// createGeneticAnalysis provides functions to create a genetic analysis
// These are performed on one or more genome files.
// They produce 3 kinds of results: Monogenic Diseases, Polygenic Diseases and Traits
// They can be performed on a Person or a Couple
// Couple analyses provide an analysis of the prospective offspring of the couple

package createGeneticAnalysis

// TODO: Some of the probabilities produced by this package are wrong
// In this package, we are assuming that genetic recombination (the formation of the genetic sequences for the sperm/eggs) happens randomly for each allele locus
// In reality, the recombination break points occur less often, and larger portions of each chromosome remain intact.
// This effects the estimates and probabilities for all of the generated analyses
// In particular, the probability of passing a defective gene does not increase as much as this package currently
//		estimates that it does, in the case of multiple defects existing in the same gene.
// Also, based on my research, I believe that recombination break points are less likely to occur within genes, meaning they are more likely to occur at the gene boundaries (codons)
// We need to remedy this problem and fix this package
// Research gene linkage and recombination to understand more.
// 
// Fixing this problem may require us to only allow will-pass-a-variant probabilities to be calculated from phased loci.
// The phase of a loci becomes much more important in determining the will-pass-a-variant probability
// Having multiple variants within a gene might not increase the probability of passing a variant, assuming all of those variants were on the same chromosome
// Thus, we need phased loci to determine an accurate will-pass-a-variant probability
// We will still be able to determine will-pass-a-variant probabilities for users who only have 1 variant on 1 base,
//		regardless of if their loci phase is known or not. That probability is 50%.



// TODO: We want to eventually use neural nets for both trait and polygenic disease analysis
// These will be trained on a set of genomes and will output a probability analysis for each trait/disease
// This is only possible once we get access to the necessary training data
//
// This is how offspring trait prediction could work with the neural net model:
//		Both users will share all relevant SNPS base pairs that determine the trait on their profile.
//		Each location has 4 possible outcomes, so for 1000 SNPs, there are 4^1000 possible offspring outcomes for a given couple. (this
//			is actually too high because recombination break points do not occur at each locus, see genetic linkage)
//		This is too many options for us to check all of them.
//		Seekia will create 100 offspring that would be produced from both users, and run each offspring through the neural net.
//		Each offspring would be different. The allele from each parent for each SNP would be randomly chosen.
// 		The user can choose how many prospective offspring to create in the settings.
//		More offspring will take longer, but will yield a more accurate trait probability.
//		Seekia will show the the average trait result and a chart showing the trait results for all created offspring.


// TODO: We should not add any passing-a-variant probabilities that are dependent on an unknown phase to user profiles
// For example, if the phase for any mutated bases are unknown, and this unknown phase effects the probability of 
//		the user passing a variant, that probability should not be shared on the user's profile.
//		Seekia currently shares these probabilities on user profiles.
//		Only probabilities which are fully known should be shared. Otherwise, the user is sharing
//		information that is not fully accurate but is instead speculative.
//
//		We must add this warning into the GUI for a user and couple genetic analyses too.
//		Basically, we need to make it clear that some probabilities are based completely on random genetic chance, and others
//		are based on our limited understanding of the user's genome (due to unphased data).


// TODO: Add the ability to weight different genome files based on their reliability.
//	Some files are much more accurate because they record each location many times.


import "seekia/resources/geneticReferences/locusMetadata"
import "seekia/resources/geneticReferences/monogenicDiseases"
import "seekia/resources/geneticReferences/polygenicDiseases"
import "seekia/resources/geneticReferences/traits"

import "seekia/internal/genetics/locusValue"
import "seekia/internal/genetics/prepareRawGenomes"
import "seekia/internal/helpers"

import "errors"
import "math"
import "encoding/json"
import "strings"
import "slices"


func verifyBasePair(inputBasePair string)bool{

	base1, base2, delimiterFound := strings.Cut(inputBasePair, ";")
	if (delimiterFound == false){
		return false
	}

	// I = Insertion
	// D = Deletion

	validBasesList := []string{"C", "A", "T", "G", "I", "D"}

	baseIsValid := slices.Contains(validBasesList, base1)
	if (baseIsValid == false){
		return false
	}

	baseIsValid = slices.Contains(validBasesList, base2)
	if (baseIsValid == false){
		return false
	}

	return true
}

//Inputs:
//	-map[string]string: Genome Identifier -> Genome Raw data string
//Outputs:
//	-bool: Process completed (it was not stopped manually before completion)
//	-string: New Genetic analysis string
//	-error
func CreatePersonGeneticAnalysis(genomesList []prepareRawGenomes.RawGenomeWithMetadata, updatePercentageCompleteFunction func(int)error, checkIfProcessIsStopped func()bool)(bool, string, error){

	prepareRawGenomesUpdatePercentageCompleteFunction := func(newPercentage int)error{

		newPercentageCompletion, err := helpers.ScaleNumberProportionally(true, newPercentage, 0, 100, 0, 50)
		if (err != nil){ return err }

		err = updatePercentageCompleteFunction(newPercentageCompletion)
		if (err != nil) { return err }

		return nil
	}

	genomesWithMetadataList, allRawGenomeIdentifiersList, multipleGenomesExist, onlyExcludeConflictsGenomeIdentifier, onlyIncludeSharedGenomeIdentifier, err := prepareRawGenomes.GetGenomesWithMetadataListFromRawGenomesList(genomesList, prepareRawGenomesUpdatePercentageCompleteFunction)
	if (err != nil) { return false, "", err }

	combinedGenomesExistString := helpers.ConvertBoolToYesOrNoString(multipleGenomesExist)

	metadataItem := map[string]string{
		"ItemType": "Metadata",
		"AnalysisVersion": "1",
		"AnalysisType": "Person",
		"CombinedGenomesExist": combinedGenomesExistString,
	}

	if (multipleGenomesExist == true){

		metadataItem["OnlyExcludeConflictsGenomeIdentifier"] = onlyExcludeConflictsGenomeIdentifier
		metadataItem["OnlyIncludeSharedGenomeIdentifier"] = onlyIncludeSharedGenomeIdentifier

		allRawGenomeIdentifiersListString := strings.Join(allRawGenomeIdentifiersList, "+")
		metadataItem["AllRawGenomeIdentifiersList"] = allRawGenomeIdentifiersListString

	} else {

		genomeIdentifier := allRawGenomeIdentifiersList[0]

		metadataItem["GenomeIdentifier"] = genomeIdentifier
	}

	processIsStopped := checkIfProcessIsStopped()
	if (processIsStopped == true){
		return false, "", nil
	}

	geneticAnalysisMapList := []map[string]string{metadataItem}

	monogenicDiseasesList, err := monogenicDiseases.GetMonogenicDiseaseObjectsList()
	if (err != nil) { return false, "", err }

	for _, monogenicDiseaseObject := range monogenicDiseasesList{

		diseaseName := monogenicDiseaseObject.DiseaseName

		diseaseAnalysisMap, variantsMapList, err := getMonogenicDiseaseAnalysis(genomesWithMetadataList, monogenicDiseaseObject)
		if (err != nil) { return false, "", err }

		diseaseAnalysisMap["ItemType"] = "MonogenicDisease"
		diseaseAnalysisMap["DiseaseName"] = diseaseName

		geneticAnalysisMapList = append(geneticAnalysisMapList, diseaseAnalysisMap)
		geneticAnalysisMapList = append(geneticAnalysisMapList, variantsMapList...)
	}

	polygenicDiseaseObjectsList, err := polygenicDiseases.GetPolygenicDiseaseObjectsList()
	if (err != nil) { return false, "", err }

	for _, diseaseObject := range polygenicDiseaseObjectsList{

		diseaseAnalysisMap, diseaseLociMapList, err := getPolygenicDiseaseAnalysis(genomesWithMetadataList, diseaseObject)
		if (err != nil) { return false, "", err }

		diseaseName := diseaseObject.DiseaseName

		diseaseAnalysisMap["ItemType"] = "PolygenicDisease"
		diseaseAnalysisMap["DiseaseName"] = diseaseName

		geneticAnalysisMapList = append(geneticAnalysisMapList, diseaseAnalysisMap)
		geneticAnalysisMapList = append(geneticAnalysisMapList, diseaseLociMapList...)
	}

	traitObjectsList, err := traits.GetTraitObjectsList()
	if (err != nil) { return false, "", err }

	for _, traitObject := range traitObjectsList{

		traitAnalysisMap, traitRulesMapList, err := getTraitAnalysis(genomesWithMetadataList, traitObject)
		if (err != nil) { return false, "", err }

		traitName := traitObject.TraitName

		traitAnalysisMap["ItemType"] = "Trait"
		traitAnalysisMap["TraitName"] = traitName

		geneticAnalysisMapList = append(geneticAnalysisMapList, traitAnalysisMap)
		geneticAnalysisMapList = append(geneticAnalysisMapList, traitRulesMapList...)
	}

	analysisBytes, err := json.MarshalIndent(geneticAnalysisMapList, "", "\t")
	if (err != nil) { return false, "", err }

	analysisString := string(analysisBytes)

	return true, analysisString, nil
}

//Outputs:
//	-bool: Process completed (was not manually stopped mid-way)
//	-string: Couple genetic analysis string
//	-error
func CreateCoupleGeneticAnalysis(personAGenomesList []prepareRawGenomes.RawGenomeWithMetadata, personBGenomesList []prepareRawGenomes.RawGenomeWithMetadata, updatePercentageCompleteFunction func(int)error, checkIfProcessIsStopped func()bool)(bool, string, error){

	personAPrepareRawGenomesUpdatePercentageCompleteFunction := func(newPercentage int)error{

		newPercentageCompletion, err := helpers.ScaleNumberProportionally(true, newPercentage, 0, 100, 0, 25)
		if (err != nil){ return err }

		err = updatePercentageCompleteFunction(newPercentageCompletion)
		if (err != nil) { return err }

		return nil
	}

	personAGenomesWithMetadataList, allPersonARawGenomeIdentifiersList, personAHasMultipleGenomes, personAOnlyExcludeConflictsGenomeIdentifier, personAOnlyIncludeSharedGenomeIdentifier, err := prepareRawGenomes.GetGenomesWithMetadataListFromRawGenomesList(personAGenomesList, personAPrepareRawGenomesUpdatePercentageCompleteFunction)
	if (err != nil) { return false, "", err }

	processIsStopped := checkIfProcessIsStopped()
	if (processIsStopped == true){
		return false, "", nil
	}

	personBPrepareRawGenomesUpdatePercentageCompleteFunction := func(newPercentage int)error{

		newPercentageCompletion, err := helpers.ScaleNumberProportionally(true, newPercentage, 0, 100, 25, 50)
		if (err != nil){ return err }

		err = updatePercentageCompleteFunction(newPercentageCompletion)
		if (err != nil) { return err }

		return nil
	}

	personBGenomesWithMetadataList, allPersonBRawGenomeIdentifiersList, personBHasMultipleGenomes, personBOnlyExcludeConflictsGenomeIdentifier, personBOnlyIncludeSharedGenomeIdentifier, err := prepareRawGenomes.GetGenomesWithMetadataListFromRawGenomesList(personBGenomesList, personBPrepareRawGenomesUpdatePercentageCompleteFunction)
	if (err != nil) { return false, "", err }

	processIsStopped = checkIfProcessIsStopped()
	if (processIsStopped == true){
		return false, "", nil
	}

