Examples with AllelicPanelOfNormals org.broadinstitute.hellbender.tools.pon.allelic.AllelicPanelOfNormals used on opensource projects

Example 16 with AllelicPanelOfNormals

use of org.broadinstitute.hellbender.tools.pon.allelic.AllelicPanelOfNormals in project gatk by broadinstitute.

the class PerformJointSegmentation method doWork.

@Override
public Object doWork() {
    ParamUtils.isPositive(initialNumAFStates, "Must have at least one allele-fraction state.");
    ParamUtils.isPositive(initialNumCRStates, "Must have at least one copy-ratio state.");
    final AllelicPanelOfNormals allelicPoN = allelicPoNFile != null ? AllelicPanelOfNormals.read(allelicPoNFile) : AllelicPanelOfNormals.EMPTY_PON;
    final AllelicCountCollection acc = new AllelicCountCollection(snpCountsFile);
    final ReadCountCollection rcc;
    try {
        rcc = ReadCountCollectionUtils.parse(new File(coverageFile));
    } catch (final IOException ex) {
        throw new UserException.BadInput("could not read input file");
    }
    final JointAFCRSegmenter jointSegmenter = JointAFCRSegmenter.createJointSegmenter(initialNumCRStates, rcc, initialNumAFStates, acc, allelicPoN);
    final List<Pair<SimpleInterval, AFCRHiddenState>> segmentation = jointSegmenter.findSegments();
    final List<ACNVModeledSegment> segments = segmentation.stream().map(pair -> new ACNVModeledSegment(pair.getLeft(), errorlessPosterior(pair.getRight().getLog2CopyRatio()), errorlessPosterior(pair.getRight().getMinorAlleleFraction()))).collect(Collectors.toList());
    //TODO: make more reasonable output for ACNV 2.0
    SegmentUtils.writeACNVModeledSegmentFile(outputSegmentsFile, segments, new Genome(rcc, acc.getCounts()));
    return "SUCCESS";
}

Example 17 with AllelicPanelOfNormals

use of org.broadinstitute.hellbender.tools.pon.allelic.AllelicPanelOfNormals in project gatk-protected by broadinstitute.

the class CreateAllelicPanelOfNormals method doWork.

@Override
protected Object doWork() {
    validateArguments();
    if (!new HDF5Library().load(null)) {
        //Note: passing null means using the default temp dir.
        throw new UserException.HardwareFeatureException("Cannot load the required HDF5 library. " + "HDF5 is currently supported on x86-64 architecture and Linux or OSX systems.");
    }
    logger.info("Starting allelic panel of normals creation...");
    final AllelicPanelOfNormals allelicPoN = new AllelicPanelOfNormalsCreator(inputFiles).create(siteFrequencyThreshold);
    logger.info("Allelic panel of normals created.");
    logger.info("Writing allelic panel of normals to output HDF5 file...");
    allelicPoN.write(outputFile, HDF5File.OpenMode.CREATE);
    logger.info("Allelic panel of normals written to " + outputFile + ".");
    if (outputTSVFile != null) {
        allelicPoN.write(outputTSVFile);
        logger.info("Allelic panel of normals written as tab-separated values to " + outputTSVFile + ".");
    }
    return "SUCCESS";
}

Example 18 with AllelicPanelOfNormals

use of org.broadinstitute.hellbender.tools.pon.allelic.AllelicPanelOfNormals in project gatk by broadinstitute.

the class AlleleFractionModellerUnitTest method testMCMCWithAllelicPoN.

/**
     * Test MCMC inference on simulated data using an allelic PoN.  Note that these MCMC tests were written to use
     * simulated hets before the allelic PoN was introduced.  Rather than generate a simulated PoN on the fly,
     * we simply use a fixed simulated PoN loaded from a file and check that its MLE hyperparameters are "sampled"
     * correctly by simply taking the MLE PoN values---i.e., the PoN does not actually cover the simulated sites and
     * hence is not used to correct reference bias in the simulated data in any way.
     * This latter functionality is tested on fixed data loaded from files in
     * {@link AlleleFractionModellerUnitTest#testBiasCorrection} instead.
     */
@Test
public void testMCMCWithAllelicPoN() {
    final double meanBiasSimulated = 1.2;
    final double biasVarianceSimulated = 0.04;
    // PoN generated with alpha = 65
    final double meanBiasOfPoN = 1.083;
    // PoN generated with beta = 60
    final double biasVarianceOfPoN = 0.0181;
    final AllelicPanelOfNormals allelicPoN = new AllelicPanelOfNormals(new AllelicCountCollection(ALLELIC_PON_NORMAL_COUNTS_FILE));
    testMCMC(meanBiasSimulated, biasVarianceSimulated, meanBiasOfPoN, biasVarianceOfPoN, allelicPoN);
}

