Java Code Examples for org.apache.commons.lang3.mutable.MutableDouble#getValue()

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Example 1
Source File: GermlineFilter.java    From gatk with BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up 
private double computeMinorAlleleFraction(final VariantContext vc, final Mutect2FilteringEngine filteringEngine, final int[] alleleCounts) {
    final MutableDouble weightedSumOfMafs = new MutableDouble(0);
    vc.getGenotypes().stream().filter(filteringEngine::isTumor).forEach(tumorGenotype -> {
        final String sample = tumorGenotype.getSampleName();
        final List<MinorAlleleFractionRecord> segments = tumorSegments.containsKey(sample) ? tumorSegments.get(sample).getOverlaps(vc).stream().collect(Collectors.toList())
                : Collections.emptyList();

        // minor allele fraction -- we abbreviate the name to make the formulas below less cumbersome
        final double maf = segments.isEmpty() ? 0.5 : segments.get(0).getMinorAlleleFraction();

        weightedSumOfMafs.add(maf * MathUtils.sum(tumorGenotype.getAD()));
    });


    // weighted average of sample minor allele fractions.  This is the expected allele fraction of a germline het in the aggregated read counts
    return weightedSumOfMafs.getValue() / MathUtils.sum(alleleCounts);
}
Example 2
Source File: ThresholdCalculator.java    From gatk with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
/**
 * Compute the filtering threshold that maximizes the F_beta score
 *
 * @param posteriors A list of posterior probabilities, which gets sorted
 * @param beta relative weight of recall to precision
 */
@VisibleForTesting
static double calculateThresholdBasedOnOptimalFScore(final List<Double> posteriors, final double beta){
    ParamUtils.isPositiveOrZero(beta, "requested F-score beta must be non-negative");

    Collections.sort(posteriors);

    final double expectedTruePositives = posteriors.stream()
            .mapToDouble(prob -> 1 - prob).sum();


    // starting from filtering everything (threshold = 0) increase the threshold to maximize the F score
    final MutableDouble truePositives = new MutableDouble(0);
    final MutableDouble falsePositives = new MutableDouble(0);
    final MutableDouble falseNegatives = new MutableDouble(expectedTruePositives);
    int optimalIndexInclusive = -1; // include all indices up to and including this. -1 mean filter all.
    double optimalFScore = 0;   // if you exclude everything, recall is zero

    final int N = posteriors.size();

    for (int n = 0; n < N; n++){
        truePositives.add(1 - posteriors.get(n));
        falsePositives.add(posteriors.get(n));
        falseNegatives.subtract(1 - posteriors.get(n));
        final double F = (1+beta*beta)*truePositives.getValue() /
                ((1+beta*beta)*truePositives.getValue() + beta*beta*falseNegatives.getValue() + falsePositives.getValue());
        if (F >= optimalFScore) {
            optimalIndexInclusive = n;
            optimalFScore = F;
        }
    }

    return optimalIndexInclusive == -1 ? 0 : (optimalIndexInclusive == N - 1 ? 1 : posteriors.get(optimalIndexInclusive));
}