	// The analysis will analyze either 1 or 2 genome pairs
	// The gui will display the results from each pair
	//Outputs:
	//	-string: Pair 1 Person A Genome Identifier
	//	-string: Pair 1 Person B Genome Identifier
	//	-bool: Second pair exists
	//	-string: Pair 2 Person A Genome Identifier
	//	-string: Pair 2 Person B Genome Identifier
	//	-error
	getGenomePairsToAnalyze := func()(string, string, bool, string, string, error){

		if (personAHasMultipleGenomes == true && personBHasMultipleGenomes == true){

			return personAOnlyExcludeConflictsGenomeIdentifier, personBOnlyExcludeConflictsGenomeIdentifier, true, personAOnlyIncludeSharedGenomeIdentifier, personBOnlyIncludeSharedGenomeIdentifier, nil
		}
		if (personAHasMultipleGenomes == true && personBHasMultipleGenomes == false){

			personBGenomeIdentifier := allPersonBRawGenomeIdentifiersList[0]

			return personAOnlyExcludeConflictsGenomeIdentifier, personBGenomeIdentifier, true, personAOnlyIncludeSharedGenomeIdentifier, personBGenomeIdentifier, nil
		}
		if (personAHasMultipleGenomes == false && personBHasMultipleGenomes == true){

			personAGenomeIdentifier := allPersonARawGenomeIdentifiersList[0]

			return personAGenomeIdentifier, personBOnlyExcludeConflictsGenomeIdentifier, true, personAGenomeIdentifier, personBOnlyIncludeSharedGenomeIdentifier, nil
		}

		//personAHasMultipleGenomes == false && personBHasMultipleGenomes == false

		personAGenomeIdentifier := allPersonARawGenomeIdentifiersList[0]
		personBGenomeIdentifier := allPersonBRawGenomeIdentifiersList[0]

		return personAGenomeIdentifier, personBGenomeIdentifier, false, "", "", nil
	}

	pair1PersonAGenomeIdentifier, pair1PersonBGenomeIdentifier, genomePair2Exists, pair2PersonAGenomeIdentifier, pair2PersonBGenomeIdentifier, err := getGenomePairsToAnalyze()
	if (err != nil){ return false, "", err }

	personAHasMultipleGenomesString := helpers.ConvertBoolToYesOrNoString(personAHasMultipleGenomes)
	personBHasMultipleGenomesString := helpers.ConvertBoolToYesOrNoString(personBHasMultipleGenomes)

	secondPairExistsString := helpers.ConvertBoolToYesOrNoString(genomePair2Exists)

	metadataItem := map[string]string{
		"ItemType": "Metadata",
		"AnalysisVersion": "1",
		"AnalysisType": "Couple",
		"PersonAHasMultipleGenomes": personAHasMultipleGenomesString,
		"PersonBHasMultipleGenomes": personBHasMultipleGenomesString,
		"Pair1PersonAGenomeIdentifier": pair1PersonAGenomeIdentifier,
		"Pair1PersonBGenomeIdentifier": pair1PersonBGenomeIdentifier,
		"SecondPairExists": secondPairExistsString,
	}

	if (genomePair2Exists == true){

		// At least 1 of the people have multiple genomes

		metadataItem["Pair2PersonAGenomeIdentifier"] = pair2PersonAGenomeIdentifier
		metadataItem["Pair2PersonBGenomeIdentifier"] = pair2PersonBGenomeIdentifier

		if (personAHasMultipleGenomes == true){
			metadataItem["PersonAOnlyExcludeConflictsGenomeIdentifier"] = personAOnlyExcludeConflictsGenomeIdentifier
			metadataItem["PersonAOnlyIncludeSharedGenomeIdentifier"] = personAOnlyIncludeSharedGenomeIdentifier
		}

		if (personBHasMultipleGenomes == true){
			metadataItem["PersonBOnlyExcludeConflictsGenomeIdentifier"] = personBOnlyExcludeConflictsGenomeIdentifier
			metadataItem["PersonBOnlyIncludeSharedGenomeIdentifier"] = personBOnlyIncludeSharedGenomeIdentifier
		}
	}

	newAnalysisMapList := []map[string]string{metadataItem}

	//First we add monogenic disease probabilities

	monogenicDiseasesList, err := monogenicDiseases.GetMonogenicDiseaseObjectsList()
	if (err != nil) { return false, "", err }

	for _, diseaseObject := range monogenicDiseasesList{

		diseaseName := diseaseObject.DiseaseName
		variantsList := diseaseObject.VariantsList
		diseaseIsDominantOrRecessive := diseaseObject.DominantOrRecessive

		offspringDiseaseMap := map[string]string{
			"ItemType": "MonogenicDisease",
			"DiseaseName": diseaseName,
		}

		personADiseaseAnalysisMap, personAVariantsMapList, err := getMonogenicDiseaseAnalysis(personAGenomesWithMetadataList, diseaseObject)
		if (err != nil) { return false, "", err }

		personBDiseaseAnalysisMap, personBVariantsMapList, err := getMonogenicDiseaseAnalysis(personBGenomesWithMetadataList, diseaseObject)
		if (err != nil) { return false, "", err }

		// This will calculate the probability of monogenic disease for the offspring from the two specified genomes
		// It then adds the pair entry to the offspringDiseaseMap
		addPairProbabilitiesToDiseaseMap := func(personAGenomeIdentifier string, personBGenomeIdentifier string)error{

			//Outputs:
			//	-bool: Probability is known
			//	-int: Probability of passing a disease variant (value between 0 and 100)
			//	-int: Number of variants tested
			//	-error
			getPersonWillPassDiseaseVariantProbability := func(personDiseaseAnalysisMap map[string]string, genomeIdentifier string)(bool, int, int, error){

				probabilityMapKey := genomeIdentifier + "_ProbabilityOfPassingADiseaseVariant"

				genomeDiseasePercentageProbability, exists := personDiseaseAnalysisMap[probabilityMapKey]
				if (exists == false) {
					return false, 0, 0, errors.New("Malformed person analysis map list: Missing probability of passing a variant value")
				}
				if (genomeDiseasePercentageProbability == "Unknown"){
					return false, 0, 0, nil
				}

				genomeDiseaseProbabilityInt, err := helpers.ConvertStringToInt(genomeDiseasePercentageProbability)
				if (err != nil) {
					return false, 0, 0, errors.New("Malformed person analysis map list: Invalid probability of passing a variant value: " + genomeDiseasePercentageProbability)
				}

				numberOfTestedVariantsString, exists := personDiseaseAnalysisMap[genomeIdentifier + "_NumberOfVariantsTested"]
				if (exists == false){
					return false, 0, 0, errors.New("Malformed person analysis map list: Probabilities map missing _NumberOfVariantsTested")
				}

				numberOfTestedVariants, err := helpers.ConvertStringToInt(numberOfTestedVariantsString)
				if (err != nil){
					return false, 0, 0, errors.New("Malformed person analysis map list: Contains invalid _NumberOfVariantsTested")
				}

				return true, genomeDiseaseProbabilityInt, numberOfTestedVariants, nil
			}

			personAProbabilityIsKnown, personAWillPassVariantProbability, personANumberOfVariantsTested, err := getPersonWillPassDiseaseVariantProbability(personADiseaseAnalysisMap, personAGenomeIdentifier)
			if (err != nil) { return err }

			personBProbabilityIsKnown, personBWillPassVariantProbability, personBNumberOfVariantsTested, err := getPersonWillPassDiseaseVariantProbability(personBDiseaseAnalysisMap, personBGenomeIdentifier)
			if (err != nil) { return err }

			personANumberOfVariantsTestedString := helpers.ConvertIntToString(personANumberOfVariantsTested)
			personBNumberOfVariantsTestedString := helpers.ConvertIntToString(personBNumberOfVariantsTested)

			offspringDiseaseMap[personAGenomeIdentifier + "_NumberOfVariantsTested"] = personANumberOfVariantsTestedString
			offspringDiseaseMap[personBGenomeIdentifier + "_NumberOfVariantsTested"] = personBNumberOfVariantsTestedString

			genomePairIdentifier := personAGenomeIdentifier + "+" + personBGenomeIdentifier

			if (personAProbabilityIsKnown == false || personBProbabilityIsKnown == false){

				offspringDiseaseMap[genomePairIdentifier + "_ProbabilityOffspringHasDisease"] = "Unknown"
				offspringDiseaseMap[genomePairIdentifier + "_ProbabilityOffspringHasVariant"] = "Unknown"

				return nil
			}

			percentageProbabilityOffspringHasDisease, percentageProbabilityOffspringHasVariant, err := GetOffspringMonogenicDiseaseProbabilities(diseaseIsDominantOrRecessive, personAWillPassVariantProbability, personBWillPassVariantProbability)
			if (err != nil) { return err }

			probabilityOffspringHasDiseaseString := helpers.ConvertIntToString(percentageProbabilityOffspringHasDisease)
			probabilityOffspringHasVariantString := helpers.ConvertIntToString(percentageProbabilityOffspringHasVariant)

			offspringDiseaseMap[genomePairIdentifier + "_ProbabilityOffspringHasDisease"] = probabilityOffspringHasDiseaseString
			offspringDiseaseMap[genomePairIdentifier + "_ProbabilityOffspringHasVariant"] = probabilityOffspringHasVariantString

			return nil
		}

		err = addPairProbabilitiesToDiseaseMap(pair1PersonAGenomeIdentifier, pair1PersonBGenomeIdentifier)
		if (err != nil) { return false, "", err }

		if (genomePair2Exists == true){

			err := addPairProbabilitiesToDiseaseMap(pair2PersonAGenomeIdentifier, pair2PersonBGenomeIdentifier)
			if (err != nil) { return false, "", err }
		}

		// Now we calculate the probabilities for individual variants
		// We add a map for each variant

		offspringVariantsMapList := make([]map[string]string, 0, len(variantsList))

		for _, variantObject := range variantsList{

			variantIdentifier := variantObject.VariantIdentifier

			offspringVariantMap := map[string]string{
				"ItemType": "MonogenicDiseaseVariant",
				"VariantIdentifier": variantIdentifier,
				"DiseaseName": diseaseName,
			}

			addPairProbabilitiesToVariantMap := func(personAGenomeIdentifier string, personBGenomeIdentifier string)error{

				genomePairIdentifier := personAGenomeIdentifier + "+" + personBGenomeIdentifier

				//Outputs:
				//	-bool: Probability is known
				//	-float64: Probability that person will pass variant to offspring (between 0 and 1)
				//	-error
				getPersonWillPassVariantProbability := func(personVariantsMapList []map[string]string, personGenomeIdentifier string)(bool, float64, error){

					for _, personVariantMap := range personVariantsMapList{

						itemType, exists := personVariantMap["ItemType"]
						if (exists == false){
							return false, 0, errors.New("PersonVariantsMapList missing ItemType")
						}
						if (itemType != "MonogenicDiseaseVariant"){
							return false, 0, errors.New("Person variant map is malformed: Contains non-MonogenicDiseaseVariant itemType: " + itemType)
						}

						currentVariantIdentifier, exists := personVariantMap["VariantIdentifier"]
						if (exists == false){
							return false, 0, errors.New("Person variant map is malformed: Missing VariantIdentifier")
						}
						if (currentVariantIdentifier != variantIdentifier){
							continue
						}

						personHasVariantInfo, exists := personVariantMap[personGenomeIdentifier + "_HasVariant"]
						if (exists == false){
							return false, 0, errors.New("Person variant map is malformed: missing person genome _HasVariant value.")
						}

						if (personHasVariantInfo == "Unknown"){
							return false, 0, nil
						}
						if (personHasVariantInfo == "Yes;Yes"){
							return true, 1, nil
						}
						if (personHasVariantInfo == "Yes;No" || personHasVariantInfo == "No;Yes"){
							return true, 0.5, nil
						}
						if (personHasVariantInfo == "No;No"){
							return true, 0, nil
						}
						return false, 0, errors.New("Person variant map is malformed: Contains invalid variant info: " + personHasVariantInfo)
					}

					return false, 0, errors.New("Cannot find disease variant in personVariantsMapList: " + variantIdentifier)
				}

				// Outputs:
				//	-bool: Probabilities are known
				//	-int: Lower bound Percentage Probability that offspring will have 0 mutations
				//	-int: Upper bound Percentage Probability that offspring will have 0 mutations
				//	-int: Lower bound Percentage Probability that offspring will have 1 mutation
				//	-int: Upper bound Percentage Probability that offspring will have 1 mutation
				//	-int: Lower bound Percentage Probability that offspring will have 2 mutations
				//	-int: Upper bound Percentage Probability that offspring will have 2 mutations
				//	-error
				getOffspringVariantProbabilities := func()(bool, int, int, int, int, int, int, error){