Example 19 with AllelicPanelOfNormals

use of org.broadinstitute.hellbender.tools.pon.allelic.AllelicPanelOfNormals in project gatk by broadinstitute.

the class AlleleFractionModellerUnitTest method dataBiasCorrection.

@DataProvider(name = "biasCorrection")
public Object[][] dataBiasCorrection() {
    LoggingUtils.setLoggingLevel(Log.LogLevel.INFO);
    final AllelicCountCollection sampleNormal = new AllelicCountCollection(SAMPLE_NORMAL_FILE);
    final AllelicCountCollection sampleWithBadSNPs = new AllelicCountCollection(SAMPLE_WITH_BAD_SNPS_FILE);
    final AllelicCountCollection sampleWithEvent = new AllelicCountCollection(SAMPLE_WITH_EVENT_FILE);
    final AllelicPanelOfNormals allelicPoNNormal = new AllelicPanelOfNormals(new AllelicCountCollection(ALLELIC_PON_NORMAL_COUNTS_FILE));
    final AllelicPanelOfNormals allelicPoNWithBadSNPs = new AllelicPanelOfNormals(new AllelicCountCollection(ALLELIC_PON_WITH_BAD_SNPS_COUNTS_FILE));
    final double minorFractionExpectedInMiddleSegmentNormal = 0.5;
    final double minorFractionExpectedInMiddleSegmentWithBadSNPsAndNormalPoN = 0.4;
    final double minorFractionExpectedInMiddleSegmentWithEvent = 0.33;
    return new Object[][] { { sampleNormal, allelicPoNNormal, minorFractionExpectedInMiddleSegmentNormal }, { sampleWithBadSNPs, allelicPoNNormal, minorFractionExpectedInMiddleSegmentWithBadSNPsAndNormalPoN }, { sampleWithEvent, allelicPoNNormal, minorFractionExpectedInMiddleSegmentWithEvent }, { sampleWithBadSNPs, allelicPoNWithBadSNPs, minorFractionExpectedInMiddleSegmentNormal } };
}

Example 20 with AllelicPanelOfNormals

use of org.broadinstitute.hellbender.tools.pon.allelic.AllelicPanelOfNormals in project gatk-protected by broadinstitute.

the class PerformJointSegmentation method doWork.

@Override
public Object doWork() {
    ParamUtils.isPositive(initialNumAFStates, "Must have at least one allele-fraction state.");
    ParamUtils.isPositive(initialNumCRStates, "Must have at least one copy-ratio state.");
    final AllelicPanelOfNormals allelicPoN = allelicPoNFile != null ? AllelicPanelOfNormals.read(allelicPoNFile) : AllelicPanelOfNormals.EMPTY_PON;
    final AllelicCountCollection acc = new AllelicCountCollection(snpCountsFile);
    final ReadCountCollection rcc;
    try {
        rcc = ReadCountCollectionUtils.parse(new File(coverageFile));
    } catch (final IOException ex) {
        throw new UserException.BadInput("could not read input file");
    }
    final JointAFCRSegmenter jointSegmenter = JointAFCRSegmenter.createJointSegmenter(initialNumCRStates, rcc, initialNumAFStates, acc, allelicPoN);
    final List<Pair<SimpleInterval, AFCRHiddenState>> segmentation = jointSegmenter.findSegments();
    final List<ACNVModeledSegment> segments = segmentation.stream().map(pair -> new ACNVModeledSegment(pair.getLeft(), errorlessPosterior(pair.getRight().getLog2CopyRatio()), errorlessPosterior(pair.getRight().getMinorAlleleFraction()))).collect(Collectors.toList());
    //TODO: make more reasonable output for ACNV 2.0
    SegmentUtils.writeACNVModeledSegmentFile(outputSegmentsFile, segments, new Genome(rcc, acc.getCounts()));
    return "SUCCESS";
}