([]int64, 0)
|
|
|
|
// TODO: Take into account different recombination rate for each chromosome
|
|
// TODO: There are also breakpoint hotspots which we need to account for
|
|
// TODO: I read somewhere that recombination break points are less likely to occur within genes,
|
|
// meaning they are more likely to occur at the gene boundaries (codons)
|
|
|
|
// 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{
|
|
|
|
//From Wikipedia:
|
|
// A centimorgan (abbreviated cM) is a unit for measuring genetic linkage.
|
|
// It is defined as the distance between chromosome positions (loci) for which the expected
|
|
// average number of intervening chromosomal crossovers in a single generation is 0.01.
|
|
// One centimorgan corresponds to about 1 million base pairs in humans on average
|
|
//
|
|
// A chromosomal crossover == recombination breakpoint
|
|
//
|
|
// For every 1,000,000 base pairs, there is a 0.01 probability that there is a breakpoint
|
|
|
|
randomFloat := pseudorandomNumberGenerator.Float64()
|
|
if (randomFloat <= 0.01){
|
|
// This has a 0.01, or 1% probability of being true
|
|
listOfRandomBreakpoints = append(listOfRandomBreakpoints, position)
|
|
}
|
|
}
|
|
|
|
return listOfRandomBreakpoints, nil
|
|
}
|
|
|
|
// Map Structure: rsID -> Locus Value
|
|
offspringGenomesList := make([]map[int64]locusValue.LocusValue, 0)
|
|
|
|
for i:=0; i < 100; i++{
|
|
|
|
// This map stores the chromosome breakpoints for person1
|
|
// Map Structure: Chromosome -> List of breakpoints
|
|
person1ChromosomeBreakpointsMap := make(map[int][]int64)
|
|
|
|
// This map stores the chromosome breakpoints for person2
|
|
// Map Structure: Chromosome -> List of breakpoints
|
|
person2ChromosomeBreakpointsMap := make(map[int][]int64)
|
|
|
|
// This stores the locus values for this prospective offspring
|
|
// Map Structure: rsID -> Locus Value
|
|
prospectiveOffspringGenome := make(map[int64]locusValue.LocusValue)
|
|
|
|
for _, rsID := range lociList{
|
|
|
|
//Outputs:
|
|
// -bool: Allele is known
|
|
// -string: Locus base
|
|
// -error
|
|
getPersonAllele := func(personLociMap map[int64]locusValue.LocusValue, personBreakpointsMap map[int][]int64)(bool, string, error){
|
|
|
|
personLocusValue, exists := personLociMap[rsID]
|
|
if (exists == false){
|
|
return false, "", nil
|
|
}
|
|
|
|
personLocusBase1 := personLocusValue.Base1Value
|
|
personLocusBase2 := personLocusValue.Base1Value
|
|
personLocusIsPhased := personLocusValue.LocusIsPhased
|
|
|
|
if (personLocusIsPhased == false){
|
|
// Breakpoints are unnecessary
|
|
// We either choose base 1 or 2
|
|
randomBool := helpers.GetRandomBool()
|
|
if (randomBool == true){
|
|
return true, personLocusBase1, nil
|
|
}
|
|
return true, personLocusBase2, nil
|
|
}
|
|
|
|
// We have a phased locus
|
|
// We figure out which allele to use by seeing which allele gets inherited from our random breakpoints list
|
|
// We figure out the chromosome and position of this locus
|
|
|
|
locusMetadataExists, locusMetadataObject, err := locusMetadata.GetLocusMetadata(rsID)
|
|
if (err != nil) { return false, "", err }
|
|
if (locusMetadataExists == false){
|
|
rsIDString := helpers.ConvertInt64ToString(rsID)
|
|
return false, "", errors.New("getProspectiveOffspringGenomesList called with unknown rsID: " + rsIDString)
|
|
}
|
|
|
|
locusPosition := locusMetadataObject.Position
|
|
locusChromosome := locusMetadataObject.Chromosome
|
|
|
|
getPersonChromosomeBreakpointsList := func()([]int64, error){
|
|
|
|
breakpointsList, exists := personBreakpointsMap[locusChromosome]
|
|
if (exists == true){
|
|
return breakpointsList, nil
|
|
}
|
|
|
|
// We have to create a new breakpoints list
|
|
|
|
newBreakpointsList, err := getRandomChromosomeBreakpoints(locusChromosome)
|
|
if (err != nil) { return nil, err }
|
|
|
|
personBreakpointsMap[locusChromosome] = newBreakpointsList
|
|
|
|
return newBreakpointsList, nil
|
|
}
|
|
|
|
personBreakpointsList, err := getPersonChromosomeBreakpointsList()
|
|
if (err != nil) { return false, "", err }
|
|
|
|
getLocusListIndex := func()int{
|
|
|
|
for index, breakpoint := range personBreakpointsList{
|
|
|
|
if (int64(locusPosition) <= breakpoint){
|
|
|
|
return index
|
|
}
|
|
}
|
|
|
|
index := len(personBreakpointsList)
|
|
|
|
// This is reached if the final breakpoint in the list is less than the locus's position, or if there were no breakpoints
|
|
|
|
return index
|
|
}
|
|
|
|
locusListIndex := getLocusListIndex()
|
|
|
|
if (locusListIndex%2 == 0){
|
|
return true, personLocusBase1, nil
|
|
}
|
|
|
|
return true, personLocusBase2, nil
|
|
}
|
|
|
|
person1AlleleIsKnown, person1Allele, err := getPersonAllele(person1LociMap, person1ChromosomeBreakpointsMap)
|
|
if (err != nil) { return false, nil, err }
|
|
if (person1AlleleIsKnown == false){
|
|
continue
|
|
}
|
|
|
|
person2AlleleIsKnown, person2Allele, err := getPersonAllele(person2LociMap, person2ChromosomeBreakpointsMap)
|
|
if (err != nil) { return false, nil, err }
|
|
if (person2AlleleIsKnown == false){
|
|
continue
|
|
}
|
|
|
|
offspringLocusValue := locusValue.LocusValue{
|
|
Base1Value: person1Allele,
|
|
Base2Value: person2Allele,
|
|
LocusIsPhased: true,
|
|
}
|
|
|
|
prospectiveOffspringGenome[rsID] = offspringLocusValue
|
|
}
|
|
|
|
if (len(prospectiveOffspringGenome) == 0){
|
|
// We don't have any locations at which both people's genomes contain a locus value.