					//Outputs:
					//	-int: Percentage Probability of 0 mutations
					//	-int: Percentage Probability of 1 mutation
					//	-int: Percentage Probability of 2 mutations
					//	-error
					getOffspringProbabilities := func(personAWillPassVariantProbability float64, personBWillPassVariantProbability float64)(int, int, int, error){
						// This is the probability that neither will pass variant
						// P = P(!A) * P(!B)
						probabilityOf0Mutations := (1 - personAWillPassVariantProbability) * (1 - personBWillPassVariantProbability)

						// This is the probability that either will pass variant, but not both
						// P(A XOR B) = P(A) + P(B) - (2 * P(A and B))
						probabilityOf1Mutation := personAWillPassVariantProbability + personBWillPassVariantProbability - (2 * personAWillPassVariantProbability * personBWillPassVariantProbability)

						// This is the probability that both will pass variant
						// P(A and B) = P(A) * P(B)
						probabilityOf2Mutations := personAWillPassVariantProbability * personBWillPassVariantProbability

						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
					}

					personAProbabilityIsKnown, personAWillPassVariantProbability, err := getPersonWillPassVariantProbability(personAVariantsMapList, personAGenomeIdentifier)
					if (err != nil) { return false, 0, 0, 0, 0, 0, 0, err }

					personBProbabilityIsKnown, personBWillPassVariantProbability, err := getPersonWillPassVariantProbability(personBVariantsMapList, personBGenomeIdentifier)
					if (err != nil) { return false,  0, 0, 0, 0, 0, 0, err }

					if (personAProbabilityIsKnown == false && personBProbabilityIsKnown == false){
						return false, 0, 0, 0, 0, 0, 0, nil
					}

					if (personAProbabilityIsKnown == true && personBProbabilityIsKnown == false){

						bestCasePersonBWillPassVariantProbability := float64(0)
						worstCasePersonBWillPassVariantProbability := float64(1)

						bestCase0MutationsProbability, bestCase1MutationProbability, bestCase2MutationsProbability, err := getOffspringProbabilities(personAWillPassVariantProbability, bestCasePersonBWillPassVariantProbability)
						if (err != nil) { return false, 0, 0, 0, 0, 0, 0, err }

						worstCase0MutationsProbability, worstCase1MutationProbability, worstCase2MutationsProbability, err := getOffspringProbabilities(personAWillPassVariantProbability, worstCasePersonBWillPassVariantProbability)
						if (err != nil) { return false, 0, 0, 0, 0, 0, 0, err }

						lowerBound1MutationProbability := min(bestCase1MutationProbability, worstCase1MutationProbability)
						upperBound1MutationProbability := max(bestCase1MutationProbability, worstCase1MutationProbability)

						return true, worstCase0MutationsProbability, bestCase0MutationsProbability, lowerBound1MutationProbability, upperBound1MutationProbability, bestCase2MutationsProbability, worstCase2MutationsProbability, nil
					}

					if (personAProbabilityIsKnown == false && personBProbabilityIsKnown == true){

						bestCasePersonAWillPassVariantProbability := float64(0)
						worstCasePersonAWillPassVariantProbability := float64(1)

						bestCase0MutationsProbability, bestCase1MutationProbability, bestCase2MutationsProbability, err := getOffspringProbabilities(bestCasePersonAWillPassVariantProbability, personBWillPassVariantProbability)
						if (err != nil) { return false, 0, 0, 0, 0, 0, 0, err }

						worstCase0MutationsProbability, worstCase1MutationProbability, worstCase2MutationsProbability, err := getOffspringProbabilities(worstCasePersonAWillPassVariantProbability, personBWillPassVariantProbability)
						if (err != nil) { return false, 0, 0, 0, 0, 0, 0, err }

						lowerBound1MutationProbability := min(bestCase1MutationProbability, worstCase1MutationProbability)
						upperBound1MutationProbability := max(bestCase1MutationProbability, worstCase1MutationProbability)

						return true, worstCase0MutationsProbability, bestCase0MutationsProbability, lowerBound1MutationProbability, upperBound1MutationProbability, bestCase2MutationsProbability, worstCase2MutationsProbability, nil
					}

					offspring0MutationsProbability, offspring1MutationProbability, offspring2MutationsProbability, err := getOffspringProbabilities(personAWillPassVariantProbability, personBWillPassVariantProbability)
					if (err != nil) { return false, 0, 0, 0, 0, 0, 0, err }

					return true, offspring0MutationsProbability, offspring0MutationsProbability, offspring1MutationProbability, offspring1MutationProbability, offspring2MutationsProbability, offspring2MutationsProbability, nil
				}

				probabilitiesKnown, probabilityOf0MutationsLowerBound, probabilityOf0MutationsUpperBound, probabilityOf1MutationLowerBound, probabilityOf1MutationUpperBound, probabilityOf2MutationsLowerBound, probabilityOf2MutationsUpperBound, err := getOffspringVariantProbabilities()
				if (err != nil) { return err }

				if (probabilitiesKnown == false){
					offspringVariantMap[genomePairIdentifier + "_ProbabilityOf0MutationsLowerBound"] = "Unknown"
					offspringVariantMap[genomePairIdentifier + "_ProbabilityOf0MutationsUpperBound"] = "Unknown"
					offspringVariantMap[genomePairIdentifier + "_ProbabilityOf1MutationLowerBound"] = "Unknown"
					offspringVariantMap[genomePairIdentifier + "_ProbabilityOf1MutationUpperBound"] = "Unknown"
					offspringVariantMap[genomePairIdentifier + "_ProbabilityOf2MutationsLowerBound"] = "Unknown"
					offspringVariantMap[genomePairIdentifier + "_ProbabilityOf2MutationsUpperBound"] = "Unknown"

					return nil
				}

				probabilityOf0MutationsLowerBoundString := helpers.ConvertIntToString(probabilityOf0MutationsLowerBound)
				probabilityOf0MutationsUpperBoundString := helpers.ConvertIntToString(probabilityOf0MutationsUpperBound)
				probabilityOf1MutationLowerBoundString := helpers.ConvertIntToString(probabilityOf1MutationLowerBound)
				probabilityOf1MutationUpperBoundString := helpers.ConvertIntToString(probabilityOf1MutationUpperBound)
				probabilityOf2MutationsLowerBoundString := helpers.ConvertIntToString(probabilityOf2MutationsLowerBound)
				probabilityOf2MutationsUpperBoundString := helpers.ConvertIntToString(probabilityOf2MutationsUpperBound)
	
				offspringVariantMap[genomePairIdentifier + "_ProbabilityOf0MutationsLowerBound"] = probabilityOf0MutationsLowerBoundString
				offspringVariantMap[genomePairIdentifier + "_ProbabilityOf0MutationsUpperBound"] = probabilityOf0MutationsUpperBoundString
				offspringVariantMap[genomePairIdentifier + "_ProbabilityOf1MutationLowerBound"] = probabilityOf1MutationLowerBoundString
				offspringVariantMap[genomePairIdentifier + "_ProbabilityOf1MutationUpperBound"] = probabilityOf1MutationUpperBoundString
				offspringVariantMap[genomePairIdentifier + "_ProbabilityOf2MutationsLowerBound"] = probabilityOf2MutationsLowerBoundString	
				offspringVariantMap[genomePairIdentifier + "_ProbabilityOf2MutationsUpperBound"] = probabilityOf2MutationsUpperBoundString

				return nil
			}

			err = addPairProbabilitiesToVariantMap(pair1PersonAGenomeIdentifier, pair1PersonBGenomeIdentifier)
			if (err != nil) { return false, "", err }

			if (genomePair2Exists == true){

				err := addPairProbabilitiesToVariantMap(pair2PersonAGenomeIdentifier, pair2PersonBGenomeIdentifier)
				if (err != nil) { return false, "", err }
			}

			offspringVariantsMapList = append(offspringVariantsMapList, offspringVariantMap)
		}

		// 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 (genomePair2Exists == true){

			// Conflicts are only possible if two genome pairs exist

			checkIfConflictExists := func()(bool, error){
		
				genomePair1Identifier := pair1PersonAGenomeIdentifier + "+" + pair1PersonBGenomeIdentifier

				genomePair2Identifier := pair2PersonAGenomeIdentifier + "+" + pair2PersonBGenomeIdentifier

				allGenomePairIdentifiersList := []string{genomePair1Identifier, genomePair2Identifier}

				probabilityOffspringHasDisease := ""
				probabilityOffspringHasVariant := ""

				for index, genomePairIdentifier := range allGenomePairIdentifiersList{

					currentProbabilityOffspringHasDisease, exists := offspringDiseaseMap[genomePairIdentifier + "_ProbabilityOffspringHasDisease"]
					if (exists == false) {
						return false, errors.New("Cannot find _ProbabilityOffspringHasDisease key when searching for conflicts.")
					}
					currentProbabilityOffspringHasVariant, exists := offspringDiseaseMap[genomePairIdentifier + "_ProbabilityOffspringHasVariant"]
					if (exists == false) {
						return false, errors.New("Cannot find _ProbabilityOffspringHasVariant key when searching for conflicts.")
					}

					if (index == 0){
						probabilityOffspringHasDisease = currentProbabilityOffspringHasDisease
						probabilityOffspringHasVariant = currentProbabilityOffspringHasVariant
						continue
					}
					if (currentProbabilityOffspringHasDisease != probabilityOffspringHasDisease){
						return true, nil
					}
					if (currentProbabilityOffspringHasVariant != probabilityOffspringHasVariant){
						return true, nil
					}
				}

				for _, variantMap := range offspringVariantsMapList{

					probabilityOf0MutationsLowerBound := ""
					probabilityOf0MutationsUpperBound := ""
					probabilityOf1MutationLowerBound := ""
					probabilityOf1MutationUpperBound := ""
					probabilityOf2MutationsLowerBound := ""
					probabilityOf2MutationsUpperBound := ""

					for index, genomePairIdentifier := range allGenomePairIdentifiersList{

						currentProbabilityOf0MutationsLowerBound, exists := variantMap[genomePairIdentifier + "_ProbabilityOf0MutationsLowerBound"]
						if (exists == false){
							return false, errors.New("Cannot find _ProbabilityOf0MutationsLowerBound key when searching for conflicts.")
						}
						currentProbabilityOf0MutationsUpperBound, exists := variantMap[genomePairIdentifier + "_ProbabilityOf0MutationsUpperBound"]
						if (exists == false){
							return false, errors.New("Cannot find _ProbabilityOf0MutationsUpperBound key when searching for conflicts.")
						}
						currentProbabilityOf1MutationLowerBound, exists := variantMap[genomePairIdentifier + "_ProbabilityOf1MutationLowerBound"]
						if (exists == false){
							return false, errors.New("Cannot find _ProbabilityOf1MutationLowerBound key when searching for conflicts.")
						}
						currentProbabilityOf1MutationUpperBound, exists := variantMap[genomePairIdentifier + "_ProbabilityOf1MutationUpperBound"]
						if (exists == false){
							return false, errors.New("Cannot find _ProbabilityOf1MutationUpperBound key when searching for conflicts.")
						}
						currentProbabilityOf2MutationsLowerBound, exists := variantMap[genomePairIdentifier + "_ProbabilityOf2MutationsLowerBound"]
						if (exists == false){
							return false, errors.New("Cannot find _ProbabilityOf2MutationsLowerBound key when searching for conflicts.")
						}
						currentProbabilityOf2MutationsUpperBound, exists := variantMap[genomePairIdentifier + "_ProbabilityOf2MutationsUpperBound"]
						if (exists == false){
							return false, errors.New("Cannot find _ProbabilityOf2MutationsUpperBound key when searching for conflicts.")
						}

						if (index == 0){
							probabilityOf0MutationsLowerBound = currentProbabilityOf0MutationsLowerBound
							probabilityOf0MutationsUpperBound = currentProbabilityOf0MutationsUpperBound

							probabilityOf1MutationLowerBound = currentProbabilityOf1MutationLowerBound
							probabilityOf1MutationUpperBound = currentProbabilityOf1MutationUpperBound

							probabilityOf2MutationsLowerBound = currentProbabilityOf2MutationsLowerBound
							probabilityOf2MutationsUpperBound = currentProbabilityOf2MutationsUpperBound
							continue
						}

						if (currentProbabilityOf0MutationsLowerBound != probabilityOf0MutationsLowerBound){
							return true, nil
						}
						if (currentProbabilityOf0MutationsUpperBound != probabilityOf0MutationsUpperBound){
							return true, nil
						}
						if (currentProbabilityOf1MutationLowerBound != probabilityOf1MutationLowerBound){
							return true, nil
						}
						if (currentProbabilityOf1MutationUpperBound != probabilityOf1MutationUpperBound){
							return true, nil
						}
						if (currentProbabilityOf2MutationsLowerBound != probabilityOf2MutationsLowerBound){
							return true, nil
						}
						if (currentProbabilityOf2MutationsUpperBound != probabilityOf2MutationsUpperBound){
							return true, nil
						}
					}
				}

				return false, nil
			}

			conflictExists, err := checkIfConflictExists()
			if (err != nil) { return false, "", err }

			conflictExistsString := helpers.ConvertBoolToYesOrNoString(conflictExists)

			offspringDiseaseMap["ConflictExists"] = conflictExistsString
		}

		newAnalysisMapList = append(newAnalysisMapList, offspringDiseaseMap)
		newAnalysisMapList = append(newAnalysisMapList, offspringVariantsMapList...)
	}

