Examples with ReadCountCollection org.broadinstitute.hellbender.tools.exome.ReadCountCollection used on opensource projects

Example 11 with ReadCountCollection

use of org.broadinstitute.hellbender.tools.exome.ReadCountCollection in project gatk-protected by broadinstitute.

the class CoveragePoNQCUtils method getContigToMedianCRMap.

@VisibleForTesting
static Map<String, Double> getContigToMedianCRMap(final ReadCountCollection readCountCollection) {
    final List<String> allContigsPresent = retrieveAllContigsPresent(readCountCollection);
    final Map<String, Double> contigToMedian = new LinkedHashMap<>();
    for (String contig : allContigsPresent) {
        final ReadCountCollection oneContigReadCountCollection = readCountCollection.subsetTargets(readCountCollection.targets().stream().filter(t -> t.getContig().equals(contig)).collect(Collectors.toSet()));
        final double[] flatCounts = Doubles.concat(oneContigReadCountCollection.counts().getData());
        // Put into CRSpace
        final double[] flatCountsInCRSpace = DoubleStream.of(flatCounts).map(d -> Math.pow(2, d)).toArray();
        contigToMedian.put(contig, new Median().evaluate(flatCountsInCRSpace));
    }
    return contigToMedian;
}

Example 12 with ReadCountCollection

use of org.broadinstitute.hellbender.tools.exome.ReadCountCollection in project gatk-protected by broadinstitute.

the class PCATangentNormalizationUtils method tangentNormalizeNonSpark.

/**
     * Tangent normalize given the raw PoN data without using Spark.
     */
private static PCATangentNormalizationResult tangentNormalizeNonSpark(final ReadCountCollection targetFactorNormalizedCounts, final RealMatrix reducedPanelCounts, final RealMatrix reducedPanelPInvCounts, final CaseToPoNTargetMapper targetMapper, final RealMatrix tangentNormalizationInputCounts) {
    // Calculate the beta-hats for the input read count columns (samples).
    logger.info("Calculating beta hats...");
    final RealMatrix tangentBetaHats = calculateBetaHats(reducedPanelPInvCounts, tangentNormalizationInputCounts, EPSILON);
    // Actual tangent normalization step.
    logger.info("Performing actual tangent normalization (" + tangentNormalizationInputCounts.getColumnDimension() + " columns)...");
    final RealMatrix tangentNormalizedCounts = tangentNormalize(reducedPanelCounts, tangentNormalizationInputCounts, tangentBetaHats);
    // Output the tangent normalized counts.
    logger.info("Post-processing tangent normalization results...");
    final ReadCountCollection tangentNormalized = targetMapper.fromPoNtoCaseCountCollection(tangentNormalizedCounts, targetFactorNormalizedCounts.columnNames());
    final ReadCountCollection preTangentNormalized = targetMapper.fromPoNtoCaseCountCollection(tangentNormalizationInputCounts, targetFactorNormalizedCounts.columnNames());
    return new PCATangentNormalizationResult(tangentNormalized, preTangentNormalized, tangentBetaHats, targetFactorNormalizedCounts);
}

Example 13 with ReadCountCollection

use of org.broadinstitute.hellbender.tools.exome.ReadCountCollection in project gatk by broadinstitute.

the class GCCorrector method correctCoverage.

/**
     *
     * @param inputCounts raw coverage before GC correction
     * @param gcContentByTarget      array of gc contents, one per target of the input
     * @return              GC-corrected coverage
     */
public static ReadCountCollection correctCoverage(final ReadCountCollection inputCounts, final double[] gcContentByTarget) {
    // each column (sample) has its own GC bias curve, hence its own GC corrector
    final List<GCCorrector> gcCorrectors = IntStream.range(0, inputCounts.columnNames().size()).mapToObj(n -> new GCCorrector(gcContentByTarget, inputCounts.counts().getColumnVector(n))).collect(Collectors.toList());
    // gc correct a copy of the input counts in-place
    final RealMatrix correctedCounts = inputCounts.counts().copy();
    correctedCounts.walkInOptimizedOrder(new DefaultRealMatrixChangingVisitor() {