|
|
return false, nil, nil
|
|
}
|
|
|
|
offspringGenomesList = append(offspringGenomesList, prospectiveOffspringGenome)
|
|
}
|
|
|
|
return true, offspringGenomesList, nil
|
|
}
|
|
|
|
// We also use this function when calculating offspring probabilities between users in viewProfileGui.go
|
|
//Outputs:
|
|
// -bool: Probability offspring has disease is known
|
|
// -int: Percentage probability offspring has disease (0-100)
|
|
// -bool: Probability offspring has variant is known
|
|
// -int: Percentage probability offspring has variant (0-100)
|
|
// -error
|
|
func GetOffspringMonogenicDiseaseProbabilities(dominantOrRecessive string, person1ProbabilityIsKnown bool, person1WillPassVariantPercentageProbability int, person2ProbabilityIsKnown bool, person2WillPassVariantPercentageProbability int)(bool, int, bool, int, error){
|
|
|
|
if (dominantOrRecessive != "Dominant" && dominantOrRecessive != "Recessive"){
|
|
return false, 0, false, 0, errors.New("GetOffspringMonogenicDiseaseProbabilities called with invalid dominantOrRecessive: " + dominantOrRecessive)
|
|
}
|
|
if (person1ProbabilityIsKnown == false && person2ProbabilityIsKnown == false){
|
|
return false, 0, false, 0, nil
|
|
}
|
|
|
|
if (person1ProbabilityIsKnown == true){
|
|
if (person1WillPassVariantPercentageProbability < 0 || person1WillPassVariantPercentageProbability > 100){
|
|
return false, 0, false, 0, errors.New("GetOffspringMonogenicDiseaseProbabilities called with invalid person1WillPassVariantProbability")
|
|
}
|
|
}
|
|
if (person2ProbabilityIsKnown == true){
|
|
if (person2WillPassVariantPercentageProbability < 0 || person2WillPassVariantPercentageProbability > 100){
|
|
return false, 0, false, 0, errors.New("GetOffspringMonogenicDiseaseProbabilities called with invalid person2WillPassVariantProbability")
|
|
}
|
|
}
|
|
if (person1ProbabilityIsKnown == false || person2ProbabilityIsKnown == false){
|
|
// Only 1 of the person's probabilities are known
|
|
|
|
getPersonWhoHasVariantProbabilityOfPassingIt := func()int{
|
|
if (person1ProbabilityIsKnown == true){
|
|
return person1WillPassVariantPercentageProbability
|
|
}
|
|
return person2WillPassVariantPercentageProbability
|
|
}
|
|
|
|
personWhoHasVariantProbabilityOfPassingIt := getPersonWhoHasVariantProbabilityOfPassingIt()
|
|
|
|
if (personWhoHasVariantProbabilityOfPassingIt == 100){
|
|
if (dominantOrRecessive == "Dominant"){
|
|
// We know the offspring will have the disease and will have a variant
|
|
return true, 100, true, 100, nil
|
|
}
|
|
//dominantOrRecessive == "Recessive"
|
|
// We don't know if the offspring will have the disease, but we know they will have a variant
|
|
return false, 0, true, 100, nil
|
|
}
|
|
if (personWhoHasVariantProbabilityOfPassingIt == 0){
|
|
|
|
if (dominantOrRecessive == "Recessive"){
|
|
// We know the offspring will not have the disease, but we don't know if they will have a variant
|
|
return true, 0, false, 0, nil
|
|
}
|
|
}
|
|
|
|
// We don't know the probabilities that the offspring will have the disease or if they will have a variant
|
|
return false, 0, false, 0, nil
|
|
}
|
|
|
|
person1WillPassVariantProbability := float64(person1WillPassVariantPercentageProbability)/100
|
|
person2WillPassVariantProbability := float64(person2WillPassVariantPercentageProbability)/100
|
|
|
|
// The probability offspring has a variant = the probability that either parent passes a variant (inclusive or)
|
|
// We find the probability of the offspring having a monogenic disease variant as follows:
|
|
// P(A U B) = P(A) + P(B) - P(A ∩ B)
|
|
// (Probability of person 1 passing a variant) + (Probability of person 2 passing a variant) - (Probability of offspring having disease)
|
|
// A person with a variant may have the disease, or just be a carrier.
|
|
probabilityOffspringHasVariant := person1WillPassVariantProbability + person2WillPassVariantProbability - (person1WillPassVariantProbability * person2WillPassVariantProbability)
|
|
|
|
if (dominantOrRecessive == "Dominant"){
|
|
|
|
// The probability of having the monogenic disease is the same as the probability of having a variant
|
|
|
|
percentageProbabilityOffspringHasVariant := int(probabilityOffspringHasVariant * 100)
|
|
|
|
return true, percentageProbabilityOffspringHasVariant, true, percentageProbabilityOffspringHasVariant, nil
|
|
}
|
|
|
|
// We find the probability of the offspring having the mongenic disease as follows:
|
|
// P(A and B) = P(A) * P(B)
|
|
// (Probability of person 1 Passing a variant) * (Probability of person 2 passing a variant)
|
|
probabilityOffspringHasDisease := person1WillPassVariantProbability * person2WillPassVariantProbability
|
|
|
|
percentageProbabilityOffspringHasDisease := probabilityOffspringHasDisease * 100
|
|
percentageProbabilityOffspringHasVariant := probabilityOffspringHasVariant * 100
|
|
|
|
// This conversion remove any digits after the radix point
|
|
// This will not result in any false 0% values, an example being 0.9% becoming 0%
|
|
// This is because the lowest non-zero probability a person can have for passing a variant is 50%
|
|
// Thus, the lowest non-zero probability of an offspring having a disease is 25%
|
|
percentageProbabilityOffspringHasDiseaseInt := int(percentageProbabilityOffspringHasDisease)
|
|
percentageProbabilityOffspringHasVariantInt := int(percentageProbabilityOffspringHasVariant)
|
|
|
|
return true, percentageProbabilityOffspringHasDiseaseInt, true, percentageProbabilityOffspringHasVariantInt, nil
|
|
}
|
|
|
|
//Outputs:
|
|
// -int: Offspring average risk weight
|
|
// -bool: Odds ratio is known
|
|
// -float64: Offspring average odds ratio
|
|
// -int: Offspring unknown odds ratios weight sum
|
|
// -error
|
|
func GetOffspringPolygenicDiseaseLocusInfo(locusRiskWeightsMap map[string]int, locusOddsRatiosMap map[string]float64, person1LocusBase1 string, person1LocusBase2 string, person2LocusBase1 string, person2LocusBase2 string)(int, bool, float64, int, error){
|
|
|
|
// We create the 4 options for the offspring's bases at this locus
|
|
|
|
offspringBasePairOutcome1 := person1LocusBase1 + ";" + person2LocusBase1
|
|
offspringBasePairOutcome2 := person1LocusBase2 + ";" + person2LocusBase2
|
|
offspringBasePairOutcome3 := person1LocusBase1 + ";" + person2LocusBase2
|
|
offspringBasePairOutcome4 := person1LocusBase2 + ";" + person2LocusBase1
|
|
|
|
baseOutcomesList := []string{offspringBasePairOutcome1, offspringBasePairOutcome2, offspringBasePairOutcome3, offspringBasePairOutcome4}
|
|
|
|
summedRiskWeight := 0
|
|
|
|
numberOfSummedOddsRatios := 0