	// Step 2: Polygenic Diseases

	polygenicDiseaseObjectsList, err := polygenicDiseases.GetPolygenicDiseaseObjectsList()
	if (err != nil){ return false, "", err }

	for _, diseaseObject := range polygenicDiseaseObjectsList{

		diseaseName := diseaseObject.DiseaseName
		diseaseLociList := diseaseObject.LociList

		_, personALociMapList, err := getPolygenicDiseaseAnalysis(personAGenomesWithMetadataList, diseaseObject)
		if (err != nil) { return false, "", err }

		_, personBLociMapList, err := getPolygenicDiseaseAnalysis(personBGenomesWithMetadataList, diseaseObject)
		if (err != nil) { return false, "", err }

		offspringLociMapList := make([]map[string]string, 0, len(diseaseLociList))

		for _, locusObject := range diseaseLociList{

			locusIdentifier := locusObject.LocusIdentifier

			locusRiskWeightsMap := locusObject.RiskWeightsMap
			locusOddsRatiosMap := locusObject.OddsRatiosMap

			offspringLocusMap := map[string]string{
				"ItemType": "PolygenicDiseaseLocus",
				"LocusIdentifier": locusIdentifier,
				"DiseaseName": diseaseName,
			}

			// This will calculate the average risk weight and probability change for the offspring from the two specified genomes
			// It then adds the pair entry to the diseaseMap
			addPairDiseaseLocusInfoToLocusMap := func(personAGenomeIdentifier string, personBGenomeIdentifier string)error{

				getPersonGenomeLocusBasePair := func(personGenomeIdentifier string, personLociMapList []map[string]string)(bool, string, error){

					for _, locusMap := range personLociMapList{

						itemType, exists := locusMap["ItemType"]
						if (exists == false){
							return false, "", errors.New("getPolygenicDiseaseAnalysis returning lociMapList with item missing ItemType")
						}
						if (itemType != "PolygenicDiseaseLocus"){
							return false, "", errors.New("getPolygenicDiseaseAnalysis returning lociMapList with non-PolygenicDiseaseLocus item: " + itemType)
						}
						currentLocusIdentifier, exists := locusMap["LocusIdentifier"]
						if (exists == false){
							return false, "", errors.New("getPolygenicDiseaseAnalysis returning lociMapList with item missing LocusIdentifier")
						}

						if (currentLocusIdentifier != locusIdentifier){
							continue
						}

						locusBasePair, exists := locusMap[personGenomeIdentifier + "_LocusBasePair"]
						if (exists == false){
							return false, "", errors.New("getPolygenicDiseaseAnalysis returning lociMapList with item missing _LocusBasePair")
						}

						if (locusBasePair == "Unknown"){
							return false, "", nil
						}

						return true, locusBasePair, nil
					}

					return false, "", errors.New("getPolygenicDiseaseAnalysis returning lociMapList missing a locus: " + locusIdentifier)
				}

				genomePairIdentifier := personAGenomeIdentifier + "+" + personBGenomeIdentifier

				personALocusBasePairKnown, personALocusBasePair, err := getPersonGenomeLocusBasePair(personAGenomeIdentifier, personALociMapList)
				if (err != nil) { return err }

				personBLocusBasePairKnown, personBLocusBasePair, err := getPersonGenomeLocusBasePair(personBGenomeIdentifier, personBLociMapList)
				if (err != nil) { return err }

				if (personALocusBasePairKnown == false || personBLocusBasePairKnown == false){

					offspringLocusMap[genomePairIdentifier + "_OffspringRiskWeight"] = "Unknown"
					offspringLocusMap[genomePairIdentifier + "_OffspringOddsRatio"] = "Unknown"
					offspringLocusMap[genomePairIdentifier + "_OffspringUnknownOddsRatiosWeightSum"] = "Unknown"

					return nil
				}

				offspringAverageRiskWeight, offspringOddsRatioKnown, offspringAverageOddsRatio, averageUnknownOddsRatiosWeightSum, err := GetOffspringPolygenicDiseaseLocusInfo(locusRiskWeightsMap, locusOddsRatiosMap, personALocusBasePair, personBLocusBasePair)
				if (err != nil) { return err }

				averageRiskWeightString := helpers.ConvertIntToString(offspringAverageRiskWeight)

				offspringLocusMap[genomePairIdentifier + "_OffspringRiskWeight"] = averageRiskWeightString

				if (offspringOddsRatioKnown == false){

					offspringLocusMap[genomePairIdentifier + "_OffspringOddsRatio"] = "Unknown"

				} else {

					averageOddsRatioString := helpers.ConvertFloat64ToString(offspringAverageOddsRatio)

					offspringLocusMap[genomePairIdentifier + "_OffspringOddsRatio"] = averageOddsRatioString
				}

				averageUnknownOddsRatiosWeightSumString := helpers.ConvertIntToString(averageUnknownOddsRatiosWeightSum)

				offspringLocusMap[genomePairIdentifier + "_OffspringUnknownOddsRatiosWeightSum"] = averageUnknownOddsRatiosWeightSumString

				return nil
			}

			err = addPairDiseaseLocusInfoToLocusMap(pair1PersonAGenomeIdentifier, pair1PersonBGenomeIdentifier)
			if (err != nil) { return false, "", err }

			if (genomePair2Exists == true){

				err := addPairDiseaseLocusInfoToLocusMap(pair2PersonAGenomeIdentifier, pair2PersonBGenomeIdentifier)
				if (err != nil) { return false, "", err }
			}

			offspringLociMapList = append(offspringLociMapList, offspringLocusMap)
		}

		// Now we iterate through loci to determine genome pair disease info

		offspringPolygenicDiseaseMap := map[string]string{
			"ItemType": "PolygenicDisease",
			"DiseaseName": diseaseName,
		}

		polygenicDiseaseLociMap, err := polygenicDiseases.GetPolygenicDiseaseLociMap(diseaseName)
		if (err != nil) { return false, "", err }

		addPairPolygenicDiseaseInfoToDiseaseMap := func(personAGenomeIdentifier string, personBGenomeIdentifier string)error{

			genomePairIdentifier := personAGenomeIdentifier + "+" + personBGenomeIdentifier

			numberOfLociTested := 0
			summedRiskWeights := 0
			minimumPossibleRiskWeightSum := 0
			maximumPossibleRiskWeightSum := 0

			for _, locusMap := range offspringLociMapList{

				locusIdentifier, exists := locusMap["LocusIdentifier"]
				if (exists == false){
					return errors.New("offspringLociMapList item missing LocusIdentifier")
				}

				locusObject, exists := polygenicDiseaseLociMap[locusIdentifier]
				if (exists == false){
					return errors.New("offspringLociMapList contains locus not found in allDiseaseLociObjectsMap")
				}

				locusMinimumRiskWeight := locusObject.MinimumRiskWeight
				locusMaximumRiskWeight := locusObject.MaximumRiskWeight

				minimumPossibleRiskWeightSum += locusMinimumRiskWeight
				maximumPossibleRiskWeightSum += locusMaximumRiskWeight

				locusRiskWeight, exists := locusMap[genomePairIdentifier + "_OffspringRiskWeight"]
				if (exists == false){
					return errors.New("offspringLociMapList contains locusMap missing _OffspringRiskWeight")
				}

				if (locusRiskWeight == "Unknown"){
					continue
				}
				numberOfLociTested += 1

				locusRiskWeightInt, err := helpers.ConvertStringToInt(locusRiskWeight)
				if (err != nil){
					return errors.New("offspringLociMapList contains locusMap with invalid _OffspringRiskWeight: " + locusRiskWeight)
				}

				summedRiskWeights += locusRiskWeightInt
			}

			if (numberOfLociTested == 0){

				// No loci were tested
				offspringPolygenicDiseaseMap[genomePairIdentifier + "_NumberOfLociTested"] = "0"
				offspringPolygenicDiseaseMap[genomePairIdentifier + "_OffspringRiskScore"] = "Unknown"

				return nil
			}

			numberOfLociTestedString := helpers.ConvertIntToString(numberOfLociTested)
			offspringPolygenicDiseaseMap[genomePairIdentifier + "_NumberOfLociTested"] = numberOfLociTestedString

			pairDiseaseRiskScore, err := helpers.ScaleNumberProportionally(true, summedRiskWeights, minimumPossibleRiskWeightSum, maximumPossibleRiskWeightSum, 0, 10)
			if (err != nil) { return err }

			pairDiseaseRiskScoreString := helpers.ConvertIntToString(pairDiseaseRiskScore)

			offspringPolygenicDiseaseMap[genomePairIdentifier + "_OffspringRiskScore"] = pairDiseaseRiskScoreString

			return nil
		}

		addPairPolygenicDiseaseInfoToDiseaseMap(pair1PersonAGenomeIdentifier, pair1PersonBGenomeIdentifier)
		if (err != nil) { return false, "", err }

		if (genomePair2Exists == true){

			err := addPairPolygenicDiseaseInfoToDiseaseMap(pair2PersonAGenomeIdentifier, pair2PersonBGenomeIdentifier)
			if (err != nil) { return false, "", err }
		}

		if (genomePair2Exists == true){

			// We check for conflicts		
			// Conflicts are only possible if two genome pairs exist

			checkIfConflictExists := func()(bool, error){

				genomePair1Identifier := pair1PersonAGenomeIdentifier + "+" + pair1PersonBGenomeIdentifier

				genomePair2Identifier := pair2PersonAGenomeIdentifier + "+" + pair2PersonBGenomeIdentifier

				allGenomePairIdentifiersList := []string{genomePair1Identifier, genomePair2Identifier}

				for _, locusMap := range offspringLociMapList{

					offspringRiskWeight := ""
					offspringOddsRatio := ""
					offspringUnknownOddsRatiosWeightSum := ""

					for index, genomePairIdentifier := range allGenomePairIdentifiersList{

						currentOffspringRiskWeight, exists := locusMap[genomePairIdentifier + "_OffspringRiskWeight"]
						if (exists == false){
							return false, errors.New("Cannot find _OffspringRiskWeight key when searching for conflicts.")
						}
						currentOffspringOddsRatio, exists := locusMap[genomePairIdentifier + "_OffspringOddsRatio"]
						if (exists == false){
							return false, errors.New("Cannot find _OffspringOddsRatio key when searching for conflicts.")
						}
						currentOffspringUnknownOddsRatiosWeightSum, exists := locusMap[genomePairIdentifier + "_OffspringUnknownOddsRatiosWeightSum"]
						if (exists == false){
							return false, errors.New("Cannot find _OffspringUnknownOddsRatiosWeightSum key when searching for conflicts.")
						}
					
						if (index == 0){
							offspringRiskWeight = currentOffspringRiskWeight
							offspringOddsRatio = currentOffspringOddsRatio
							offspringUnknownOddsRatiosWeightSum = currentOffspringUnknownOddsRatiosWeightSum
							continue
						}
						if (currentOffspringRiskWeight != offspringRiskWeight){
							return true, nil
						}
						if (currentOffspringOddsRatio != offspringOddsRatio){
							return true, nil
						}
						if (currentOffspringUnknownOddsRatiosWeightSum != offspringUnknownOddsRatiosWeightSum){
							return true, nil
						}
					}
				}

				return false, nil
			}

			conflictExists, err := checkIfConflictExists()
			if (err != nil) { return false, "", err }

			conflictExistsString := helpers.ConvertBoolToYesOrNoString(conflictExists)

			offspringPolygenicDiseaseMap["ConflictExists"] = conflictExistsString
		}

		newAnalysisMapList = append(newAnalysisMapList, offspringPolygenicDiseaseMap)
		newAnalysisMapList = append(newAnalysisMapList, offspringLociMapList...)
	}

