Initial attempt at identifying potentially interesting variants in a Mendelian disease context when the called genotypes are uncertain.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@5473 348d0f76-0448-11de-a6fe-93d51630548a
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kiran
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package org.broadinstitute.sting.oneoffprojects.walkers;
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import org.broad.tribble.util.variantcontext.Allele;
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import org.broad.tribble.util.variantcontext.Genotype;
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import org.broad.tribble.util.variantcontext.VariantContext;
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import org.broad.tribble.vcf.VCFHeader;
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import org.broadinstitute.sting.commandline.Argument;
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import org.broadinstitute.sting.commandline.Output;
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import org.broadinstitute.sting.gatk.contexts.AlignmentContext;
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import org.broadinstitute.sting.gatk.contexts.ReferenceContext;
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import org.broadinstitute.sting.gatk.contexts.variantcontext.VariantContextUtils;
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import org.broadinstitute.sting.gatk.refdata.RefMetaDataTracker;
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import org.broadinstitute.sting.gatk.report.GATKReport;
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import org.broadinstitute.sting.gatk.report.GATKReportTable;
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import org.broadinstitute.sting.gatk.walkers.RMD;
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import org.broadinstitute.sting.gatk.walkers.Requires;
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import org.broadinstitute.sting.gatk.walkers.RodWalker;
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import org.broadinstitute.sting.utils.MathUtils;
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import org.broadinstitute.sting.utils.SampleUtils;
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import org.broadinstitute.sting.utils.exceptions.UserException;
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import org.broadinstitute.sting.utils.text.XReadLines;
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import org.broadinstitute.sting.utils.vcf.VCFUtils;
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import java.io.File;
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import java.io.FileNotFoundException;
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import java.io.PrintStream;
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import java.util.*;
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/**
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* Given a VCF file and one or more scenarios for affected individuals, calculates the probability that a given site's genotypes
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* are consistent with the expected pattern for a given disease model.
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*/
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@Requires(value={},referenceMetaData=@RMD(name="variant", type=VariantContext.class))
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public class AffectedConsistencyWalker extends RodWalker<Integer, Integer> {
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public enum DiseaseModel { DOMINANT, RECESSIVE }
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@Output
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public PrintStream out;
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@Argument(fullName="affected", shortName="A", doc="A scenario file (or files) for affected individuals. Scenarios are specified with an identifier and a comma-separated list of samples (e.g. Pedigree_1 sample1,sample2,sample3). Each line is another scenario.", required=true)
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public String[] AFFECTED_SAMPLE_SCENARIOS;
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@Argument(fullName="diseaseModel", shortName="DM", doc="The disease model (DOMINANT or RECESSIVE)", required=true)
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public DiseaseModel DISEASE_MODEL;
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@Argument(fullName="verbose", shortName="V", doc="If specified, enable verbose mode with a lot of output useful for debugging", required=false)
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public PrintStream VERBOSE_WRITER = null;
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public Map<String, Set<String>> sampleScenarios;
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public GATKReport consistencyReport;
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public Set<String> availableSamples;
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private Map<String, Set<String>> loadAffectedSampleScenarios() {
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// Load all the specified sample scenarios specified in one or more files
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ArrayList<String> scenarioStrings = new ArrayList<String>();
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for (String affectedSampleScenario : AFFECTED_SAMPLE_SCENARIOS) {
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File affectedSampleScenarioFile = new File(affectedSampleScenario);
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try {
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XReadLines lineReader = new XReadLines(affectedSampleScenarioFile);
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for (String line : lineReader) {
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// Ignore commented-out lines
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if (!line.contains("#")) {
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scenarioStrings.add(line);
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}
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}
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} catch (FileNotFoundException e) {
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throw new UserException(String.format("The scenario file '%s' was not found", affectedSampleScenarioFile.getAbsolutePath()));
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}
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}
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// Parse all the sample scenario strings (comma- or white-space-separated sample lists)
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Map<String, Set<String>> scenarios = new HashMap<String, Set<String>>();
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for (String scenarioString : scenarioStrings) {
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String[] pieces = scenarioString.split("[\\s]+");
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if (pieces.length != 2) {
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throw new UserException(
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String.format("The scenario line '%s' could not be understood. Please make sure that your " +
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"scenario file has only two columns: the first being an arbitrary scenario id " +
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"(e.g. 'Pedigree_1') and the second being a comma-separated list of samples " +
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"(e.g. 'sample1,sample2,sample3')",
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scenarioString
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)
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);
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}
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String scenarioId = pieces[0];
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String[] sampleNames = pieces[1].split(",");
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Set<String> samples = new HashSet<String>();
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for (String sample : sampleNames) {
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if (!availableSamples.contains(sample)) {