|
|
summedOddsRatios := float64(0)
|
|
|
|
numberOfSummedUnknownOddsRatioWeights := 0
|
|
summedUnknownOddsRatioWeights := 0
|
|
|
|
for _, outcomeBasePair := range baseOutcomesList{
|
|
|
|
isValid := verifyBasePair(outcomeBasePair)
|
|
if (isValid == false){
|
|
return 0, false, 0, 0, errors.New("GetOffspringPolygenicDiseaseLocusInfo called with invalid locus base pair: " + outcomeBasePair)
|
|
}
|
|
|
|
offspringOutcomeRiskWeight, exists := locusRiskWeightsMap[outcomeBasePair]
|
|
if (exists == false){
|
|
// We do not know the risk weight for this base pair
|
|
// We treat this as a 0 risk for both weight and odds ratio
|
|
// No effect on risk is represented as an odds ratio of 1
|
|
|
|
summedOddsRatios += 1
|
|
numberOfSummedOddsRatios += 1
|
|
continue
|
|
}
|
|
summedRiskWeight += offspringOutcomeRiskWeight
|
|
|
|
offspringOutcomeOddsRatio, exists := locusOddsRatiosMap[outcomeBasePair]
|
|
if (exists == false){
|
|
// This particular outcome has no known odds ratio
|
|
// We add it to the unknown odds ratio weights sum
|
|
summedUnknownOddsRatioWeights += offspringOutcomeRiskWeight
|
|
numberOfSummedUnknownOddsRatioWeights += 1
|
|
} else {
|
|
summedOddsRatios += offspringOutcomeOddsRatio
|
|
numberOfSummedOddsRatios += 1
|
|
}
|
|
}
|
|
|
|
averageRiskWeight := summedRiskWeight/4
|
|
|
|
getAverageUnknownOddsRatiosWeightSum := func()int{
|
|
|
|
if (numberOfSummedUnknownOddsRatioWeights == 0){
|
|
return 0
|
|
}
|
|
averageUnknownOddsRatiosWeightSum := summedUnknownOddsRatioWeights/numberOfSummedUnknownOddsRatioWeights
|
|
return averageUnknownOddsRatiosWeightSum
|
|
}
|
|
|
|
averageUnknownOddsRatiosWeightSum := getAverageUnknownOddsRatiosWeightSum()
|
|
|
|
if (numberOfSummedOddsRatios == 0){
|
|
|
|
return averageRiskWeight, false, 0, averageUnknownOddsRatiosWeightSum, nil
|
|
}
|
|
|
|
averageOddsRatio := summedOddsRatios/float64(numberOfSummedOddsRatios)
|
|
|
|
return averageRiskWeight, true, averageOddsRatio, averageUnknownOddsRatiosWeightSum, nil
|
|
}
|
|
|
|
|
|
//Outputs:
|
|
// -bool: Any rules tested (if false, no offspring trait information is known)
|
|
// -int: Number of rules tested
|
|
// -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
|
|
// -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){
|
|
|
|
// First, we create 100 prospective offspring genomes.
|
|
|
|
traitLociList := traitObject.LociList
|
|
|
|
anyLocusValueExists, prospectiveOffspringGenomesList, err := getProspectiveOffspringGenomesList(traitLociList, person1LocusValuesMap, person2LocusValuesMap)
|
|
if (err != nil) { return false, 0, nil, nil, err }
|
|
if (anyLocusValueExists == false){
|
|
return false, 0, nil, nil, nil
|
|
}
|
|
|
|
traitRulesList := traitObject.RulesList
|
|
|
|
// Map Structure: Rule Identifier -> Number of offspring who pass the rule (out of 100 prospective offspring)
|
|
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)
|
|
|
|
for offspringIndex, offspringGenomeMap := range prospectiveOffspringGenomesList{
|
|
|
|
// We iterate through rules to determine genome pair trait info
|
|
|
|
for _, ruleObject := range traitRulesList{
|
|
|
|
ruleIdentifierHex := ruleObject.RuleIdentifier
|
|
|
|
ruleIdentifier, err := encoding.DecodeHexStringTo3ByteArray(ruleIdentifierHex)
|
|
if (err != nil) { return false, 0, nil, nil, err }
|
|
|
|
if (offspringIndex != 0){
|
|
|
|
_, 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
|
|
|
|
//Outputs:
|
|
// -bool: Offspring passes rule is known
|
|
// -bool: Offspring passes rule
|
|
getOffspringPassesRuleStatus := func()(bool, bool){
|
|
|
|
// If any rule locus status is unknown, then we consider the offspring-passes-rule status to be unknown,
|
|
// unless we know that there is a rule that the offspring does not pass
|
|
anyRuleIsUnknown := false
|
|
|
|
for _, ruleLocusObject := range ruleLocusObjectsList{
|
|
|
|
locusRSID := ruleLocusObject.LocusRSID
|
|
|
|
locusRequiredBasePairsList := ruleLocusObject.BasePairsList
|
|
|
|
offspringLocusValue, exists := offspringGenomeMap[locusRSID]
|
|
if (exists == false){
|
|
anyRuleIsUnknown = true
|
|
// We keep searching to see if there are any rules we know the offspring does not pass
|
|
continue
|
|
}
|
|
|
|
offspringBase1 := offspringLocusValue.Base1Value
|
|
offspringBase2 := offspringLocusValue.Base2Value
|
|
|
|
offspringBasePair := offspringBase1 + ";" + offspringBase2
|
|
|
|
offspringPassesRuleLocus := slices.Contains(locusRequiredBasePairsList, offspringBasePair)
|
|
if (offspringPassesRuleLocus == false){
|
|
// The offspring does not pass this rule locus
|
|
// Thus, the offspring does not pass the rule
|
|
return true, false
|
|
}
|
|
}
|
|
|
|
if (anyRuleIsUnknown == true){
|
|
// We don't know if the offspring passes the rule
|
|
return false, false
|
|
}
|
|
|
|
// The offspring passes the rule
|
|
return true, true
|
|
}
|
|
|
|
offspringPassesRuleIsKnown, offspringPassesRule := getOffspringPassesRuleStatus()
|
|
if (offspringPassesRuleIsKnown == false){
|
|
continue
|
|
}
|
|
|
|
offspringRulesWithKnownStatusMap[ruleIdentifier] = ruleObject
|
|
|
|
if (offspringPassesRule == 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
|
|
}
|
|
|
|
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
|
|
}
|
|
}
|
|
|
|
numberOfRulesTested := len(offspringProbabilityOfPassingRulesMap)
|
|
|
|
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
|
|
}
|
|
|
|
// This function will retrieve the base pair of the locus from the input genome map
|
|
// We need this because each rsID has aliases, so we must sometimes check those aliases to find locus values
|
|
//
|
|
// Outputs:
|
|
// -bool: Valid base pair value found
|
|
// -string: Base 1 Value (Nucleotide base for the SNP)
|
|
// -string: Base 2 Value (Nucleotide base for the SNP)
|
|
// -bool: Locus base pair is phased
|
|
// -error
|
|
func getGenomeLocusBasePair(inputGenomeMap map[int64]locusValue.LocusValue, locusRSID int64)(bool, string, string, bool, error){
|
|
|
|
// Outputs:
|
|
// -bool: Locus value found
|
|
// -locusValue.LocusValue
|
|
// -error
|
|
getLocusValue := func()(bool, locusValue.LocusValue, error){
|
|
|
|
currentLocusValue, exists := inputGenomeMap[locusRSID]
|
|
if (exists == true){
|
|
return true, currentLocusValue, nil
|
|
}
|
|
|
|
// We check for aliases
|
|
|
|
anyAliasesExist, rsidAliasesList, err := locusMetadata.GetRSIDAliases(locusRSID)
|
|
if (err != nil) { return false, locusValue.LocusValue{}, err }
|
|
if (anyAliasesExist == false){
|
|
return false, locusValue.LocusValue{}, nil
|
|
}
|
|
|
|