	// Step 3: Traits

	traitObjectsList, err := traits.GetTraitObjectsList()
	if (err != nil) { return false, "", err }

	for _, traitObject := range traitObjectsList{

		traitName := traitObject.TraitName
		traitRulesList := traitObject.RulesList

		_, personATraitRulesMapList, err := getTraitAnalysis(personAGenomesWithMetadataList, traitObject)
		if (err != nil) { return false, "", err }

		_, personBTraitRulesMapList, err := getTraitAnalysis(personBGenomesWithMetadataList, traitObject)
		if (err != nil) { return false, "", err }

		offspringRulesMapList := make([]map[string]string, 0, len(traitRulesList))

		for _, ruleObject := range traitRulesList{

			ruleIdentifier := ruleObject.RuleIdentifier

			// This is a list that describes the locus rsids and their values that must be fulfilled to pass the rule
			ruleLocusObjectsList := ruleObject.LociList

			offspringRuleMap := map[string]string{
				"ItemType": "TraitRule",
				"RuleIdentifier": ruleIdentifier,
				"TraitName": traitName,
			}

			// This will calculate the number of offspring that will pass the rule for the offspring from the two specified genomes
			// It then adds the pair entry to the ruleMap
			addPairTraitRuleInfoToRuleMap := func(personAGenomeIdentifier string, personBGenomeIdentifier string)error{

				//Outputs:
				//	-bool: All rule loci are known
				//	-map[string]string: RSID -> Locus base pair value
				//	-error
				getPersonGenomeRuleLociValuesMap := func(personGenomeIdentifier string, personTraitRulesMapList []map[string]string)(bool, map[string]string, error){

					for _, ruleMap := range personTraitRulesMapList{

						itemType, exists := ruleMap["ItemType"]
						if (exists == false){
							return false, nil, errors.New("getTraitAnalysis returning rulesMapList with item missing ItemType")
						}
						if (itemType != "TraitRule"){
							return false, nil, errors.New("getTraitAnalysis returning rulesMapList with non-TraitRule item: " + itemType)
						}
						currentRuleIdentifier, exists := ruleMap["RuleIdentifier"]
						if (exists == false){
							return false, nil, errors.New("getTraitAnalysis returning rulesMapList with item missing RuleIdentifier")
						}

						if (currentRuleIdentifier != ruleIdentifier){
							continue
						}

						// Map structure: Locus identifier -> Locus base pair value
						personTraitLociBasePairsMap := make(map[string]string)

						for _, locusObject := range ruleLocusObjectsList{

							locusIdentifier := locusObject.LocusIdentifier

							personLocusBasePair, exists := ruleMap[personGenomeIdentifier + "_RuleLocusBasePair_" + locusIdentifier]
							if (exists == false){
								return false, nil, errors.New("_LocusBasePair_ value not found in person trait analysis ruleMap")
							}

							if (personLocusBasePair == "Unknown"){
								// Not all locus values are known, thus, we cannot determine if the genome passes the rule
								return false, nil, nil
							}

							personTraitLociBasePairsMap[locusIdentifier] = personLocusBasePair
						}

						return true, personTraitLociBasePairsMap, nil
					}

					return false, nil, errors.New("getTraitAnalysis returning rulesMapList missing a rule: " + ruleIdentifier)
				}

				allPersonALociKnown, personAGenomeRuleLociValuesMap, err := getPersonGenomeRuleLociValuesMap(personAGenomeIdentifier, personATraitRulesMapList)
				if (err != nil) { return err }

				allPersonBLociKnown, personBGenomeRuleLociValuesMap, err := getPersonGenomeRuleLociValuesMap(personBGenomeIdentifier, personBTraitRulesMapList)
				if (err != nil) { return err }

				genomePairIdentifier := personAGenomeIdentifier + "+" + personBGenomeIdentifier

				if (allPersonALociKnown == false || allPersonBLociKnown == false){

					// We only know how many of the 4 prospective offspring pass the rule if all loci are known for both people's genomes

					offspringRuleMap[genomePairIdentifier + "_OffspringProbabilityOfPassingRule"] = "Unknown"
					return nil
				}

				// This is a probability between 0 and 1
				offspringProbabilityOfPassingRule := float64(1)

				for _, ruleLocusObject := range ruleLocusObjectsList{

					locusIdentifier := ruleLocusObject.LocusIdentifier

					personALocusBasePair, exists := personAGenomeRuleLociValuesMap[locusIdentifier]
					if (exists == false){
						return errors.New("personAGenomeRuleLociValuesMap missing locusIdentifier")
					}

					personBLocusBasePair, exists := personBGenomeRuleLociValuesMap[locusIdentifier]
					if (exists == false){
						return errors.New("personBGenomeRuleLociValuesMap missing locusIdentifier")
					}

					locusRequiredBasePairsList := ruleLocusObject.BasePairsList

					offspringProbabilityOfPassingRuleLocus, err := GetOffspringTraitRuleLocusInfo(locusRequiredBasePairsList, personALocusBasePair, personBLocusBasePair)
					if (err != nil) { return err }

					offspringProbabilityOfPassingRule *= offspringProbabilityOfPassingRuleLocus
				}

				offspringPercentageProbabilityOfPassingRule := offspringProbabilityOfPassingRule * 100

				offspringPercentageProbabilityOfPassingRuleString := helpers.ConvertFloat64ToStringRounded(offspringPercentageProbabilityOfPassingRule, 0)

				offspringRuleMap[genomePairIdentifier + "_OffspringProbabilityOfPassingRule"] = offspringPercentageProbabilityOfPassingRuleString

				return nil
			}

			err = addPairTraitRuleInfoToRuleMap(pair1PersonAGenomeIdentifier, pair1PersonBGenomeIdentifier)
			if (err != nil) { return false, "", err }

			if (genomePair2Exists == true){

				err := addPairTraitRuleInfoToRuleMap(pair2PersonAGenomeIdentifier, pair2PersonBGenomeIdentifier)
				if (err != nil) { return false, "", err }
			}

			offspringRulesMapList = append(offspringRulesMapList, offspringRuleMap)
		}

		// Now we iterate through rules to determine genome pair trait info

		offspringTraitMap := map[string]string{
			"ItemType": "Trait",
			"TraitName": traitName,
		}

		traitRulesMap, err := traits.GetTraitRulesMap(traitName)
		if (err != nil) { return false, "", err }

		addPairTraitInfoToTraitMap := func(personAGenomeIdentifier string, personBGenomeIdentifier string)error{

			genomePairIdentifier := personAGenomeIdentifier + "+" + personBGenomeIdentifier

			if (len(traitRulesList) == 0){
				// This trait is not yet able to be analyzed.
				// This feature will be added soon
				// These traits will use neural networks instead of rules
				offspringTraitMap[genomePairIdentifier + "_NumberOfRulesTested"] = "0"
				return nil
			}

			numberOfRulesTested := 0

			// Map Structure: Outcome -> Average score from all rules
			averageOutcomeScoresMap := make(map[string]float64)

			for _, ruleMap := range offspringRulesMapList{

				ruleIdentifier, exists := ruleMap["RuleIdentifier"]
				if (exists == false){
					return errors.New("offspringRulesMapList item missing RuleIdentifier")
				}

				offspringPercentageProbabilityOfPassingRule, exists := ruleMap[genomePairIdentifier + "_OffspringProbabilityOfPassingRule"]
				if (exists == false){
					return errors.New("offspringRulesMapList contains ruleMap missing _OffspringProbabilityOfPassingRule")
				}

				if (offspringPercentageProbabilityOfPassingRule == "Unknown"){
					continue
				}

				numberOfRulesTested += 1

				offspringPercentageProbabilityOfPassingRuleFloat64, err := helpers.ConvertStringToFloat64(offspringPercentageProbabilityOfPassingRule)
				if (err != nil){
					return errors.New("offspringRulesMapList contains ruleMap with invalid _OffspringProbabilityOfPassingRule: " + offspringPercentageProbabilityOfPassingRule)
				}

				// This is the 0 - 1 probability value
				offspringProbabilityOfPassingRule := offspringPercentageProbabilityOfPassingRuleFloat64/100

				ruleObject, exists := traitRulesMap[ruleIdentifier]
				if (exists == false){
					return errors.New("offspringRulesMapList contains rule not found in traitRulesMap: " + ruleIdentifier)
				}

				ruleOutcomePointsMap := ruleObject.OutcomePointsMap

				for outcomeName, outcomePointsEffect := range ruleOutcomePointsMap{

					pointsToAdd := float64(outcomePointsEffect) * offspringProbabilityOfPassingRule

					averageOutcomeScoresMap[outcomeName] += pointsToAdd
				}
			}

			numberOfRulesTestedString := helpers.ConvertIntToString(numberOfRulesTested)
			offspringTraitMap[genomePairIdentifier + "_NumberOfRulesTested"] = numberOfRulesTestedString

			if (numberOfRulesTested == 0){

				return nil
			}

			traitOutcomesList := traitObject.OutcomesList

			for _, outcomeName := range traitOutcomesList{

				getOffspringAverageOutcomeScore := func()float64{

					averageOutcomeScore, exists := averageOutcomeScoresMap[outcomeName]
					if (exists == false){
						// No rules effected this outcome.
						return 0
					}
					return averageOutcomeScore
				}

				offspringAverageOutcomeScore := getOffspringAverageOutcomeScore()

				offspringAverageOutcomeScoreString := helpers.ConvertFloat64ToStringRounded(offspringAverageOutcomeScore, 2)

				offspringTraitMap[genomePairIdentifier + "_OffspringAverageOutcomeScore_" + outcomeName] = offspringAverageOutcomeScoreString
			}

			return nil
		}

		addPairTraitInfoToTraitMap(pair1PersonAGenomeIdentifier, pair1PersonBGenomeIdentifier)
		if (err != nil) { return false, "", err }

		if (genomePair2Exists == true){

			err := addPairTraitInfoToTraitMap(pair2PersonAGenomeIdentifier, pair2PersonBGenomeIdentifier)
			if (err != nil) { return false, "", err }
		}

		if (genomePair2Exists == true){

			// We check for conflicts
			// Conflicts are only possible if two genome pairs exist

			checkIfConflictExists := func()(bool, error){

				genomePair1Identifier := pair1PersonAGenomeIdentifier + "+" + pair1PersonBGenomeIdentifier

				genomePair2Identifier := pair2PersonAGenomeIdentifier + "+" + pair2PersonBGenomeIdentifier

				allGenomePairIdentifiersList := []string{genomePair1Identifier, genomePair2Identifier}

				for _, ruleMap := range offspringRulesMapList{

					offspringProbabilityOfPassingRule := ""

					for index, genomePairIdentifier := range allGenomePairIdentifiersList{

						currentOffspringProbabilityOfPassingRule, exists := ruleMap[genomePairIdentifier + "_OffspringProbabilityOfPassingRule"]
						if (exists == false){
							return false, errors.New("Cannot find _OffspringProbabilityOfPassingRule key when searching for conflicts.")
						}