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throw new UserException(
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String.format("The sample '%s' was not found in the ROD bound as the 'variant' track " +
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"(i.e. the file that was supplied via '-B:variant,VCF /path/to/my.vcf'). " +
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"Please make sure all samples specified for processing are present in " +
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"your VCF.",
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sample)
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);
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} else {
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samples.add(sample);
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}
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}
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scenarios.put(scenarioId, samples);
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}
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if (scenarios.size() == 0) {
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throw new UserException("There were no scenarios specified. Please specify at least one set of affected samples.");
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}
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return scenarios;
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}
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public void initialize() {
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// Figure out what samples I can possibly have (from the bound VCF file)
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ArrayList<String> rodNames = new ArrayList<String>();
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rodNames.add("variant");
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Map<String, VCFHeader> vcfRods = VCFUtils.getVCFHeadersFromRods(getToolkit(), rodNames);
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availableSamples = SampleUtils.getSampleList(vcfRods, VariantContextUtils.GenotypeMergeType.REQUIRE_UNIQUE);
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// Load the scenarios to consider
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sampleScenarios = loadAffectedSampleScenarios();
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// Prepare the output report
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consistencyReport = new GATKReport();
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consistencyReport.addTable("AffectedConsistency", "Table of results indicating if the observed genotypes matched the expected genotypes");
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GATKReportTable table = consistencyReport.getTable("AffectedConsistency");
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table.addPrimaryKey("locus_and_scenario", false);
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table.addColumn("chr", "unknown");
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table.addColumn("start", 0);
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table.addColumn("scenario", "unknown");
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table.addColumn("P_of_C_given_DM_is_true", 0.0);
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table.addColumn("P_of_C_given_DM_is_false", 0.0);
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table.addColumn("OR_DM_is_true_vs_DM_is_false", 0.0);
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for ( String sample : availableSamples ) {
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table.addColumn(sample, "unknown");
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}
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if (VERBOSE_WRITER != null) {
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VERBOSE_WRITER.println("This is a test of the verbose writer");
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}
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System.exit(0);
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}
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private VariantContext getExpectedGenotypeConfiguration(Set<String> affectedSamples, VariantContext obs) {
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List<Allele> homRefAlleles = new ArrayList<Allele>();
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homRefAlleles.add(obs.getReference());
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homRefAlleles.add(obs.getReference());
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List<Allele> hetAlleles = new ArrayList<Allele>();
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hetAlleles.add(obs.getReference());
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hetAlleles.add(obs.getAlternateAllele(0));
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List<Allele> homVarAlleles = new ArrayList<Allele>();
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homVarAlleles.add(obs.getAlternateAllele(0));
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homVarAlleles.add(obs.getAlternateAllele(0));
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Collection<Genotype> expectedGenotypes = new ArrayList<Genotype>();
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for ( String sample : obs.getSampleNames() ) {
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Genotype expectedGenotype = new Genotype(sample, homRefAlleles);
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if (affectedSamples.contains(sample)) {
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expectedGenotype = (DISEASE_MODEL == DiseaseModel.DOMINANT) ? new Genotype(sample, hetAlleles) : new Genotype(sample, homVarAlleles);
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}
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expectedGenotypes.add(expectedGenotype);
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}
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return new VariantContext("expected", obs.getChr(), obs.getStart(), obs.getEnd(), obs.getAlleles(), expectedGenotypes);
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}
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private double getLogLikelihoodOfDiseaseModelHypothesis(VariantContext obs, VariantContext exp, boolean diseaseModelIsSupported) {
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return getLogLikelihoodOfDiseaseModelHypothesis(obs, exp, diseaseModelIsSupported, 0, 0.0);
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}
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private double getLogLikelihoodOfDiseaseModelHypothesis(VariantContext obs, VariantContext exp, boolean diseaseModelIsSupported, int sampleIndex, double logLikelihoodSoFar) {
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if (sampleIndex < exp.getNSamples()) {
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Genotype expGenotype = exp.getGenotype(sampleIndex);
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Genotype obsGenotype = obs.getGenotype(sampleIndex);
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if (obsGenotype.hasLikelihoods()) {
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double[] normalizedLikelihoods = MathUtils.normalizeFromLog10(obsGenotype.getLikelihoods().getAsVector());
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boolean[] expectedGenotypes = { expGenotype.isHomRef(), expGenotype.isHet(), expGenotype.isHomVar() };
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for (int i = 0; i < 3; i++) {
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if (expectedGenotypes[i] == diseaseModelIsSupported) {
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return getLogLikelihoodOfDiseaseModelHypothesis(obs, exp, diseaseModelIsSupported, sampleIndex + 1, logLikelihoodSoFar + Math.log10(normalizedLikelihoods[i]));
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}
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}
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} else {
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return getLogLikelihoodOfDiseaseModelHypothesis(obs, exp, diseaseModelIsSupported, sampleIndex + 1, logLikelihoodSoFar);
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}
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}
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return logLikelihoodSoFar;