for _, rsidAlias := range rsidAliasesList{
|
|
|
|
currentLocusValue, exists := inputGenomeMap[rsidAlias]
|
|
if (exists == true){
|
|
return true, currentLocusValue, nil
|
|
}
|
|
}
|
|
|
|
return false, locusValue.LocusValue{}, nil
|
|
}
|
|
|
|
locusValueFound, locusValueObject, err := getLocusValue()
|
|
if (err != nil) { return false, "", "", false, err }
|
|
if (locusValueFound == false){
|
|
return false, "", "", false, nil
|
|
}
|
|
|
|
base1Value := locusValueObject.Base1Value
|
|
base2Value := locusValueObject.Base2Value
|
|
locusIsPhased := locusValueObject.LocusIsPhased
|
|
|
|
return true, base1Value, base2Value, locusIsPhased, nil
|
|
}
|
|
|
|
|
|
//Outputs:
|
|
// -geneticAnalysis.PersonMonogenicDiseaseInfo: Monogenic disease analysis object
|
|
// -error
|
|
func getPersonMonogenicDiseaseAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.GenomeWithMetadata, diseaseObject monogenicDiseases.MonogenicDisease)(geneticAnalysis.PersonMonogenicDiseaseInfo, error){
|
|
|
|
emptyDiseaseInfoObject := geneticAnalysis.PersonMonogenicDiseaseInfo{}
|
|
|
|
dominantOrRecessive := diseaseObject.DominantOrRecessive
|
|
variantsList := diseaseObject.VariantsList
|
|
|
|
// We use this map to keep track of which RSIDs corresponds to each variant
|
|
// We also use it to have a map of all variants for the disease
|
|
// Map Structure: Variant Identifier -> []rsID
|
|
variantRSIDsMap := make(map[[3]byte][]int64)
|
|
|
|
// This map stores all rsIDs for this monogenic disease
|
|
// These are locations in the disease's gene which, if mutated, are known to cause the disease
|
|
// We use this map to avoid duplicate rsIDs, because one rsID can have multiple variants which belong to it
|
|
// We also store all alias rsIDs in this map
|
|
allRSIDsMap := make(map[int64]struct{})
|
|
|
|
for _, variantObject := range variantsList{
|
|
|
|
variantIdentifierHex := variantObject.VariantIdentifier
|
|
|
|
variantIdentifier, err := encoding.DecodeHexStringTo3ByteArray(variantIdentifierHex)
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
|
|
variantRSID := variantObject.VariantRSID
|
|
|
|
variantRSIDsList := []int64{variantRSID}
|
|
|
|
// We add aliases to variantRSIDsList
|
|
|
|
anyAliasesExist, rsidAliasesList, err := locusMetadata.GetRSIDAliases(variantRSID)
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
if (anyAliasesExist == true){
|
|
variantRSIDsList = append(variantRSIDsList, rsidAliasesList...)
|
|
}
|
|
|
|
variantRSIDsMap[variantIdentifier] = variantRSIDsList
|
|
|
|
for _, rsID := range variantRSIDsList{
|
|
allRSIDsMap[rsID] = struct{}{}
|
|
}
|
|
}
|
|
|
|
// Now we create a new map without any rsID aliases
|
|
// Each rsID in this map represents a unique locus on the genome
|
|
// Each rsID may have aliases, but they are not included in this map
|
|
allUniqueRSIDsMap := make(map[int64]struct{})
|
|
|
|
for rsID, _ := range allRSIDsMap{
|
|
|
|
anyAliasesExist, rsidAliasesList, err := locusMetadata.GetRSIDAliases(rsID)
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
if (anyAliasesExist == false){
|
|
allUniqueRSIDsMap[rsID] = struct{}{}
|
|
continue
|
|
}
|
|
|
|
// We see if we already added an alias of this rsID to the map
|
|
|
|
checkIfAliasAlreadyExists := func()bool{
|
|
|
|
for _, rsIDAlias := range rsidAliasesList{
|
|
_, exists := allUniqueRSIDsMap[rsIDAlias]
|
|
if (exists == true){
|
|
return true
|
|
}
|
|
}
|
|
return false
|
|
}
|
|
|
|
aliasAlreadyExists := checkIfAliasAlreadyExists()
|
|
if (aliasAlreadyExists == true){
|
|
// We already added this alias
|
|
continue
|
|
}
|
|
allUniqueRSIDsMap[rsID] = struct{}{}
|
|
}
|
|
|
|
// Map Structure: Genome Identifier -> PersonGenomeMonogenicDiseaseInfo
|
|
monogenicDiseaseInfoMap := make(map[[16]byte]geneticAnalysis.PersonGenomeMonogenicDiseaseInfo)
|
|
|
|
for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{
|
|
|
|
genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier
|
|
genomeMap := genomeWithMetadataObject.GenomeMap
|
|
|
|
// This stores all variant info for this genome
|
|
// Map Structure: Variant Identifier -> PersonGenomeMonogenicDiseaseVariantInfo
|
|
variantsInfoMap := make(map[[3]byte]geneticAnalysis.PersonGenomeMonogenicDiseaseVariantInfo)
|
|
|
|
for _, variantObject := range variantsList{
|
|
|
|
variantIdentifierHex := variantObject.VariantIdentifier
|
|
|
|
variantIdentifier, err := encoding.DecodeHexStringTo3ByteArray(variantIdentifierHex)
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
|
|
variantRSID := variantObject.VariantRSID
|
|
|
|
basePairValueFound, base1Value, base2Value, locusIsPhased, err := getGenomeLocusBasePair(genomeMap, variantRSID)
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
if (basePairValueFound == false){
|
|
|
|
// This genome does not contain info for this variant
|
|
// We skip it
|
|
continue
|
|
}
|
|
|
|
// This genome has at least 1 variant
|
|
|
|
variantDefectiveBase := variantObject.DefectiveBase
|
|
|
|
getBaseIsVariantMutationBool := func(inputBase string)bool{
|
|
|
|
if (inputBase == variantDefectiveBase){
|
|
return true
|
|
}
|
|
// Base could be mutated to a different unhealthy base
|
|
// That mutation could be a neutral/healthier change
|
|
// We only care about this specific variant
|
|
return false
|
|
}
|
|
|
|
base1IsDefective := getBaseIsVariantMutationBool(base1Value)
|
|
base2IsDefective := getBaseIsVariantMutationBool(base2Value)
|
|
|
|
newDiseaseVariantInfoObject := geneticAnalysis.PersonGenomeMonogenicDiseaseVariantInfo{
|
|
Base1HasVariant: base1IsDefective,
|
|
Base2HasVariant: base2IsDefective,
|
|
LocusIsPhased: locusIsPhased,
|
|
}
|
|
|
|
variantsInfoMap[variantIdentifier] = newDiseaseVariantInfoObject
|
|
|
|
//TODO: Add LocusIsPhased to readGeneticAnalysis package
|
|
}
|
|
|
|
// We are done adding variant information for the genome
|
|
// Now we determine probability that user will pass a disease variant to offspring, and if the user has the disease
|
|
|
|
numberOfVariantsTested := len(variantsInfoMap)
|
|
|
|
if (numberOfVariantsTested == 0){
|
|
// We don't know anything about this genome's disease risk for this disease
|
|
// We won't add any information to the map
|
|
continue
|
|
}
|
|
|
|
// This stores the number of loci that were tested
|
|
// Each locus can have multiple potential variants
|
|
numberOfLociTested := 0
|
|
|
|
// This stores the number of tested loci that are phased
|
|
// A higher number means that the results are more potentially more accurate
|
|
// It is only more accurate if multiple heterozygous variants on seperate loci exist.
