Examples with FeatureContext org.broadinstitute.hellbender.engine.FeatureContext used on opensource projects

Example 16 with FeatureContext

use of org.broadinstitute.hellbender.engine.FeatureContext in project gatk by broadinstitute.

the class GenotypingEngine method calculateGenotypes.

/**
     * Main entry function to calculate genotypes of a given VC with corresponding GL's that is shared across genotypers (namely UG and HC).
     *
     * @param features                           Features
     * @param refContext                         Reference context
     * @param rawContext                         Raw context
     * @param stratifiedContexts                 Stratified alignment contexts
     * @param vc                                 Input VC
     * @param model                              GL calculation model
     * @param inheritAttributesFromInputVC       Output VC will contain attributes inherited from input vc
     * @return                                   VC with assigned genotypes
     */
protected VariantCallContext calculateGenotypes(final FeatureContext features, final ReferenceContext refContext, final AlignmentContext rawContext, Map<String, AlignmentContext> stratifiedContexts, final VariantContext vc, final GenotypeLikelihoodsCalculationModel model, final boolean inheritAttributesFromInputVC, final ReadLikelihoods<Allele> likelihoods, final SAMFileHeader header) {
    final boolean limitedContext = features == null || refContext == null || rawContext == null || stratifiedContexts == null;
    // if input VC can't be genotyped, exit with either null VCC or, in case where we need to emit all sites, an empty call
    if (hasTooManyAlternativeAlleles(vc) || vc.getNSamples() == 0) {
        return emptyCallContext(features, refContext, rawContext, header);
    }
    final int defaultPloidy = configuration.genotypeArgs.samplePloidy;
    final int maxAltAlleles = configuration.genotypeArgs.MAX_ALTERNATE_ALLELES;
    VariantContext reducedVC = vc;
    if (maxAltAlleles < vc.getAlternateAlleles().size()) {
        final List<Allele> allelesToKeep = AlleleSubsettingUtils.calculateMostLikelyAlleles(vc, defaultPloidy, maxAltAlleles);
        final GenotypesContext reducedGenotypes = allelesToKeep.size() == 1 ? GATKVariantContextUtils.subsetToRefOnly(vc, defaultPloidy) : AlleleSubsettingUtils.subsetAlleles(vc.getGenotypes(), defaultPloidy, vc.getAlleles(), allelesToKeep, GenotypeAssignmentMethod.SET_TO_NO_CALL, vc.getAttributeAsInt(VCFConstants.DEPTH_KEY, 0));
        reducedVC = new VariantContextBuilder(vc).alleles(allelesToKeep).genotypes(reducedGenotypes).make();
    }
    final AFCalculator afCalculator = configuration.genotypeArgs.USE_NEW_AF_CALCULATOR ? newAFCalculator : afCalculatorProvider.getInstance(vc, defaultPloidy, maxAltAlleles);
    final AFCalculationResult AFresult = afCalculator.getLog10PNonRef(reducedVC, defaultPloidy, maxAltAlleles, getAlleleFrequencyPriors(vc, defaultPloidy, model));
    final OutputAlleleSubset outputAlternativeAlleles = calculateOutputAlleleSubset(AFresult, vc);
    // posterior probability that at least one alt allele exists in the samples
    final double probOfAtLeastOneAltAllele = Math.pow(10, AFresult.getLog10PosteriorOfAFGT0());
    // note the math.abs is necessary because -10 * 0.0 => -0.0 which isn't nice
    final double log10Confidence = !outputAlternativeAlleles.siteIsMonomorphic || configuration.genotypingOutputMode == GenotypingOutputMode.GENOTYPE_GIVEN_ALLELES || configuration.annotateAllSitesWithPLs ? AFresult.getLog10PosteriorOfAFEq0() + 0.0 : AFresult.getLog10PosteriorOfAFGT0() + 0.0;
    // Add 0.0 removes -0.0 occurrences.
    final double phredScaledConfidence = (-10.0 * log10Confidence) + 0.0;
    // skip this if we are already looking at a vc with NON_REF as the first alt allele i.e. if we are in GenotypeGVCFs
    if (!passesEmitThreshold(phredScaledConfidence, outputAlternativeAlleles.siteIsMonomorphic) && !forceSiteEmission() && noAllelesOrFirstAlleleIsNotNonRef(outputAlternativeAlleles.alleles)) {
        // technically, at this point our confidence in a reference call isn't accurately estimated
        //  because it didn't take into account samples with no data, so let's get a better estimate
        final double[] AFpriors = getAlleleFrequencyPriors(vc, defaultPloidy, model);
        final int INDEX_FOR_AC_EQUALS_1 = 1;
        return limitedContext ? null : estimateReferenceConfidence(vc, stratifiedContexts, AFpriors[INDEX_FOR_AC_EQUALS_1], true, probOfAtLeastOneAltAllele);
    }
    // start constructing the resulting VC
    final List<Allele> outputAlleles = outputAlternativeAlleles.outputAlleles(vc.getReference());
    final VariantContextBuilder builder = new VariantContextBuilder(callSourceString(), vc.getContig(), vc.getStart(), vc.getEnd(), outputAlleles);
    builder.log10PError(log10Confidence);
    if (!passesCallThreshold(phredScaledConfidence)) {
        builder.filter(GATKVCFConstants.LOW_QUAL_FILTER_NAME);
    }
    // create the genotypes
    //TODO: omit subsetting if output alleles is not a proper subset of vc.getAlleles
    final GenotypesContext genotypes = outputAlleles.size() == 1 ? GATKVariantContextUtils.subsetToRefOnly(vc, defaultPloidy) : AlleleSubsettingUtils.subsetAlleles(vc.getGenotypes(), defaultPloidy, vc.getAlleles(), outputAlleles, GenotypeAssignmentMethod.USE_PLS_TO_ASSIGN, vc.getAttributeAsInt(VCFConstants.DEPTH_KEY, 0));
    // calculating strand bias involves overwriting data structures, so we do it last
    final Map<String, Object> attributes = composeCallAttributes(inheritAttributesFromInputVC, vc, rawContext, stratifiedContexts, features, refContext, outputAlternativeAlleles.alternativeAlleleMLECounts(), outputAlternativeAlleles.siteIsMonomorphic, AFresult, outputAlternativeAlleles.outputAlleles(vc.getReference()), genotypes, model, likelihoods);
    VariantContext vcCall = builder.genotypes(genotypes).attributes(attributes).make();
    if (annotationEngine != null && !limitedContext) {
        // limitedContext callers need to handle annotations on their own by calling their own annotationEngine
        // Note: we want to use the *unfiltered* and *unBAQed* context for the annotations
        final ReadPileup pileup = rawContext.getBasePileup();
        stratifiedContexts = AlignmentContext.splitContextBySampleName(pileup, header);
        vcCall = annotationEngine.annotateContext(vcCall, features, refContext, likelihoods, a -> true);
    }
    // then we may need to trim the alleles (because the original VariantContext may have had to pad at the end).
    if (// limitedContext callers need to handle allele trimming on their own to keep their alleles in sync
    outputAlleles.size() != vc.getAlleles().size() && !limitedContext) {
        vcCall = GATKVariantContextUtils.reverseTrimAlleles(vcCall);
    }
    return new VariantCallContext(vcCall, confidentlyCalled(phredScaledConfidence, probOfAtLeastOneAltAllele));
}