- Genotype assignment in case of equally likeli combination is now random
- Genotype combinations with 0 confidence are now left unphased
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@ -109,6 +109,9 @@ public class PhaseByTransmission extends RodWalker<HashMap<Byte,Integer>, HashMa
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private final Byte NUM_HET_HET_HET = 4;
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private final Byte NUM_VIOLATIONS = 5;
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//Random number generator
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private Random rand = new Random();
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private enum FamilyMember {
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MOTHER,
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FATHER,
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@ -309,17 +312,22 @@ public class PhaseByTransmission extends RodWalker<HashMap<Byte,Integer>, HashMa
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private Genotype getPhasedGenotype(Allele refAllele, Allele altAllele, Genotype genotype, double transmissionProb, Genotype phasedGenotype){
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int phredScoreTransmission = -1;
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if(transmissionProb != NO_TRANSMISSION_PROB)
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phredScoreTransmission = MathUtils.probabilityToPhredScale(1-(transmissionProb));
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//Handle null, missing and unavailable genotypes
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//Note that only cases where a null/missing/unavailable genotype was passed in the first place can lead to a null/missing/unavailable
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//genotype so it is safe to return the original genotype in this case.
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if(genotype == null || !phasedGenotype.isAvailable() || phasedGenotype.isNoCall())
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//In addition, if the phasing confidence is 0, then return the unphased, original genotypes.
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if(phredScoreTransmission ==0 || genotype == null || !phasedGenotype.isAvailable() || phasedGenotype.isNoCall())
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return genotype;
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//Add the transmission probability
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Map<String, Object> genotypeAttributes = new HashMap<String, Object>();
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genotypeAttributes.putAll(genotype.getAttributes());
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if(transmissionProb>NO_TRANSMISSION_PROB)
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genotypeAttributes.put(TRANSMISSION_PROBABILITY_TAG_NAME, MathUtils.probabilityToPhredScale(1-(transmissionProb)));
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genotypeAttributes.put(TRANSMISSION_PROBABILITY_TAG_NAME, phredScoreTransmission);
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ArrayList<Allele> phasedAlleles = new ArrayList<Allele>(2);
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for(Allele allele : phasedGenotype.getAlleles()){
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@ -538,36 +546,46 @@ public class PhaseByTransmission extends RodWalker<HashMap<Byte,Integer>, HashMa
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//Prior vars
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double bestConfigurationLikelihood = 0.0;
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double norm = 0.0;
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boolean isMV = false;
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int bestConfigurationGenotypeDiffs=4;
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Genotype.Type bestMotherGenotype = getTypeSafeNull(mother);
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Genotype.Type bestFatherGenotype = getTypeSafeNull(father);
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Genotype.Type bestChildGenotype = getTypeSafeNull(child);
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int configuration_index =0;
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ArrayList<Boolean> isMV = new ArrayList<Boolean>();
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isMV.add(false);
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ArrayList<Genotype.Type> bestMotherGenotype = new ArrayList<Genotype.Type>();
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bestMotherGenotype.add(getTypeSafeNull(mother));
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ArrayList<Genotype.Type> bestFatherGenotype = new ArrayList<Genotype.Type>();
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bestFatherGenotype.add(getTypeSafeNull(father));
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ArrayList<Genotype.Type> bestChildGenotype = new ArrayList<Genotype.Type>();
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bestChildGenotype.add(getTypeSafeNull(child));
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//Get the most likely combination
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//Only check for most likely combination if at least a parent and the child have genotypes
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if(childLikelihoods.size()>2 && (motherLikelihoods.size() + fatherLikelihoods.size())>3){
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int mvCount;
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double configurationLikelihood;
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int configurationGenotypeDiffs;
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for(Map.Entry<Genotype.Type,Double> motherGenotype : motherLikelihoods.entrySet()){
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for(Map.Entry<Genotype.Type,Double> fatherGenotype : fatherLikelihoods.entrySet()){
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for(Map.Entry<Genotype.Type,Double> childGenotype : childLikelihoods.entrySet()){
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mvCount = mvCountMatrix.get(motherGenotype.getKey()).get(fatherGenotype.getKey()).get(childGenotype.getKey());
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configurationLikelihood = mvCount>0 ? Math.pow(deNovoPrior,mvCount)*motherGenotype.getValue()*fatherGenotype.getValue()*childGenotype.getValue() : (1.0-11*deNovoPrior)*motherGenotype.getValue()*fatherGenotype.getValue()*childGenotype.getValue();
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norm += configurationLikelihood;
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configurationGenotypeDiffs = countFamilyGenotypeDiff(mother.getType(),father.getType(),child.getType(),motherGenotype.getKey(),fatherGenotype.getKey(),childGenotype.getKey());
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//Keep this combination if
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//It has a better likelihood
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//Or it has the same likelihood but requires less changes from original genotypes
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if ((configurationLikelihood > bestConfigurationLikelihood) ||
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(configurationLikelihood == bestConfigurationLikelihood && configurationGenotypeDiffs < bestConfigurationGenotypeDiffs)) {
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if (configurationLikelihood > bestConfigurationLikelihood){
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bestConfigurationLikelihood = configurationLikelihood;
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bestMotherGenotype = motherGenotype.getKey();
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bestFatherGenotype = fatherGenotype.getKey();
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bestChildGenotype = childGenotype.getKey();
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isMV = mvCount>0;
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bestConfigurationGenotypeDiffs=configurationGenotypeDiffs;
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isMV.clear();
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isMV.add(mvCount>0);
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bestMotherGenotype.clear();
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bestMotherGenotype.add(motherGenotype.getKey());
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bestFatherGenotype.clear();
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bestFatherGenotype.add(fatherGenotype.getKey());
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bestChildGenotype.clear();
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bestChildGenotype.add(childGenotype.getKey());
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}
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else if(configurationLikelihood == bestConfigurationLikelihood) {
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bestMotherGenotype.add(motherGenotype.getKey());
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bestFatherGenotype.add(fatherGenotype.getKey());
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bestChildGenotype.add(childGenotype.getKey());
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isMV.add(mvCount>0);
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}
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}
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}
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@ -575,17 +593,22 @@ public class PhaseByTransmission extends RodWalker<HashMap<Byte,Integer>, HashMa
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//normalize the best configuration probability
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bestConfigurationLikelihood = bestConfigurationLikelihood / norm;
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//In case of multiple equally likely combinations, take a random one
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if(bestMotherGenotype.size()>1){
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configuration_index = rand.nextInt(bestMotherGenotype.size()-1);
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}
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}
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else{
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bestConfigurationLikelihood = NO_TRANSMISSION_PROB;
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}
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//Get the phased alleles for the genotype configuration
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TrioPhase phasedTrioGenotypes = transmissionMatrix.get(bestMotherGenotype).get(bestFatherGenotype).get(bestChildGenotype);
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TrioPhase phasedTrioGenotypes = transmissionMatrix.get(bestMotherGenotype.get(configuration_index)).get(bestFatherGenotype.get(configuration_index)).get(bestChildGenotype.get(configuration_index));
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//Return the phased genotypes
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phasedTrioGenotypes.getPhasedGenotypes(ref,alt,mother,father,child,bestConfigurationLikelihood,finalGenotypes);
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return isMV;
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//Return the phased genotypes
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phasedTrioGenotypes.getPhasedGenotypes(ref,alt,mother,father,child,bestConfigurationLikelihood,finalGenotypes);
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return isMV.get(configuration_index);
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}
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