						if (index == 0){

							offspringProbabilityOfPassingRule = currentOffspringProbabilityOfPassingRule
							continue
						}
						if (currentOffspringProbabilityOfPassingRule != offspringProbabilityOfPassingRule){
							return true, nil
						}
					}
				}

				return false, nil
			}

			conflictExists, err := checkIfConflictExists()
			if (err != nil) { return false, "", err }

			conflictExistsString := helpers.ConvertBoolToYesOrNoString(conflictExists)

			offspringTraitMap["ConflictExists"] = conflictExistsString
		}

		newAnalysisMapList = append(newAnalysisMapList, offspringTraitMap)
		newAnalysisMapList = append(newAnalysisMapList, offspringRulesMapList...)
	}

	analysisBytes, err := json.MarshalIndent(newAnalysisMapList, "", "\t")
	if (err != nil) { return false, "", err }

	analysisString := string(analysisBytes)

	return true, analysisString, nil
}

// We also use this function when calculating offspring probabilities between users in viewProfileGui.go
//Outputs:
//	-int: Percentage probability offspring has disease (0-100)
//	-int: Percentage probability offspring has variant (0-100)
//	-error
func GetOffspringMonogenicDiseaseProbabilities(dominantOrRecessive string, personAWillPassVariantPercentageProbability int, personBWillPassVariantPercentageProbability int)(int, int, error){

	if (dominantOrRecessive != "Dominant" && dominantOrRecessive != "Recessive"){
		return 0, 0, errors.New("GetOffspringMonogenicDiseaseProbabilities called with invalid dominantOrRecessive: " + dominantOrRecessive)
	}

	personAWillPassVariantProbability := float64(personAWillPassVariantPercentageProbability)/100
	personBWillPassVariantProbability := float64(personBWillPassVariantPercentageProbability)/100

	if (personAWillPassVariantProbability < 0 || personAWillPassVariantProbability > 1){
		return 0, 0, errors.New("GetOffspringMonogenicDiseaseProbabilities called with invalid personAWillPassVariantProbability")
	}

	if (personBWillPassVariantProbability < 0 || personBWillPassVariantProbability > 1){
		return 0, 0, errors.New("GetOffspringMonogenicDiseaseProbabilities called with invalid personBWillPassVariantProbability")
	}

	// 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 A passing a variant) + (Probability of person B passing a variant) - (Probability of offspring having disease)
	// A person with a variant may have the disease, or just be a carrier.
	probabilityOffspringHasVariant := personAWillPassVariantProbability + personBWillPassVariantProbability - (personAWillPassVariantProbability * personBWillPassVariantProbability)

	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 percentageProbabilityOffspringHasVariant, 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 A Passing a variant) * (Probability of person B passing a variant)
	probabilityOffspringHasDisease := personAWillPassVariantProbability * personBWillPassVariantProbability

	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 percentageProbabilityOffspringHasDiseaseInt, 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, personALocusBasePair string, personBLocusBasePair string)(int, bool, float64, int, error){

	personABase1, personABase2, delimiterFound := strings.Cut(personALocusBasePair, ";")
	if (delimiterFound == false){
		return 0, false, 0, 0, errors.New("GetOffspringPolygenicDiseaseLocusInfo called with invalid person A locus base pair: " + personALocusBasePair)
	}
	personBBase1, personBBase2, delimiterFound := strings.Cut(personBLocusBasePair, ";")
	if (delimiterFound == false){
		return 0, false, 0, 0, errors.New("GetOffspringPolygenicDiseaseLocusInfo called with invalid person B locus base pair: " + personBLocusBasePair)
	}

	// We create the 4 options for the offspring's bases at this locus

	offspringBasePairOutcomeA := personABase1 + ";" + personBBase1
	offspringBasePairOutcomeB := personABase2 + ";" + personBBase2
	offspringBasePairOutcomeC := personABase1 + ";" + personBBase2
	offspringBasePairOutcomeD := personABase2 + ";" + personBBase1

	baseOutcomesList := []string{offspringBasePairOutcomeA, offspringBasePairOutcomeB, offspringBasePairOutcomeC, offspringBasePairOutcomeD}

	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

			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: 
//	-float64: Probability of offspring passing rule (0-1)
//	-error
func GetOffspringTraitRuleLocusInfo(locusRequiredBasePairsList []string, personALocusBasePair string, personBLocusBasePair string)(float64, error){

	personABase1, personABase2, delimiterFound := strings.Cut(personALocusBasePair, ";")
	if (delimiterFound == false){
		return 0, errors.New("GetOffspringTraitRuleLocusInfo called with invalid personA locus base pair: " + personALocusBasePair)
	}
	personBBase1, personBBase2, delimiterFound := strings.Cut(personBLocusBasePair, ";")
	if (delimiterFound == false){
		return 0, errors.New("GetOffspringTraitRuleLocusInfo called with invalid personB locus base pair: " + personBLocusBasePair)
	}

	// We create the 4 options for the offspring's bases at this locus

	offspringBasePairOutcomeA := personABase1 + ";" + personBBase1
	offspringBasePairOutcomeB := personABase2 + ";" + personBBase2
	offspringBasePairOutcomeC := personABase1 + ";" + personBBase2
	offspringBasePairOutcomeD := personABase2 + ";" + personBBase1

	baseOutcomesList := []string{offspringBasePairOutcomeA, offspringBasePairOutcomeB, offspringBasePairOutcomeC, offspringBasePairOutcomeD}

	numberOfOffspringOutcomesWhomPassRuleLocus := 0

	for _, outcomeBasePair := range baseOutcomesList{

		isValid := verifyBasePair(outcomeBasePair)
		if (isValid == false){
			return 0, errors.New("GetOffspringTraitRuleLocusInfo called with invalid locus base pair: " + outcomeBasePair)
		}

		outcomePassesRuleLocus := slices.Contains(locusRequiredBasePairsList, outcomeBasePair)
		if (outcomePassesRuleLocus == true){
			numberOfOffspringOutcomesWhomPassRuleLocus += 1
		}
	}

	offspringProbabilityOfPassingRuleLocus := float64(numberOfOffspringOutcomesWhomPassRuleLocus)/float64(4)

	return offspringProbabilityOfPassingRuleLocus, 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: Base pairs are 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:
//	-map[string]string: Monogenic disease analysis map (contains probabilities for each genomeIdentifier and number of tested variants)
//	-[]map[string]string: Variants map list (contains variant info for each genomeIdentifier)
//	-error
func getMonogenicDiseaseAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.GenomeWithMetadata, diseaseObject monogenicDiseases.MonogenicDisease)(map[string]string, []map[string]string, error){

	diseaseName := diseaseObject.DiseaseName
	dominantOrRecessive := diseaseObject.DominantOrRecessive
	variantsList := diseaseObject.VariantsList

	// We use this map to keep track of which RSIDs corresponds to each variant
	// Map Structure: Variant Identifier -> []rsID
	variantRSIDsMap := make(map[string][]int64)

	variantsMapList := make([]map[string]string, 0, len(variantsList))

	for _, variantObject := range variantsList{

		variantIdentifier := variantObject.VariantIdentifier

		// Map Structure:
		//	-GenomeIdentifier -> ("Yes"/"No" + ";" + "Yes"/"No") or "Unknown"
		variantMap := map[string]string{
			"ItemType": "MonogenicDiseaseVariant",
			"VariantIdentifier": variantIdentifier,
			"DiseaseName": diseaseName,
		}

		variantRSID := variantObject.VariantRSID
		variantDefectiveBase := variantObject.DefectiveBase

		variantRSIDsList := []int64{variantRSID}

		// We add aliases to variantRSIDsList

		anyAliasesExist, rsidAliasesList, err := locusMetadata.GetRSIDAliases(variantRSID)
		if (err != nil) { return nil, nil, err }
		if (anyAliasesExist == true){
			variantRSIDsList = append(variantRSIDsList, rsidAliasesList...)
		}

		variantRSIDsMap[variantIdentifier] = variantRSIDsList

		for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{

			genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier
			genomeMap := genomeWithMetadataObject.GenomeMap

			basePairValueFound, base1Value, base2Value, locusIsPhased, err := getGenomeLocusBasePair(genomeMap, variantRSID)
			if (err != nil) { return nil, nil, err }
			if (basePairValueFound == false){

				variantMap[genomeIdentifier + "_HasVariant"] = "Unknown"
				continue
			}

			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)

			base1IsDefectiveString := helpers.ConvertBoolToYesOrNoString(base1IsDefective)
			base2IsDefectiveString := helpers.ConvertBoolToYesOrNoString(base2IsDefective)

			genomeHasVariantMapValue := base1IsDefectiveString + ";" + base2IsDefectiveString
			locusIsPhasedString := helpers.ConvertBoolToYesOrNoString(locusIsPhased)

			variantMap[genomeIdentifier + "_HasVariant"] = genomeHasVariantMapValue
			variantMap[genomeIdentifier + "_LocusIsPhased"] = locusIsPhasedString

			//TODO: Add LocusIsPhased to readGeneticAnalysis package
		}

		variantsMapList = append(variantsMapList, variantMap)
	}

	// Now we determine probability that user will pass disease to offspring, and probability that user has disease
	// We compute this for each genome

	diseaseAnalysisMap := make(map[string]string)

	// We will use this list when checking for conflicts
	allGenomeIdentifiersList := make([]string, 0, len(inputGenomesWithMetadataList))

	for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{

		genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier

		allGenomeIdentifiersList = append(allGenomeIdentifiersList, genomeIdentifier)

		numberOfVariantsTested := 0

		for _, variantMap := range variantsMapList{

			genomeHasVariantValue, exists := variantMap[genomeIdentifier + "_HasVariant"]
			if (exists == false){
				return nil, nil, errors.New("variantMap malformed: Map missing a _HasVariant for genome")
			}

			if (genomeHasVariantValue != "Unknown"){
				numberOfVariantsTested += 1
			}
		}

		numberOfVariantsTestedString := helpers.ConvertIntToString(numberOfVariantsTested)

		diseaseAnalysisMap[genomeIdentifier + "_NumberOfVariantsTested"] = numberOfVariantsTestedString

		// Outputs:
		//	-bool: Probability is known (will be false if the genome has no tested variants)
		//	-float64: Probability Person has disease
		//	-float64: Probability Person will pass a defect (variant) to offspring
		//	-error
		getPersonDiseaseInfo := func()(bool, float64, float64, error){

			anyProbabilityKnown := false

			// 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 _, variantMap := range variantsMapList{

				personHasVariantStatus, exists := variantMap[genomeIdentifier + "_HasVariant"]
				if (exists == false){
					return false, 0, 0, errors.New("variantMap malformed: Map missing a _HasVariant for genome.")
				}

				if (personHasVariantStatus == "Unknown"){
					// We don't know if the genome has the variant. Skip to next variant
					continue
				}

				anyProbabilityKnown = true

				locusIsPhasedStatus, exists := variantMap[genomeIdentifier + "_LocusIsPhased"]
				if (exists == false){
					return false, 0, 0, errors.New("variantMap malformed: Map missing _LocusIsPhased for genome.")
				}

				base1HasVariant, base2HasVariant, foundSemicolon := strings.Cut(personHasVariantStatus, ";")
				if (foundSemicolon == false){
					return false, 0, 0, errors.New("variantMap is malformed: Contains invalid personHasVariantValue: " + personHasVariantStatus)
				}

				if (base1HasVariant == "No" && base2HasVariant == "No"){
					// Neither chromosome contains the variant mutation.
					continue
				}

				if (base1HasVariant == "Yes" && base2HasVariant == "Yes"){
					// Both chromosomes contain the same variant mutation.
					// Person has the disease.
					// Person will definitely pass disease variant to offspring.
					return true, 1, 1, nil
				}

				// We know that this variant exists on 1 of the bases, but not both.