|
|
numberOfPhasedLoci := 0
|
|
|
|
for rsID, _ := range allUniqueRSIDsMap{
|
|
|
|
locusValueExists, _, _, locusIsPhased, err := getGenomeLocusBasePair(genomeMap, rsID)
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
if (locusValueExists == false){
|
|
continue
|
|
}
|
|
|
|
numberOfLociTested += 1
|
|
|
|
if (locusIsPhased == true){
|
|
numberOfPhasedLoci += 1
|
|
}
|
|
}
|
|
|
|
// Outputs:
|
|
// -bool: Person has disease
|
|
// -float64: Probability Person will pass a defect (variant) to offspring (0-1)
|
|
// -error
|
|
getPersonDiseaseInfo := func()(bool, float64, error){
|
|
|
|
// These variables are used to count the number of defective variants that exist on each chromosome
|
|
numberOfVariants_Chromosome1 := 0
|
|
numberOfVariants_Chromosome2 := 0
|
|
numberOfVariants_UnknownChromosome := 0
|
|
|
|
// We use this map to keep track of how many mutations exist for each rsID
|
|
// This allows us to know if 2 different variant mutations exist for a single rsID
|
|
// For example, base1 is a different deleterious mutation than base2
|
|
// If this ever happens, we know that the user has the disease,
|
|
// because both copies of the gene locus are defective.
|
|
rsidMutationsMap := make(map[int64]int)
|
|
|
|
for variantIdentifier, variantInfoObject := range variantsInfoMap{
|
|
|
|
locusIsPhasedStatus := variantInfoObject.LocusIsPhased
|
|
|
|
base1HasVariant := variantInfoObject.Base1HasVariant
|
|
base2HasVariant := variantInfoObject.Base2HasVariant
|
|
|
|
if (base1HasVariant == false && base2HasVariant == false){
|
|
// Neither chromosome contains the variant mutation.
|
|
continue
|
|
}
|
|
|
|
if (base1HasVariant == true && base2HasVariant == true){
|
|
// Both chromosomes contain the same variant mutation.
|
|
// Person has the disease.
|
|
// Person will definitely pass disease variant to offspring.
|
|
return true, 1, nil
|
|
}
|
|
|
|
// We know that this variant exists on 1 of the bases, but not both.
|
|
|
|
variantRSIDsList, exists := variantRSIDsMap[variantIdentifier]
|
|
if (exists == false){
|
|
return false, 0, errors.New("variantRSIDsMap missing variantIdentifier.")
|
|
}
|
|
|
|
for _, rsID := range variantRSIDsList{
|
|
rsidMutationsMap[rsID] += 1
|
|
}
|
|
|
|
if (locusIsPhasedStatus == true){
|
|
|
|
if (base1HasVariant == true){
|
|
numberOfVariants_Chromosome1 += 1
|
|
}
|
|
if (base2HasVariant == true){
|
|
numberOfVariants_Chromosome2 += 1
|
|
}
|
|
} else {
|
|
|
|
if (base1HasVariant == true || base2HasVariant == true){
|
|
numberOfVariants_UnknownChromosome += 1
|
|
}
|
|
}
|
|
}
|
|
|
|
totalNumberOfVariants := numberOfVariants_Chromosome1 + numberOfVariants_Chromosome2 + numberOfVariants_UnknownChromosome
|
|
|
|
if (totalNumberOfVariants == 0){
|
|
// Person does not have any disease variants.
|
|
// They do not have the disease, and have no chance of passing a disease variant
|
|
return false, 0, nil
|
|
}
|
|
|
|
// Now we check to see if there are any loci which have 2 different variants, one for each base
|
|
|
|
for _, numberOfMutations := range rsidMutationsMap{
|
|
|
|
if (numberOfMutations >= 2){
|
|
// Person has 2 mutations on the same location
|
|
// They must have the disease, and will definitely pass a variant to their offspring
|
|
return true, 1, nil
|
|
}
|
|
}
|
|
|
|
// At this point, we know that there are no homozygous variant mutations
|
|
// All variant mutations are heterozygous, meaning the other chromosome strand's base is healthy
|
|
|
|
//Outputs:
|
|
// -bool: Person has disease
|
|
getPersonHasDiseaseBool := func()bool{
|
|
|
|
if (dominantOrRecessive == "Dominant"){
|
|
// Only 1 variant is needed for the person to have the disease
|
|
// We know they have at least 1 variant
|
|
return true
|
|
}
|
|
|
|
// dominantOrRecessive == "Recessive"
|
|
|
|
if (totalNumberOfVariants == 1){
|
|
// There is only 1 variant in total.
|
|
// This single variant cannot exist on both chromosomes.
|
|
// The person does not have the disease
|
|
return false
|
|
}
|
|
|
|
// We know that there are at least 2 variants
|
|
|
|
if (numberOfVariants_Chromosome1 >= 1 && numberOfVariants_Chromosome2 >= 1){
|
|
|
|
// We know there is at least 1 variant mutation on each chromosome
|
|
// Therefore, the person has the disease
|
|
return true
|
|
}
|
|
|
|
if (numberOfVariants_UnknownChromosome == 0){
|
|
|
|
// We know that variants do not exist on both chromosomes, only on 1.
|
|
// Thus, the person does not have the disease
|
|
return false
|
|
}
|
|
|
|
// We know there are at least 2 variants
|
|
// We know there is at least 1 variant whose phase is unknown
|
|
|
|
// If all mutations are on the same chromosome, the person does not have the disease.
|
|
// If at least 1 mutation exists on each chromosome, the person does have the disease.
|
|
// Either way, we don't know enough to say if the person has the disease.
|
|
// We will report that they do not, because their genome does not conclusively say that they do.
|
|
// This is why phased genomes are useful and provide a more accurate reading
|
|
// TODO: Explain this to the user in the GUI
|
|
// We must explain that unphased genomes will not detect disease sometimes
|
|
|
|
return false
|
|
}
|
|
|
|
personHasDiseaseBool := getPersonHasDiseaseBool()
|
|
|
|
// Output:
|
|
// -float64: Probability person will pass a disease variant to their offspring (0-1)
|
|
getPersonWillPassVariantProbability := func()float64{
|
|
|
|
if (totalNumberOfVariants == 1){
|
|
|
|
// There is only 1 variant on any chromosome
|
|
// The probability of the person passing a variant is 50%.
|
|
return 0.5
|
|
}
|
|
|
|
// We know that there are at least 2 variants
|
|
|
|
if (numberOfVariants_Chromosome1 >= 1 && numberOfVariants_Chromosome2 >= 1){
|
|
|
|
// We know there is at least 1 variant mutation on each chromosome
|
|
// Therefore, the person will definitely pass a variant
|
|
return 1
|
|
}
|
|
if (numberOfVariants_UnknownChromosome == 0){
|
|
|
|
// We know that variants do not exist on both chromosomes, only on 1.