        @Override
        public double visit(int target, int column, double coverage) {
            return gcCorrectors.get(column).correctedCoverage(coverage, gcContentByTarget[target]);
        }
    });
    // we would like the average correction factor to be 1.0 in the sense that average coverage before and after
    // correction should be equal
    final double[] columnNormalizationFactors = IntStream.range(0, inputCounts.columnNames().size()).mapToDouble(c -> inputCounts.counts().getColumnVector(c).getL1Norm() / correctedCounts.getColumnVector(c).getL1Norm()).toArray();
    correctedCounts.walkInOptimizedOrder(new DefaultRealMatrixChangingVisitor() {

        @Override
        public double visit(int target, int column, double coverage) {
            return coverage * columnNormalizationFactors[column];
        }
    });
    return new ReadCountCollection(inputCounts.targets(), inputCounts.columnNames(), correctedCounts);
}

Example 14 with ReadCountCollection

use of org.broadinstitute.hellbender.tools.exome.ReadCountCollection in project gatk by broadinstitute.

the class CoveragePoNQCUtils method hasSuspiciousContigs.

/**
     *  Given a single sample tangent normalization (or other coverage profile), determine whether any contig looks like
     *   it has an arm level event (defined as 25% (or more) of the contig amplified/deleted)
     *
     * @param singleSampleTangentNormalized Tangent normalized data for a single sample.
     * @return never {@code null}
     */
private static Boolean hasSuspiciousContigs(final ReadCountCollection singleSampleTangentNormalized, final Map<String, Double> contigToMedian) {
    final List<String> allContigsPresent = retrieveAllContigsPresent(singleSampleTangentNormalized);
    for (String contig : allContigsPresent) {
        final ReadCountCollection oneContigReadCountCollection = singleSampleTangentNormalized.subsetTargets(singleSampleTangentNormalized.targets().stream().filter(t -> t.getContig().equals(contig)).collect(Collectors.toSet()));
        final RealVector counts = oneContigReadCountCollection.counts().getColumnVector(0);
        for (int i = 0; i < 4; i++) {
            final RealVector partitionCounts = counts.getSubVector(i * counts.getDimension() / 4, counts.getDimension() / 4);
            final double[] partitionArray = DoubleStream.of(partitionCounts.toArray()).map(d -> Math.pow(2, d)).sorted().toArray();
            double median = new Median().evaluate(partitionArray);
            final double medianShiftInCRSpace = contigToMedian.getOrDefault(contig, 1.0) - 1.0;
            median -= medianShiftInCRSpace;
            if ((median > AMP_THRESHOLD) || (median < DEL_THRESHOLD)) {
                logger.info("Suspicious contig: " + singleSampleTangentNormalized.columnNames().get(0) + " " + contig + " (" + median + " -- " + i + ")");
                return true;
            }
        }
    }
    return false;
}

Example 15 with ReadCountCollection

use of org.broadinstitute.hellbender.tools.exome.ReadCountCollection in project gatk by broadinstitute.

the class CoveragePoNQCUtils method getContigToMedianCRMap.

@VisibleForTesting
static Map<String, Double> getContigToMedianCRMap(final ReadCountCollection readCountCollection) {
    final List<String> allContigsPresent = retrieveAllContigsPresent(readCountCollection);
    final Map<String, Double> contigToMedian = new LinkedHashMap<>();
    for (String contig : allContigsPresent) {
        final ReadCountCollection oneContigReadCountCollection = readCountCollection.subsetTargets(readCountCollection.targets().stream().filter(t -> t.getContig().equals(contig)).collect(Collectors.toSet()));
        final double[] flatCounts = Doubles.concat(oneContigReadCountCollection.counts().getData());
        // Put into CRSpace
        final double[] flatCountsInCRSpace = DoubleStream.of(flatCounts).map(d -> Math.pow(2, d)).toArray();
        contigToMedian.put(contig, new Median().evaluate(flatCountsInCRSpace));
    }
    return contigToMedian;
}