Examples with GammaDistribution org.apache.commons.math3.distribution.GammaDistribution used on opensource projects

Example 6 with GammaDistribution

use of org.apache.commons.math3.distribution.GammaDistribution in project gatk by broadinstitute.

the class JointAFCRSegmenterUnitTest method testSegmentation.

@Test
public void testSegmentation() {
    final RandomGenerator rng = RandomGeneratorFactory.createRandomGenerator(new Random(563));
    // probability that a datum is a het i.e. #hets / (#hets + #targets)
    final double hetProportion = 0.25;
    final List<Double> trueWeights = Arrays.asList(0.2, 0.5, 0.3);
    final double[] trueMinorAlleleFractions = new double[] { 0.12, 0.32, 0.5 };
    final double[] trueLog2CopyRatios = new double[] { -2.0, 0.0, 1.7 };
    final List<AFCRHiddenState> trueJointStates = IntStream.range(0, trueLog2CopyRatios.length).mapToObj(n -> new AFCRHiddenState(trueMinorAlleleFractions[n], trueLog2CopyRatios[n])).collect(Collectors.toList());
    final double trueMemoryLength = 1e5;
    final double trueCauchyWidth = 0.2;
    final int initialNumCRStates = 20;
    final int initialNumAFStates = 20;
    final AlleleFractionGlobalParameters trueAFParams = new AlleleFractionGlobalParameters(1.0, 0.01, 0.01);
    final JointAFCRHMM trueJointModel = new JointAFCRHMM(trueJointStates, trueWeights, trueMemoryLength, trueAFParams, AllelicPanelOfNormals.EMPTY_PON, trueCauchyWidth);
    // generate joint truth
    final int chainLength = 10000;
    final List<SimpleInterval> positions = CopyRatioSegmenterUnitTest.randomPositions("chr1", chainLength, rng, trueMemoryLength / 4);
    final List<Integer> trueHiddenStates = trueJointModel.generateHiddenStateChain(positions);
    final List<AFCRHiddenState> trueAFCRSequence = trueHiddenStates.stream().map(trueJointModel::getHiddenStateValue).collect(Collectors.toList());
    final double[] trueCopyRatioSequence = trueAFCRSequence.stream().mapToDouble(AFCRHiddenState::getLog2CopyRatio).toArray();
    final double[] trueAlleleFractionSequence = trueAFCRSequence.stream().mapToDouble(AFCRHiddenState::getMinorAlleleFraction).toArray();
    // generate separate af and cr data
    final GammaDistribution biasGenerator = AlleleFractionSegmenterUnitTest.getGammaDistribution(trueAFParams, rng);
    final double outlierProbability = trueAFParams.getOutlierProbability();
    final AllelicCountCollection afData = new AllelicCountCollection();
    final List<Double> crData = new ArrayList<>();
    final List<Target> crTargets = new ArrayList<>();
    for (int n = 0; n < positions.size(); n++) {
        final SimpleInterval position = positions.get(n);
        final AFCRHiddenState jointState = trueAFCRSequence.get(n);
        final double minorFraction = jointState.getMinorAlleleFraction();
        final double log2CopyRatio = jointState.getLog2CopyRatio();
        if (rng.nextDouble() < hetProportion) {
            // het datum
            afData.add(AlleleFractionSegmenterUnitTest.generateAllelicCount(minorFraction, position, rng, biasGenerator, outlierProbability));
        } else {
            //target datum
            crTargets.add(new Target(position));
            crData.add(CopyRatioSegmenterUnitTest.generateData(trueCauchyWidth, log2CopyRatio, rng));
        }
    }
    final ReadCountCollection rcc = new ReadCountCollection(crTargets, Arrays.asList("SAMPLE"), new Array2DRowRealMatrix(crData.stream().mapToDouble(x -> x).toArray()));
    final JointAFCRSegmenter segmenter = JointAFCRSegmenter.createJointSegmenter(initialNumCRStates, rcc, initialNumAFStates, afData, AllelicPanelOfNormals.EMPTY_PON);
    final TargetCollection<SimpleInterval> tc = new HashedListTargetCollection<>(positions);
    final List<Pair<SimpleInterval, AFCRHiddenState>> segmentation = segmenter.findSegments();
    final List<ACNVModeledSegment> jointSegments = segmentation.stream().map(pair -> {
        final SimpleInterval position = pair.getLeft();
        final AFCRHiddenState jointState = pair.getRight();
        final PosteriorSummary crSummary = PerformJointSegmentation.errorlessPosterior(jointState.getLog2CopyRatio());
        final PosteriorSummary afSummary = PerformJointSegmentation.errorlessPosterior(jointState.getMinorAlleleFraction());
        return new ACNVModeledSegment(position, crSummary, afSummary);
    }).collect(Collectors.toList());
    final double[] segmentCopyRatios = jointSegments.stream().flatMap(s -> Collections.nCopies(tc.targetCount(s.getInterval()), s.getSegmentMeanPosteriorSummary().getCenter()).stream()).mapToDouble(x -> x).toArray();
    final double[] segmentMinorFractions = jointSegments.stream().flatMap(s -> Collections.nCopies(tc.targetCount(s.getInterval()), s.getMinorAlleleFractionPosteriorSummary().getCenter()).stream()).mapToDouble(x -> x).toArray();
    final double averageMinorFractionError = Arrays.stream(MathArrays.ebeSubtract(trueAlleleFractionSequence, segmentMinorFractions)).map(Math::abs).average().getAsDouble();
    final double averageCopyRatioError = Arrays.stream(MathArrays.ebeSubtract(trueCopyRatioSequence, segmentCopyRatios)).map(Math::abs).average().getAsDouble();
    Assert.assertEquals(averageMinorFractionError, 0, 0.04);
    Assert.assertEquals(averageCopyRatioError, 0, 0.04);
}