|
|
// Thus, the person has a 50% probability of passing a variant
|
|
return 0.5
|
|
}
|
|
|
|
// We know all variants are heterozygous
|
|
|
|
// From Wikipeia:
|
|
// The human genome contains somewhere between 19,000 and 20,000 protein-coding genes.
|
|
// These genes contain an average of 10 introns and the average size of an intron is about 6 kb (6,000 base pairs)
|
|
// This means that the average size of a protein-coding gene is about 62 kb (62,000 base pairs)
|
|
|
|
// The probability of a recombination breakpoint occurring within the gene is very small
|
|
// If there is 1 breakpoint every 100 million locations, on average, and each gene is 62,000 base pairs long,
|
|
// then the probability of a breakpoint occurring within a gene is 62,000/100,000,000 = 0.00062 = .062%
|
|
// Thus, we disregard the risk of a breakpoint occurring within a gene
|
|
// I also read somewhere that breakpoints are less likely to occurr within genes, which makes this likelihood even smaller
|
|
|
|
// At this point, we know there at at least 2 variants
|
|
// We know that at least 1 of the variants has an unknown phase
|
|
// We don't know if all of the variants belong to the same chromosome
|
|
// If variants exist on both chromosomes, then the probability of passing a variant is 100%
|
|
// If all variants exist on the same chromosome, then the probability of passing a variant is 50%
|
|
// We know there is at least a 50% chance of passing a variant, and possibly higher
|
|
|
|
return 0.5
|
|
}
|
|
|
|
personWillPassVariantProbability := getPersonWillPassVariantProbability()
|
|
|
|
return personHasDiseaseBool, personWillPassVariantProbability, nil
|
|
}
|
|
|
|
personHasDisease, probabilityPersonWillPassAnyVariant, err := getPersonDiseaseInfo()
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
|
|
percentageProbabilityPersonWillPassADiseaseVariant := int(probabilityPersonWillPassAnyVariant * 100)
|
|
|
|
diseaseAnalysisObject := geneticAnalysis.PersonGenomeMonogenicDiseaseInfo{
|
|
PersonHasDisease: personHasDisease,
|
|
NumberOfVariantsTested: numberOfVariantsTested,
|
|
NumberOfLociTested: numberOfLociTested,
|
|
NumberOfPhasedLoci: numberOfPhasedLoci,
|
|
ProbabilityOfPassingADiseaseVariant: percentageProbabilityPersonWillPassADiseaseVariant,
|
|
VariantsInfoMap: variantsInfoMap,
|
|
}
|
|
|
|
monogenicDiseaseInfoMap[genomeIdentifier] = diseaseAnalysisObject
|
|
}
|
|
|
|
personMonogenicDiseaseInfoObject := geneticAnalysis.PersonMonogenicDiseaseInfo{
|
|
MonogenicDiseaseInfoMap: monogenicDiseaseInfoMap,
|
|
}
|
|
|
|
if (len(monogenicDiseaseInfoMap) <= 1){
|
|
// We do not need to check for conflicts, there is only <=1 genome with disease information
|
|
// Nothing left to do. Analysis is complete.
|
|
return personMonogenicDiseaseInfoObject, nil
|
|
}
|
|
|
|
// We check for conflicts
|
|
|
|
getConflictExistsBool := func()(bool, error){
|
|
|
|
firstItemReached := false
|
|
|
|
personHasDisease := false
|
|
probabilityOfPassingAVariant := 0
|
|
|
|
for _, currentGenomeDiseaseAnalysisObject := range monogenicDiseaseInfoMap{
|
|
|
|
currentGenomePersonHasDisease := currentGenomeDiseaseAnalysisObject.PersonHasDisease
|
|
currentGenomeProbabilityOfPassingAVariant := currentGenomeDiseaseAnalysisObject.ProbabilityOfPassingADiseaseVariant
|
|
|
|
if (firstItemReached == false){
|
|
personHasDisease = currentGenomePersonHasDisease
|
|
probabilityOfPassingAVariant = currentGenomeProbabilityOfPassingAVariant
|
|
firstItemReached = true
|
|
continue
|
|
}
|
|
|
|
if (currentGenomePersonHasDisease != personHasDisease){
|
|
return true, nil
|
|
}
|
|
if (currentGenomeProbabilityOfPassingAVariant != probabilityOfPassingAVariant){
|
|
return true, nil
|
|
}
|
|
}
|
|
|
|
// Now we test variants for conflicts
|
|
// We are only doing this to see if there are variants which one genome has and another doesn't
|
|
// For example, the analysis results say that you have a 50% chance of passing a variant for both genomes, but
|
|
// they have detected a different variant for each genome.
|
|
// This means that your real risk of passing a variant may actually be higher, and you are more likely to have the disease too
|
|
|
|
for variantIdentifier, _ := range variantRSIDsMap{
|
|
|
|
// Each variant base pair is either true/false, true/true, false/false, false/true
|
|
|
|
// Two different genomes have true/false and false/true, it will not count as a conflict
|
|
// If the locus is unphased, then there is no difference between true/false and false/true
|
|
// If the locus is phased, then this flip is only meaningful if it effects the probability of disease/passing a variant
|
|
// We already checked those probabilities for conflicts earlier
|
|
// Therefore, any flip is not considered a conflict
|
|
// We only care about conflicts where 1 genome says you have a variant and the other says you don't, or
|
|
// one says you have only 1 mutation and the other says you have 2 at that location
|
|
|
|
firstItemReached := false
|
|
|
|
base1HasVariant := false
|
|
base2HasVariant := false
|
|
|
|
for _, currentGenomeDiseaseAnalysisObject := range monogenicDiseaseInfoMap{
|
|
|
|
variantsInfoMap := currentGenomeDiseaseAnalysisObject.VariantsInfoMap
|
|
|
|
variantInfoObject, exists := variantsInfoMap[variantIdentifier]
|
|
if (exists == false){
|
|
if (firstItemReached == true){
|
|
// A previous genome has information for this variant, and the current one does not
|
|
return true, nil
|
|
}
|
|
continue
|
|
}
|
|
|
|