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}
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@Override
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public Integer map(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context) {
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if (tracker != null) {
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Collection<VariantContext> vcs = tracker.getAllVariantContexts(ref, null, ref.getLocus(), true, true);
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if (vcs.size() == 1) {
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VariantContext obs = vcs.iterator().next();
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for (String scenarioId : sampleScenarios.keySet()) {
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Set<String> affectedSamples = sampleScenarios.get(scenarioId);
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VariantContext exp = getExpectedGenotypeConfiguration(affectedSamples, obs);
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/*
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GATKReport report = new GATKReport();
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String reportName = String.format("GenotypeTable_%s_%s_%s", scenarioId, ref.getLocus().getContig(), ref.getLocus().getStart());
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String reportDesc = String.format("Info for scenario %s at locus %s", scenarioId, ref.getLocus());
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report.addTable(reportName, reportDesc);
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GATKReportTable table = report.getTable(reportName);
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table.addPrimaryKey("sample_pk", false);
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table.addColumn("table", "unknown");
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table.addColumn("sample", "unknown");
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table.addColumn("affected", false);
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table.addColumn("homref_prob", "unknown");
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table.addColumn("het_prob", "unknown");
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table.addColumn("homvar_prob", "unknown");
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table.addColumn("observed_genotype", "unknown");
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table.addColumn("expected_genotype", "unknown");
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for (String sample : obs.getSampleNames()) {
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double[] normalizedLikelihoods = {0.0, 0.0, 0.0};
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if (obs.getGenotype(sample).hasLikelihoods()) {
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normalizedLikelihoods = MathUtils.normalizeFromLog10(obs.getGenotype(sample).getLikelihoods().getAsVector());
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}
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table.set(sample, "table", reportName);
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table.set(sample, "sample", sample);
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table.set(sample, "affected", affectedSamples.contains(sample));
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table.set(sample, "homref_prob", normalizedLikelihoods[0]);
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table.set(sample, "het_prob", normalizedLikelihoods[1]);
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table.set(sample, "homvar_prob", normalizedLikelihoods[2]);
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table.set(sample, "observed_genotype", obs.getGenotype(sample).getGenotypeString());
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table.set(sample, "expected_genotype", exp.getGenotype(sample).getGenotypeString());
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}
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report.print(out);
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*/
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double logLikelihoodThatDiseaseModelIsSupported = getLogLikelihoodOfDiseaseModelHypothesis(obs, exp, true);
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double logLikelihoodThatDiseaseModelIsNotSupported = getLogLikelihoodOfDiseaseModelHypothesis(obs, exp, false);
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double logOddsRatioThatDiseaseModelIsSupported = logLikelihoodThatDiseaseModelIsSupported / logLikelihoodThatDiseaseModelIsNotSupported;
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String key = String.format("%s_%s_%s", ref.getLocus().getContig(), ref.getLocus().getStart(), scenarioId);
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consistencyReport.getTable("AffectedConsistency").set(key, "scenario", scenarioId);
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consistencyReport.getTable("AffectedConsistency").set(key, "chr", ref.getLocus().getContig());
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consistencyReport.getTable("AffectedConsistency").set(key, "start", ref.getLocus().getStart());
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consistencyReport.getTable("AffectedConsistency").set(key, "P_of_C_given_DM_is_true", logLikelihoodThatDiseaseModelIsSupported);
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consistencyReport.getTable("AffectedConsistency").set(key, "P_of_C_given_DM_is_false", logLikelihoodThatDiseaseModelIsNotSupported);
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consistencyReport.getTable("AffectedConsistency").set(key, "OR_DM_is_true_vs_DM_is_false", logOddsRatioThatDiseaseModelIsSupported);
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for ( String sample : availableSamples ) {
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String obsAndExpectedGenotypes = String.format("%s;%s", obs.getGenotype(sample).getGenotypeString(), exp.getGenotype(sample).getGenotypeString());
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consistencyReport.getTable("AffectedConsistency").set(key, sample, obsAndExpectedGenotypes);
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}
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}
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}
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}
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return null;
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}
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/**
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* Provide an initial value for reduce computations.
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*
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* @return Initial value of reduce.
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*/
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@Override
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public Integer reduceInit() {
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return null;
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}
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/**
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* Reduces a single map with the accumulator provided as the ReduceType.
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*
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* @param value result of the map.
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* @param sum accumulator for the reduce.
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* @return accumulator with result of the map taken into account.
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*/
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@Override
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public Integer reduce(Integer value, Integer sum) {
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return null;
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}
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public void onTraversalDone(Integer result) {
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consistencyReport.print(out);
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}
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}
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