Example 7 with GammaDistribution

use of org.apache.commons.math3.distribution.GammaDistribution in project gatk-protected by broadinstitute.

the class AlleleFractionSegmenterUnitTest method generateAllelicCount.

protected static AllelicCount generateAllelicCount(final double minorFraction, final SimpleInterval position, final RandomGenerator rng, final GammaDistribution biasGenerator, final double outlierProbability) {
    final int numReads = 100;
    final double bias = biasGenerator.sample();
    //flip a coin to decide alt minor (alt fraction = minor fraction) or ref minor (alt fraction = 1 - minor fraction)
    final double altFraction = rng.nextDouble() < 0.5 ? minorFraction : 1 - minorFraction;
    //the probability of an alt read is the alt fraction modified by the bias or, in the case of an outlier, random
    final double pAlt = rng.nextDouble() < outlierProbability ? rng.nextDouble() : altFraction / (altFraction + (1 - altFraction) * bias);
    final int numAltReads = new BinomialDistribution(rng, numReads, pAlt).sample();
    final int numRefReads = numReads - numAltReads;
    return new AllelicCount(position, numAltReads, numRefReads);
}

Example 8 with GammaDistribution

use of org.apache.commons.math3.distribution.GammaDistribution in project gatk-protected by broadinstitute.

the class JointAFCRSegmenterUnitTest method testSegmentation.