currentBase1HasVariant := variantInfoObject.Base1HasVariant
|
|
currentBase2HasVariant := variantInfoObject.Base2HasVariant
|
|
|
|
if (firstItemReached == false){
|
|
base1HasVariant = currentBase1HasVariant
|
|
base2HasVariant = currentBase2HasVariant
|
|
firstItemReached = true
|
|
continue
|
|
}
|
|
|
|
if (base1HasVariant == currentBase1HasVariant && base2HasVariant == currentBase2HasVariant){
|
|
// No conflict exists
|
|
continue
|
|
}
|
|
if (base1HasVariant == currentBase2HasVariant && base2HasVariant == currentBase1HasVariant){
|
|
// We don't count this as a conflict
|
|
continue
|
|
}
|
|
|
|
// A conflict exists
|
|
return true, nil
|
|
}
|
|
}
|
|
|
|
return false, nil
|
|
}
|
|
|
|
conflictExists, err := getConflictExistsBool()
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
|
|
personMonogenicDiseaseInfoObject.ConflictExists = conflictExists
|
|
|
|
return personMonogenicDiseaseInfoObject, nil
|
|
}
|
|
|
|
|
|
//Outputs:
|
|
// -geneticAnalysis.PersonPolygenicDiseaseInfo
|
|
// -error
|
|
func getPersonPolygenicDiseaseAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.GenomeWithMetadata, diseaseObject polygenicDiseases.PolygenicDisease)(geneticAnalysis.PersonPolygenicDiseaseInfo, error){
|
|
|
|
// We use this when returning errors
|
|
emptyDiseaseInfoObject := geneticAnalysis.PersonPolygenicDiseaseInfo{}
|
|
|
|
diseaseLociList := diseaseObject.LociList
|
|
|
|
// This map stores the polygenic disease for each of the person's genomes
|
|
// Map Structure: Genome Identifier -> PersonGenomePolygenicDiseaseInfo
|
|
personPolygenicDiseaseInfoMap := make(map[[16]byte]geneticAnalysis.PersonGenomePolygenicDiseaseInfo)
|
|
|
|
// We construct polygenic disease probability info for each genome
|
|
|
|
for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{
|
|
|
|
genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier
|
|
genomeMap := genomeWithMetadataObject.GenomeMap
|
|
|
|
// Map Structure: Locus Identifier -> PersonGenomePolygenicDiseaseLocusInfo
|
|
genomeLociInfoMap := make(map[[3]byte]geneticAnalysis.PersonGenomePolygenicDiseaseLocusInfo)
|
|
|
|
minimumPossibleRiskWeightSum := 0
|
|
maximumPossibleRiskWeightSum := 0
|
|
|
|
summedDiseaseRiskWeight := 0
|
|
|
|
for _, locusObject := range diseaseLociList{
|
|
|
|
locusIdentifierHex := locusObject.LocusIdentifier
|
|
|
|
locusIdentifier, err := encoding.DecodeHexStringTo3ByteArray(locusIdentifierHex)
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
|
|
locusRSID := locusObject.LocusRSID
|
|
locusRiskWeightsMap := locusObject.RiskWeightsMap
|
|
locusOddsRatiosMap := locusObject.OddsRatiosMap
|
|
locusMinimumWeight := locusObject.MinimumRiskWeight
|
|
locusMaximumWeight := locusObject.MaximumRiskWeight
|
|
|
|
basePairValueFound, locusBase1Value, locusBase2Value, _, err := getGenomeLocusBasePair(genomeMap, locusRSID)
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
if (basePairValueFound == false){
|
|
continue
|
|
}
|
|
|
|
//Outputs:
|
|
// -int: Genome disease locus risk weight
|
|
// -bool: Genome disease locus odds ratio known
|
|
// -float64: Genome disease locus odds ratio
|
|
// -error
|
|
getGenomeDiseaseLocusRiskInfo := func()(int, bool, float64, error){
|
|
|
|
locusBasePairJoined := locusBase1Value + ";" + locusBase2Value
|
|
|
|
riskWeight, exists := locusRiskWeightsMap[locusBasePairJoined]
|
|
if (exists == false){
|
|
// This is an unknown base combination
|
|
// We will treat it as a 0 risk weight
|
|
return 0, true, 1, nil
|
|
}
|
|
|
|
if (riskWeight == 0){
|
|
return 0, true, 1, nil
|
|
}
|
|
|
|
oddsRatio, exists := locusOddsRatiosMap[locusBasePairJoined]
|
|
if (exists == false){
|
|
return riskWeight, false, 0, nil
|
|
}
|
|
|
|
return riskWeight, true, oddsRatio, nil
|
|
}
|
|
|
|
locusRiskWeight, locusOddsRatioIsKnown, locusOddsRatio, err := getGenomeDiseaseLocusRiskInfo()
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
|
|
newLocusInfoObject := geneticAnalysis.PersonGenomePolygenicDiseaseLocusInfo{
|
|
LocusBase1: locusBase1Value,
|
|
LocusBase2: locusBase2Value,
|
|
RiskWeight: locusRiskWeight,
|
|
OddsRatioIsKnown: locusOddsRatioIsKnown,
|
|
}
|
|
|
|
if (locusOddsRatioIsKnown == true){
|
|
newLocusInfoObject.OddsRatio = locusOddsRatio
|
|
}
|
|
|
|
genomeLociInfoMap[locusIdentifier] = newLocusInfoObject
|
|
|
|
minimumPossibleRiskWeightSum += locusMinimumWeight
|
|
maximumPossibleRiskWeightSum += locusMaximumWeight
|
|
|
|
summedDiseaseRiskWeight += locusRiskWeight
|
|
}
|
|
|
|
numberOfLociTested := len(genomeLociInfoMap)
|
|
|
|
if (numberOfLociTested == 0){
|
|
// We have no information about this disease for this genome
|
|
continue
|
|
}
|
|
|
|
diseaseRiskScore, err := helpers.ScaleNumberProportionally(true, summedDiseaseRiskWeight, minimumPossibleRiskWeightSum, maximumPossibleRiskWeightSum, 0, 10)
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
|
|
newDiseaseInfoObject := geneticAnalysis.PersonGenomePolygenicDiseaseInfo{
|
|
NumberOfLociTested: numberOfLociTested,
|
|
RiskScore: diseaseRiskScore,
|
|
LociInfoMap: genomeLociInfoMap,
|
|
}
|
|
|
|
personPolygenicDiseaseInfoMap[genomeIdentifier] = newDiseaseInfoObject
|
|
}
|
|
|
|
newPersonPolygenicDiseaseInfoObject := geneticAnalysis.PersonPolygenicDiseaseInfo{
|
|
PolygenicDiseaseInfoMap: personPolygenicDiseaseInfoMap,
|
|
}
|
|
|
|
if (len(personPolygenicDiseaseInfoMap) <= 1){
|
|
// We do not need to check for conflicts, there is only <=1 genome with disease information
|
|
// Nothing left to do. Analysis is complete.
