Examples with BinomialTest org.apache.commons.math3.stat.inference.BinomialTest used on opensource projects

Example 1 with BinomialTest

use of org.apache.commons.math3.stat.inference.BinomialTest in project gatk-protected by broadinstitute.

the class HetPulldownCalculator method isPileupHetCompatible.

/**
     * Returns true if the distribution of major and other base-pair counts from a pileup at a locus is compatible with
     * allele fraction of 0.5.
     *
     * <p>
     *     Compatibility is defined by a p-value threshold.  That is, compute the two-sided p-value of observing
     *     a number of major read counts out of a total number of reads, assuming the given heterozygous
     *     allele fraction.  If the p-value is less than the given threshold, then reject the null hypothesis
     *     that the heterozygous allele fraction is 0.5 (i.e., SNP is likely to be homozygous) and return false,
     *     otherwise return true.
     * </p>
     * @param baseCounts        base-pair counts
     * @param totalBaseCount    total base-pair counts (excluding N, etc.)
     * @param pvalThreshold     p-value threshold for two-sided binomial test (should be in [0, 1], but no check is performed)
     * @return                  boolean compatibility with heterozygous allele fraction
     */
@VisibleForTesting
protected static boolean isPileupHetCompatible(final Nucleotide.Counter baseCounts, final int totalBaseCount, final double pvalThreshold) {
    final int majorReadCount = Arrays.stream(BASES).mapToInt(b -> (int) baseCounts.get(b)).max().getAsInt();
    if (majorReadCount == 0 || totalBaseCount - majorReadCount == 0) {
        return false;
    }
    final double pval = new BinomialTest().binomialTest(totalBaseCount, majorReadCount, HET_ALLELE_FRACTION, AlternativeHypothesis.TWO_SIDED);
    return pval >= pvalThreshold;
}

Example 2 with BinomialTest

use of org.apache.commons.math3.stat.inference.BinomialTest in project gatk by broadinstitute.

the class HetPulldownCalculator method isPileupHetCompatible.

/**
     * Returns true if the distribution of major and other base-pair counts from a pileup at a locus is compatible with
     * allele fraction of 0.5.
     *
     * <p>
     *     Compatibility is defined by a p-value threshold.  That is, compute the two-sided p-value of observing
     *     a number of major read counts out of a total number of reads, assuming the given heterozygous
     *     allele fraction.  If the p-value is less than the given threshold, then reject the null hypothesis
     *     that the heterozygous allele fraction is 0.5 (i.e., SNP is likely to be homozygous) and return false,
     *     otherwise return true.
     * </p>
     * @param baseCounts        base-pair counts
     * @param totalBaseCount    total base-pair counts (excluding N, etc.)
     * @param pvalThreshold     p-value threshold for two-sided binomial test (should be in [0, 1], but no check is performed)
     * @return                  boolean compatibility with heterozygous allele fraction
     */
@VisibleForTesting
protected static boolean isPileupHetCompatible(final Nucleotide.Counter baseCounts, final int totalBaseCount, final double pvalThreshold) {
    final int majorReadCount = Arrays.stream(BASES).mapToInt(b -> (int) baseCounts.get(b)).max().getAsInt();
    if (majorReadCount == 0 || totalBaseCount - majorReadCount == 0) {
        return false;
    }
    final double pval = new BinomialTest().binomialTest(totalBaseCount, majorReadCount, HET_ALLELE_FRACTION, AlternativeHypothesis.TWO_SIDED);
    return pval >= pvalThreshold;
}