				variantIdentifier, exists := variantMap["VariantIdentifier"]
				if (exists == false){
					return false, 0, 0, errors.New("VariantMap missing VariantIdentifier.")
				}

				variantRSIDsList, exists := variantRSIDsMap[variantIdentifier]
				if (exists == false){
					return false, 0, 0, errors.New("variantRSIDMap missing variantIdentifier.")
				}

				for _, rsid := range variantRSIDsList{
					rsidMutationsMap[rsid] += 1
				}

				if (locusIsPhasedStatus == "Yes"){

					if (base1HasVariant == "Yes"){
						numberOfVariants_Chromosome1 += 1
					}
					if (base2HasVariant == "Yes"){
						numberOfVariants_Chromosome2 += 1
					}
				} else {

					if (base1HasVariant == "Yes" || base2HasVariant == "Yes"){
						numberOfVariants_UnknownChromosome += 1
					}
				}
			}

			if (anyProbabilityKnown == false){
				return false, 0, 0, nil
			}

			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 true, 0, 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, 1, nil
				}
			}

			// At this point, we know that there are no homozygous variant mutations
			// All variant mutations are heterozygous, meaning the other chromosome base is healthy

			// Probability is expressed as a float between 0 - 1
			getProbabilityPersonHasDisease := func()float64{

				if (dominantOrRecessive == "Dominant"){
					// Only 1 variant is needed for the person to have the disease
					// We know they have at least 1 variant
					return 1
				}

				// 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 0
				}

				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 1
				}

				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 0
				}

				if (numberOfVariants_Chromosome1 == 0 && numberOfVariants_Chromosome2 == 0){

					// All variants have an unknown phase, and we know there are multiple of them.
					// The probability the person does not have the disease is the probability that all mutations are on the same chromosome
					// We calculate the probability that all of the mutations are on the same chromosome
					// If they are all on the same chromosome, the person does not have the disease
					// If at least 1 variant exists on both chromosomes, the person has the disease

					// We calculate the probability that all variants are all on the same chromosome
					// Probability of n variants existing on the same chromosome = 1/(2^n)
					// P(X) = Probability all variants existing on chromosome 1 = 1/(2^n)
					// P(Y) = Probability all variants existing on chromosome 2 = 1/(2^n)
					// P(A U B) = P(A) + P(B) (If A and B are mutually exclusive)
					// P(X) and P(Y) are mutually exclusive
					// Probability of n variants existing on either chromosome 1 or 2 = P(X) + P(Y)
					// Probability person has disease = !P(X U Y)

					probabilityAllVariantsAreOnOneChromosome := 1/(math.Pow(2, float64(numberOfVariants_UnknownChromosome)))

					probabilityPersonHasDisease := 1 - (probabilityAllVariantsAreOnOneChromosome * 2)

					return probabilityPersonHasDisease
				}

				// We know that there is at least 1 variant whose phase is known
				// We know that there are no variants whose phase is known which exist on both chromosomes
				// We know there are at least some variants whose phase is unknown

				// The probability that the person has the disease is
				//		the probability that the unknown-phase variants exist on the same chromosome as the ones which we know exist do
				// This probability is 50% for each unknown-phase variant

				probabilityAllVariantsAreOnOneChromosome := 1/(math.Pow(2, float64(numberOfVariants_UnknownChromosome)))

				probabilityPersonHasDisease := 1 - probabilityAllVariantsAreOnOneChromosome

				return probabilityPersonHasDisease
			}

			probabilityPersonHasDisease := getProbabilityPersonHasDisease()

			// We know all variants are heterozygous

			// Probability person will not pass any of n variants to their offspring: 1/(2^n)
			// Probability person will pass at least 1 of n variants to their offspring: 1 - (1/(2^n))

			probabilityPersonWillPassAnyVariant := 1 - (1/(math.Pow(2, float64(totalNumberOfVariants))))

			return true, probabilityPersonHasDisease, probabilityPersonWillPassAnyVariant, nil
		}

		probabilityKnown, probabilityPersonHasDisease, probabilityPersonWillPassAnyVariant, err := getPersonDiseaseInfo()
		if (err != nil) { return nil, nil, err }
		if (probabilityKnown == false){
			diseaseAnalysisMap[genomeIdentifier + "_ProbabilityOfHavingDisease"] = "Unknown"
			diseaseAnalysisMap[genomeIdentifier + "_ProbabilityOfPassingADiseaseVariant"] = "Unknown"
			continue
		}

		percentageProbabilityPersonHasDisease := probabilityPersonHasDisease * 100
		percentageProbabilityPersonWillPassADiseaseVariant := probabilityPersonWillPassAnyVariant * 100

		probabilityOfHavingDiseaseString := helpers.ConvertFloat64ToStringRounded(percentageProbabilityPersonHasDisease, 0)
		probabilityOfPassingADiseaseVariantString := helpers.ConvertFloat64ToStringRounded(percentageProbabilityPersonWillPassADiseaseVariant, 0)

		diseaseAnalysisMap[genomeIdentifier + "_ProbabilityOfHavingDisease"] = probabilityOfHavingDiseaseString
		diseaseAnalysisMap[genomeIdentifier + "_ProbabilityOfPassingADiseaseVariant"] = probabilityOfPassingADiseaseVariantString
	}

	if (len(allGenomeIdentifiersList) == 1){
		// We do not need to check for conflicts
		// Nothing left to do. Analysis is complete.
		return diseaseAnalysisMap, variantsMapList, nil
	}

	// We check for conflicts

	getConflictExistsBool := func()(bool, error){

		// We start with disease analysis map

		probabilityOfHavingDisease := ""
		probabilityOfPassingAVariant := ""

		for index, genomeIdentifier := range allGenomeIdentifiersList{

			currentProbabilityOfHavingDisease, exists := diseaseAnalysisMap[genomeIdentifier + "_ProbabilityOfHavingDisease"]
			if (exists == false){
				return false, errors.New("Cannot create analysis: diseaseAnalysisMap missing _ProbabilityOfHavingDisease")
			}

			currentProbabilityOfPassingAVariant, exists := diseaseAnalysisMap[genomeIdentifier + "_ProbabilityOfPassingADiseaseVariant"]
			if (exists == false){
				return false, errors.New("Cannot create analysis: diseaseAnalysisMap missing _ProbabilityOfPassingADiseaseVariant")
			}

			if (index == 0){
				probabilityOfHavingDisease = currentProbabilityOfHavingDisease
				probabilityOfPassingAVariant = currentProbabilityOfPassingAVariant
				continue
			}

			if (currentProbabilityOfHavingDisease != probabilityOfHavingDisease){
				return true, nil
			}
			if (currentProbabilityOfPassingAVariant != probabilityOfPassingAVariant){
				return true, nil
			}
		}

		// Now we test variants for conflicts

		for _, variantMap := range variantsMapList{

			// Each variant value is either "Yes;No", "No;Yes", "No;No", or "Yes;Yes"

			// Two different genomes have "Yes;No" and "No;Yes", it will not count as a conflict
			// If the locus is unphased, then there is no difference between "Yes;No" and "No;Yes"
			// 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

			genomeHasVariantStatus := ""

			for index, genomeIdentifier := range allGenomeIdentifiersList{

				currentGenomeHasVariantStatus, exists := variantMap[genomeIdentifier + "_HasVariant"]
				if (exists == false){
					return false, errors.New("variantMap missing genomeIdentifier key when checking for conflicts")
				}

				if (index == 0){
					genomeHasVariantStatus = currentGenomeHasVariantStatus
					continue
				}

				if (currentGenomeHasVariantStatus != genomeHasVariantStatus){

					if (currentGenomeHasVariantStatus == "Yes;No" && genomeHasVariantStatus == "No;Yes"){
						continue
					}
					if (currentGenomeHasVariantStatus == "No;Yes" && genomeHasVariantStatus == "Yes;No"){
						continue
					}
					return true, nil
				}
			}
		}

		return false, nil
	}

	conflictExists, err := getConflictExistsBool()
	if (err != nil) { return nil, nil, err }

	conflictExistsString := helpers.ConvertBoolToYesOrNoString(conflictExists)

	diseaseAnalysisMap["ConflictExists"] = conflictExistsString

	return diseaseAnalysisMap, variantsMapList, nil
}



//Outputs:
//	-map[string]string: Polygenic Disease analysis map (contains weight/probability for each genomeIdentifier and number of loci tested)
//	-[]map[string]string: Loci map list (contains locus info for each genomeIdentifier)
//	-error
func getPolygenicDiseaseAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.GenomeWithMetadata, diseaseObject polygenicDiseases.PolygenicDisease)(map[string]string, []map[string]string, error){

	diseaseName := diseaseObject.DiseaseName
	diseaseLociList := diseaseObject.LociList

	lociMapList := make([]map[string]string, 0, len(diseaseLociList))

	// Map Structure: Locus identifier -> Disease Locus object
	locusObjectsMap := make(map[string]polygenicDiseases.DiseaseLocus)

	for _, locusObject := range diseaseLociList{

		locusIdentifier := locusObject.LocusIdentifier

		locusObjectsMap[locusIdentifier] = locusObject

		locusMap := map[string]string{
			"ItemType": "PolygenicDiseaseLocus",
			"LocusIdentifier": locusIdentifier,
			"DiseaseName": diseaseName,
		}

		locusRSID := locusObject.LocusRSID
		locusRiskWeightsMap := locusObject.RiskWeightsMap
		locusOddsRatiosMap := locusObject.OddsRatiosMap

		for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{

			genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier
			genomeMap := genomeWithMetadataObject.GenomeMap

			//Outputs:
			//	-bool: Disease locus info is known
			//	-string: Locus Bases
			//	-int: Genome disease locus risk weight
			//	-bool: Genome disease locus odds ratio known
			//	-float64: Genome disease locus odds ratio
			//	-error
			getGenomeDiseaseLocusInfo := func()(bool, string, int, bool, float64, error){

				basePairValueFound, base1Value, base2Value, _, err := getGenomeLocusBasePair(genomeMap, locusRSID)	
				if (err != nil) { return false, "", 0, false, 0, err }
				if (basePairValueFound == false){
					return false, "", 0, false, 0, nil
				}

				locusBasePair := base1Value + ";" + base2Value

				riskWeight, exists := locusRiskWeightsMap[locusBasePair]
				if (exists == false){
					// This is an unknown base combination
					// We will treat it as a 0 risk weight
					return true, locusBasePair, 0, true, 1, nil
				}

				if (riskWeight == 0){
					return true, locusBasePair, 0, true, 1, nil
				}
		
				oddsRatio, exists := locusOddsRatiosMap[locusBasePair]
				if (exists == false){
					return true, locusBasePair, 0, false, 0, nil
				}
			
				return true, locusBasePair, riskWeight, true, oddsRatio, nil
			}

			diseaseLocusInfoKnown, locusBasePair, locusRiskWeight, locusOddsRatioKnown, locusOddsRatio, err := getGenomeDiseaseLocusInfo()
			if (err != nil) { return nil, nil, err }

			if (diseaseLocusInfoKnown == false){
				
				locusMap[genomeIdentifier + "_LocusBasePair"] = "Unknown"
				locusMap[genomeIdentifier + "_RiskWeight"] = "Unknown"
				locusMap[genomeIdentifier + "_OddsRatio"] = "Unknown"
			} else {

				locusMap[genomeIdentifier + "_LocusBasePair"] = locusBasePair
		
				riskWeightString := helpers.ConvertIntToString(locusRiskWeight)
				
				locusMap[genomeIdentifier + "_RiskWeight"] = riskWeightString

				if (locusOddsRatioKnown == false){
					locusMap[genomeIdentifier + "_OddsRatio"] = "Unknown"
				} else {
					locusOddsRatioString := helpers.ConvertFloat64ToString(locusOddsRatio)
					locusMap[genomeIdentifier + "_OddsRatio"] = locusOddsRatioString
				}
			}
		}

		lociMapList = append(lociMapList, locusMap)
	}

	// Now we construct polygenic disease probability map for each genome

	diseaseAnalysisMap := make(map[string]string)