|
|
return newPersonPolygenicDiseaseInfoObject, nil
|
|
}
|
|
|
|
// We check for conflicts between the different genome's results
|
|
|
|
getConflictExistsBool := func()(bool, error){
|
|
|
|
// First we check to see if any of the genomes have different risk scores or NumberOfLociTested
|
|
|
|
genomeRiskScore := 0
|
|
genomeNumberOfLociTested := 0
|
|
|
|
firstItemReached := false
|
|
|
|
for _, personGenomeDiseaseInfoObject := range personPolygenicDiseaseInfoMap{
|
|
|
|
currentGenomeRiskScore := personGenomeDiseaseInfoObject.RiskScore
|
|
currentGenomeNumberOfLociTested := personGenomeDiseaseInfoObject.NumberOfLociTested
|
|
|
|
if (firstItemReached == false){
|
|
genomeRiskScore = currentGenomeRiskScore
|
|
genomeNumberOfLociTested = currentGenomeNumberOfLociTested
|
|
firstItemReached = true
|
|
continue
|
|
}
|
|
|
|
if (genomeRiskScore != currentGenomeRiskScore){
|
|
return true, nil
|
|
}
|
|
if (genomeNumberOfLociTested != currentGenomeNumberOfLociTested){
|
|
return true, nil
|
|
}
|
|
}
|
|
|
|
// Now we check for conflicts between the different locus values
|
|
// We consider a conflict any time the same locus has different weights/odds ratios
|
|
// We don't care if the loci have different base pair values, so long as those base pairs have the same risk weights/odds ratios
|
|
|
|
for _, locusObject := range diseaseLociList{
|
|
|
|
locusIdentifierHex := locusObject.LocusIdentifier
|
|
|
|
locusIdentifier, err := encoding.DecodeHexStringTo3ByteArray(locusIdentifierHex)
|
|
if (err != nil) { return false, err }
|
|
|
|
locusRiskWeight := 0
|
|
locusOddsRatio := float64(0)
|
|
|
|
firstItemReached := false
|
|
|
|
for _, personGenomeDiseaseInfoObject := range personPolygenicDiseaseInfoMap{
|
|
|
|
genomeLociInfoMap := personGenomeDiseaseInfoObject.LociInfoMap
|
|
|
|
genomeLocusObject, exists := genomeLociInfoMap[locusIdentifier]
|
|
if (exists == false){
|
|
if (firstItemReached == true){
|
|
// A previous genome has information for this locus, and the current one does not
|
|
return true, nil
|
|
}
|
|
continue
|
|
}
|
|
|
|
genomeLocusRiskWeight := genomeLocusObject.RiskWeight
|
|
genomeLocusOddsRatio := genomeLocusObject.OddsRatio
|
|
|
|
if (firstItemReached == false){
|
|
locusRiskWeight = genomeLocusRiskWeight
|
|
locusOddsRatio = genomeLocusOddsRatio
|
|
firstItemReached = true
|
|
continue
|
|
}
|
|
if (locusRiskWeight == genomeLocusRiskWeight && locusOddsRatio == genomeLocusOddsRatio){
|
|
// No conflict exists for this locus on the genomes we have already checked
|
|
continue
|
|
}
|
|
|
|
// Conflict exists
|
|
return true, nil
|
|
}
|
|
}
|
|
|
|
return false, nil
|
|
}
|
|
|
|
conflictExists, err := getConflictExistsBool()
|
|
if (err != nil) { return emptyDiseaseInfoObject, err }
|
|
|
|
newPersonPolygenicDiseaseInfoObject.ConflictExists = conflictExists
|
|
|
|
return newPersonPolygenicDiseaseInfoObject, nil
|
|
}
|
|
|
|
|
|
|
|
//Outputs:
|
|
// -geneticAnalysis.PersonTraitInfo: Trait analysis object
|
|
// -error
|
|
func getPersonTraitAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.GenomeWithMetadata, traitObject traits.Trait)(geneticAnalysis.PersonTraitInfo, 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)
|
|
|
|
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)
|
|
|
|
for _, locusRSID := range traitLociList{
|
|
|
|
locusBasePairKnown, locusBase1, locusBase2, locusIsPhased, err := getGenomeLocusBasePair(genomeMap, locusRSID)
|
|
if (err != nil) { return emptyPersonTraitInfo, err }
|
|
if (locusBasePairKnown == false){
|
|
continue
|
|
}
|
|
|
|
newLocusValue := locusValue.LocusValue{
|
|
LocusIsPhased: locusIsPhased,
|
|
Base1Value: locusBase1,
|
|
Base2Value: locusBase2,
|
|
}
|
|
|
|
genomeLocusValuesMap[locusRSID] = newLocusValue
|
|
}
|
|
|
|
// 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)
|
|
|
|
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
|
|
|
|
// Outputs:
|
|
// -bool: Genome passes rule is known
|
|
// -bool: Genome passes rule
|
|
// -error
|
|
getGenomePassesRuleBool := func()(bool, bool, error){
|
|
|
|
// We check to see if genome passes all rule loci
|
|
// We consider a rule Known if the genome either passes all loci, or fails to pass 1 locus
|
|
// We consider a rule Unknown if any loci are unknown, and all loci which are known pass the rule
|
|
|
|
anyLocusIsUnknown := false
|
|
|
|
for _, locusObject := range ruleLociList{
|
|
|
|
locusRSID := locusObject.LocusRSID
|
|
|
|
locusBasePairKnown, locusBase1, locusBase2, _, err := getGenomeLocusBasePair(genomeMap, locusRSID)
|
|
if (err != nil) { return false, false, err }
|
|
if (locusBasePairKnown == false){
|
|
anyLocusIsUnknown = true
|
|
continue
|
|
}
|
|
|
|
locusBasePairJoined := locusBase1 + ";" + locusBase2
|
|
|
|
locusBasePairsList := locusObject.BasePairsList
|
|
|
|
genomePassesRuleLocus := slices.Contains(locusBasePairsList, locusBasePairJoined)
|
|
if (genomePassesRuleLocus == false){
|
|
// The genome has failed to pass a single rule locus, thus, the rule is not passed
|
|
return true, false, nil
|
|
}
|
|
}
|
|
|
|
if (anyLocusIsUnknown == true){
|
|
// The rule is not passed, but it's status is unknown
|
|
// There were no rules which were known not to pass
|
|
return false, false, nil
|
|
}
|
|
|
|
// All rules were passed
|
|
|
|
return true, true, nil
|
|
}
|
|
|
|
genomePassesRuleIsKnown, genomePassesRule, err := getGenomePassesRuleBool()
|
|
if (err != nil) { return emptyPersonTraitInfo, 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
|
|
}
|
|
}
|
|
}
|
|
|
|
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{
|
|
TraitInfoMap: newPersonTraitInfoMap,
|
|
}
|
|
|
|
if (len(newPersonTraitInfoMap) <= 1){
|
|
// We do not need to check for conflicts, there is only <=1 genome with trait information
|
|
// Nothing left to do. Analysis is complete.
|
|
return newPersonTraitInfoObject, nil
|
|
}
|
|
|
|
// We check for conflicts
|
|
|
|
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
|
|
|
|
firstItemReached := false
|
|
|
|
outcomeScoresMap := make(map[string]int)
|
|
passesRulesMap := make(map[[3]byte]bool)
|
|
|
|
for _, genomeTraitInfoObject := range newPersonTraitInfoMap{
|
|
|
|
currentGenomeOutcomeScoresMap := genomeTraitInfoObject.OutcomeScoresMap
|
|
currentGenomePassesRulesMap := genomeTraitInfoObject.GenomePassesRulesMap
|
|
|
|
if (firstItemReached == false){
|
|
outcomeScoresMap = currentGenomeOutcomeScoresMap
|
|
passesRulesMap = currentGenomePassesRulesMap
|
|
firstItemReached = true
|
|
continue
|
|
}
|
|
|
|
areEqual := maps.Equal(currentGenomeOutcomeScoresMap, outcomeScoresMap)
|
|
if (areEqual == false){
|
|
// A conflict exists
|
|
return true, nil
|
|
}
|
|
areEqual = maps.Equal(currentGenomePassesRulesMap, passesRulesMap)
|
|
if (areEqual == false){
|
|
// A conflict exists
|
|
return true, nil
|
|
}
|
|
}
|
|
|
|
return false, nil
|
|
}
|
|
|
|
conflictExists, err := getConflictExistsBool()
|
|
if (err != nil) { return emptyPersonTraitInfo, err }
|
|
|
|
newPersonTraitInfoObject.ConflictExists = conflictExists
|
|
|
|
return newPersonTraitInfoObject, nil
|
|
}
|
|
|
|
|