@Test
public void testSegmentation() {
    final RandomGenerator rng = RandomGeneratorFactory.createRandomGenerator(new Random(563));
    // probability that a datum is a het i.e. #hets / (#hets + #targets)
    final double hetProportion = 0.25;
    final List<Double> trueWeights = Arrays.asList(0.2, 0.5, 0.3);
    final double[] trueMinorAlleleFractions = new double[] { 0.12, 0.32, 0.5 };
    final double[] trueLog2CopyRatios = new double[] { -2.0, 0.0, 1.7 };
    final List<AFCRHiddenState> trueJointStates = IntStream.range(0, trueLog2CopyRatios.length).mapToObj(n -> new AFCRHiddenState(trueMinorAlleleFractions[n], trueLog2CopyRatios[n])).collect(Collectors.toList());
    final double trueMemoryLength = 1e5;
    final double trueCauchyWidth = 0.2;
    final int initialNumCRStates = 20;
    final int initialNumAFStates = 20;
    final AlleleFractionGlobalParameters trueAFParams = new AlleleFractionGlobalParameters(1.0, 0.01, 0.01);
    final JointAFCRHMM trueJointModel = new JointAFCRHMM(trueJointStates, trueWeights, trueMemoryLength, trueAFParams, AllelicPanelOfNormals.EMPTY_PON, trueCauchyWidth);
    // generate joint truth
    final int chainLength = 10000;
    final List<SimpleInterval> positions = CopyRatioSegmenterUnitTest.randomPositions("chr1", chainLength, rng, trueMemoryLength / 4);
    final List<Integer> trueHiddenStates = trueJointModel.generateHiddenStateChain(positions);
    final List<AFCRHiddenState> trueAFCRSequence = trueHiddenStates.stream().map(trueJointModel::getHiddenStateValue).collect(Collectors.toList());
    final double[] trueCopyRatioSequence = trueAFCRSequence.stream().mapToDouble(AFCRHiddenState::getLog2CopyRatio).toArray();
    final double[] trueAlleleFractionSequence = trueAFCRSequence.stream().mapToDouble(AFCRHiddenState::getMinorAlleleFraction).toArray();
    // generate separate af and cr data
    final GammaDistribution biasGenerator = AlleleFractionSegmenterUnitTest.getGammaDistribution(trueAFParams, rng);
    final double outlierProbability = trueAFParams.getOutlierProbability();
    final AllelicCountCollection afData = new AllelicCountCollection();
    final List<Double> crData = new ArrayList<>();
    final List<Target> crTargets = new ArrayList<>();
    for (int n = 0; n < positions.size(); n++) {
        final SimpleInterval position = positions.get(n);
        final AFCRHiddenState jointState = trueAFCRSequence.get(n);
        final double minorFraction = jointState.getMinorAlleleFraction();
        final double log2CopyRatio = jointState.getLog2CopyRatio();
        if (rng.nextDouble() < hetProportion) {
            // het datum
            afData.add(AlleleFractionSegmenterUnitTest.generateAllelicCount(minorFraction, position, rng, biasGenerator, outlierProbability));
        } else {
            //target datum
            crTargets.add(new Target(position));
            crData.add(CopyRatioSegmenterUnitTest.generateData(trueCauchyWidth, log2CopyRatio, rng));
        }
    }
    final ReadCountCollection rcc = new ReadCountCollection(crTargets, Arrays.asList("SAMPLE"), new Array2DRowRealMatrix(crData.stream().mapToDouble(x -> x).toArray()));
    final JointAFCRSegmenter segmenter = JointAFCRSegmenter.createJointSegmenter(initialNumCRStates, rcc, initialNumAFStates, afData, AllelicPanelOfNormals.EMPTY_PON);
    final TargetCollection<SimpleInterval> tc = new HashedListTargetCollection<>(positions);
    final List<Pair<SimpleInterval, AFCRHiddenState>> segmentation = segmenter.findSegments();
    final List<ACNVModeledSegment> jointSegments = segmentation.stream().map(pair -> {
        final SimpleInterval position = pair.getLeft();
        final AFCRHiddenState jointState = pair.getRight();
        final PosteriorSummary crSummary = PerformJointSegmentation.errorlessPosterior(jointState.getLog2CopyRatio());
        final PosteriorSummary afSummary = PerformJointSegmentation.errorlessPosterior(jointState.getMinorAlleleFraction());
        return new ACNVModeledSegment(position, crSummary, afSummary);
    }).collect(Collectors.toList());
    final double[] segmentCopyRatios = jointSegments.stream().flatMap(s -> Collections.nCopies(tc.targetCount(s.getInterval()), s.getSegmentMeanPosteriorSummary().getCenter()).stream()).mapToDouble(x -> x).toArray();
    final double[] segmentMinorFractions = jointSegments.stream().flatMap(s -> Collections.nCopies(tc.targetCount(s.getInterval()), s.getMinorAlleleFractionPosteriorSummary().getCenter()).stream()).mapToDouble(x -> x).toArray();
    final double averageMinorFractionError = Arrays.stream(MathArrays.ebeSubtract(trueAlleleFractionSequence, segmentMinorFractions)).map(Math::abs).average().getAsDouble();
    final double averageCopyRatioError = Arrays.stream(MathArrays.ebeSubtract(trueCopyRatioSequence, segmentCopyRatios)).map(Math::abs).average().getAsDouble();
    Assert.assertEquals(averageMinorFractionError, 0, 0.04);
    Assert.assertEquals(averageCopyRatioError, 0, 0.04);
}