	// We use this list to check for conflicts later
	allGenomeIdentifiersList := make([]string, 0, len(inputGenomesWithMetadataList))

	for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{

		genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier

		allGenomeIdentifiersList = append(allGenomeIdentifiersList, genomeIdentifier)

		numberOfLociTested := 0

		minimumPossibleRiskWeightSum := 0
		maximumPossibleRiskWeightSum := 0

		summedDiseaseRiskWeight := 0
		
		for _, locusMap := range lociMapList{

			genomeRiskWeight, exists := locusMap[genomeIdentifier + "_RiskWeight"]
			if (exists == false){
				return nil, nil, errors.New("locusMap malformed: Map missing a genomeIdentifier riskWeight")
			}
		
			if (genomeRiskWeight == "Unknown"){
				// The genome does not have this locus
				// We cannot test for risk weight
				continue
			}

			numberOfLociTested += 1

			locusIdentifier, exists := locusMap["LocusIdentifier"]
			if (exists == false) {
				return nil, nil, errors.New("locusMap malformed: Map missing LocusIdentifier")
			}

			locusObject, exists := locusObjectsMap[locusIdentifier]
			if (exists == false){
				return nil, nil, errors.New("LocusObjectsMap missing locus: " + locusIdentifier)
			}

			locusMinimumWeight := locusObject.MinimumRiskWeight
			locusMaximumWeight := locusObject.MaximumRiskWeight

			minimumPossibleRiskWeightSum += locusMinimumWeight
			maximumPossibleRiskWeightSum += locusMaximumWeight

			genomeRiskWeightInt, err := helpers.ConvertStringToInt(genomeRiskWeight)
			if (err != nil) {
				return nil, nil, errors.New("Locus map malformed: Contains invalid _RiskWeight: " + genomeRiskWeight)
			}

			summedDiseaseRiskWeight += genomeRiskWeightInt
		}

		numberOfLociTestedString := helpers.ConvertIntToString(numberOfLociTested)

		diseaseAnalysisMap[genomeIdentifier + "_NumberOfLociTested"] = numberOfLociTestedString

		if (numberOfLociTested == 0){
			diseaseAnalysisMap[genomeIdentifier + "_RiskScore"] = "Unknown"

			continue
		}

		diseaseRiskScore, err := helpers.ScaleNumberProportionally(true, summedDiseaseRiskWeight, minimumPossibleRiskWeightSum, maximumPossibleRiskWeightSum, 0, 10)
		if (err != nil) { return nil, nil, err }

		diseaseRiskScoreString := helpers.ConvertIntToString(diseaseRiskScore)

		diseaseAnalysisMap[genomeIdentifier + "_RiskScore"] = diseaseRiskScoreString
	}

	if (len(allGenomeIdentifiersList) == 1){
		// We do not need to check for conflicts
		// Nothing left to do. Analysis is complete.
		return diseaseAnalysisMap, lociMapList, nil
	}

	// We check for conflicts

	getConflictExistsBool := func()(bool, error){

		for _, locusMap := range lociMapList{

			locusBasePair := ""

			for index, genomeIdentifier := range allGenomeIdentifiersList{

				currentLocusBasePair, exists := locusMap[genomeIdentifier + "_LocusBasePair"]
				if (exists == false){
					return false, errors.New("Cannot find _LocusBasePair key when searching for conflicts")
				}

				if (index == 0){

					locusBasePair = currentLocusBasePair
					continue
				}
				if (currentLocusBasePair != locusBasePair){
					return true, nil
				}
			}
		}

		return false, nil
	}

	conflictExists, err := getConflictExistsBool()
	if (err != nil) { return nil, nil, err }

	conflictExistsString := helpers.ConvertBoolToYesOrNoString(conflictExists)

	diseaseAnalysisMap["ConflictExists"] = conflictExistsString

	return diseaseAnalysisMap, lociMapList, nil
}



//Outputs:
//	-map[string]string: Trait analysis map (contains weight/probability for each genomeIdentifier and number of rules tested)
//	-[]map[string]string: Loci map list (contains locus info for each genomeIdentifier)
//	-error
func getTraitAnalysis(inputGenomesWithMetadataList []prepareRawGenomes.GenomeWithMetadata, traitObject traits.Trait)(map[string]string, []map[string]string, error){

	traitName := traitObject.TraitName
	traitLociList := traitObject.LociList
	traitRulesList := traitObject.RulesList

	// We first add loci values to trait analysis map

	traitAnalysisMap := make(map[string]string)

	// We use this list to check for conflicts later
	allGenomeIdentifiersList := make([]string, 0, len(inputGenomesWithMetadataList))

	for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{

		genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier

		allGenomeIdentifiersList = append(allGenomeIdentifiersList, genomeIdentifier)

		genomeMap := genomeWithMetadataObject.GenomeMap

		for _, locusRSID := range traitLociList{

			locusRSIDString := helpers.ConvertInt64ToString(locusRSID)

			locusBasePairKnown, locusBase1, locusBase2, locusIsPhased, err := getGenomeLocusBasePair(genomeMap, locusRSID)
			if (err != nil) { return nil, nil, err }
			if (locusBasePairKnown == false){

				traitAnalysisMap[genomeIdentifier + "_LocusValue_rs" + locusRSIDString] = "Unknown"
			} else {

				locusBasePair := locusBase1 + ";" + locusBase2

				locusIsPhasedString := helpers.ConvertBoolToYesOrNoString(locusIsPhased)

				traitAnalysisMap[genomeIdentifier + "_LocusValue_rs" + locusRSIDString] = locusBasePair
				traitAnalysisMap[genomeIdentifier + "_LocusIsPhased_rs" + locusRSIDString] = locusIsPhasedString
			}
		}
	}

	// This map stores the TraitRule maps
	rulesMapList := make([]map[string]string, 0, len(traitRulesList))

	// Map Structure: Rule identifier -> Rule object
	ruleObjectsMap := make(map[string]traits.TraitRule)

	if (len(traitRulesList) != 0){

		// This trait contains at least 1 rule

		for _, ruleObject := range traitRulesList{

			ruleIdentifier := ruleObject.RuleIdentifier

			ruleObjectsMap[ruleIdentifier] = ruleObject

			ruleMap := map[string]string{
				"ItemType": "TraitRule",
				"RuleIdentifier": ruleIdentifier,
				"TraitName": traitName,
			}

			ruleLociList := ruleObject.LociList

			for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{

				genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier
				genomeMap := genomeWithMetadataObject.GenomeMap

				// We add locus base pairs to ruleMap
				// We also check to see if genome passes all rule loci
				// We only consider a rule Known if the genome either passes all loci, or fails to pass 1 locus

				allRuleLociKnown := true
				anyLocusFailureKnown := false //This is true if at least 1 locus is known to not pass

				for _, locusObject := range ruleLociList{

					locusIdentifier := locusObject.LocusIdentifier
					locusRSID := locusObject.LocusRSID

					locusBasePairKnown, locusBase1, locusBase2, _, err := getGenomeLocusBasePair(genomeMap, locusRSID)
					if (err != nil) { return nil, nil, err }
					if (locusBasePairKnown == false){

						ruleMap[genomeIdentifier + "_RuleLocusBasePair_" + locusIdentifier] = "Unknown"

						// The genome has failed to pass a single rule locus, thus, the rule is not passed
						// We still continue so we can add all locus base pairs to the ruleMap
						allRuleLociKnown = false
						continue
					}

					locusBasePair := locusBase1 + ";" + locusBase2

					ruleMap[genomeIdentifier + "_RuleLocusBasePair_" + locusIdentifier] = locusBasePair

					if (anyLocusFailureKnown == true){
						// We don't have to check if the rule locus is passed, because we already know the rule is not passed
						continue
					}

					locusBasePairsList := locusObject.BasePairsList

					genomePassesRuleLocus := slices.Contains(locusBasePairsList, locusBasePair)
					if (genomePassesRuleLocus == false){
						// We know the rule is not passed
						// We still continue so we can add all locus base pairs to the ruleMap
						anyLocusFailureKnown = true
						continue
					}
				}

				if (anyLocusFailureKnown == true){

					ruleMap[genomeIdentifier + "_PassesRule"] = "No"

				} else if (allRuleLociKnown == false){

					ruleMap[genomeIdentifier + "_PassesRule"] = "Unknown"
				} else {

					ruleMap[genomeIdentifier + "_PassesRule"] = "Yes"
				}
			}

			rulesMapList = append(rulesMapList, ruleMap)
		}

		// Now we construct trait outcome scores map for each genome

		traitOutcomesList := traitObject.OutcomesList

		for _, genomeWithMetadataObject := range inputGenomesWithMetadataList{

			genomeIdentifier := genomeWithMetadataObject.GenomeIdentifier

			// A rule is considered tested if at least 1 locus within the rule is known to fail, or all loci within the rule pass
			numberOfRulesTested := 0

			// Map Structure: Trait outcome -> Number of points
			traitOutcomeScoresMap := make(map[string]int)

			for _, ruleMap := range rulesMapList{

				genomePassesRule, exists := ruleMap[genomeIdentifier + "_PassesRule"]
				if (exists == false){
					return nil, nil, errors.New("ruleMap malformed: Map missing a genomeIdentifier _PassesRule")
				}

				if (genomePassesRule == "Unknown"){
					continue
				}

				numberOfRulesTested += 1

				if (genomePassesRule == "No"){
					continue
				}

				ruleIdentifier, exists := ruleMap["RuleIdentifier"]
				if (exists == false) {
					return nil, nil, errors.New("ruleMap malformed: Map missing RuleIdentifier")
				}

				ruleObject, exists := ruleObjectsMap[ruleIdentifier]
				if (exists == false){
					return nil, nil, errors.New("RuleObjectsMap missing rule: " + ruleIdentifier)
				}

				ruleOutcomePointsMap := ruleObject.OutcomePointsMap

				for traitOutcome, pointsChange := range ruleOutcomePointsMap{

					traitOutcomeScoresMap[traitOutcome] += pointsChange
				}
			}

			numberOfRulesTestedString := helpers.ConvertIntToString(numberOfRulesTested)

			traitAnalysisMap[genomeIdentifier + "_NumberOfRulesTested"] = numberOfRulesTestedString

			if (numberOfRulesTested == 0){
				// No rules were tested. The number of points in each outcome are all unknown.
				continue
			}

			// We add all outcomes for which there were no points

			for _, traitOutcome := range traitOutcomesList{

				_, exists := traitOutcomeScoresMap[traitOutcome]
				if (exists == false){
					traitOutcomeScoresMap[traitOutcome] = 0
				}
			}

			for traitOutcome, outcomeScore := range traitOutcomeScoresMap{

				outcomeScoreString := helpers.ConvertIntToString(outcomeScore)

				traitAnalysisMap[genomeIdentifier + "_OutcomeScore_" + traitOutcome] = outcomeScoreString
			}
		}
	} else {

		// No rules exist for this trait

		for _, genomeIdentifier := range allGenomeIdentifiersList{

			traitAnalysisMap[genomeIdentifier + "_NumberOfRulesTested"] = "0"
		}
	}

	if (len(allGenomeIdentifiersList) == 1){
		// We do not need to check for conflicts
		// Nothing left to do. Analysis is complete.
		return traitAnalysisMap, rulesMapList, nil
	}

	// We check for conflicts

	getConflictExistsBool := func()(bool, error){

		//TODO: Check for locus value conflicts once locus values are used in neural network prediction.

		// We only have to check each rule result, because they will determine the overall person results

		for _, ruleMap := range rulesMapList{

			passesRule := ""

			for index, genomeIdentifier := range allGenomeIdentifiersList{

				currentPassesRule, exists := ruleMap[genomeIdentifier + "_PassesRule"]
				if (exists == false){
					return false, errors.New("Cannot find _PassesRule key when searching for conflicts")
				}

				if (index == 0){

					passesRule = currentPassesRule
					continue
				}
				if (currentPassesRule != passesRule){
					return true, nil
				}
			}
		}

		return false, nil
	}

	conflictExists, err := getConflictExistsBool()
	if (err != nil) { return nil, nil, err }

	conflictExistsString := helpers.ConvertBoolToYesOrNoString(conflictExists)

	traitAnalysisMap["ConflictExists"] = conflictExistsString

	return traitAnalysisMap, rulesMapList, nil
}