*** We no longer have a separate model for the single-sample case. ***
For now, a single sample input will be special-cased in the EM model - but that will change when the EM model degenerates to the single sample output with a single sample as input. For now, the EM code for multi-samples isn't finished; I'm planning on checking that in soon. The SingleSampleIntegrationTest now uses the UnifiedCaller instead of SSG, and so should all of you. More on that in a separate email. Other minor cleanups added too. git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1785 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
ebanks
parent
32128e093a
commit
04fe50cadd
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@ -7,9 +7,9 @@ import org.apache.log4j.Logger;
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import java.util.Set;
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public class MultiSampleAllMAFsGenotypeCalculationModel extends GenotypeCalculationModel {
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public class AllMAFsGenotypeCalculationModel extends GenotypeCalculationModel {
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protected MultiSampleAllMAFsGenotypeCalculationModel() {}
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protected AllMAFsGenotypeCalculationModel() {}
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public boolean calculateGenotype(RefMetaDataTracker tracker, char ref, AlignmentContext context, DiploidGenotypePriors priors) {
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@ -11,7 +11,7 @@ import java.util.*;
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import net.sf.samtools.SAMRecord;
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import net.sf.samtools.SAMReadGroupRecord;
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public class MultiSampleEMGenotypeCalculationModel extends GenotypeCalculationModel {
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public class EMGenotypeCalculationModel extends GenotypeCalculationModel {
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// We need to set a limit on the EM iterations in case something flukey goes on
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private static final int MAX_EM_ITERATIONS = 6;
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@ -19,13 +19,16 @@ public class MultiSampleEMGenotypeCalculationModel extends GenotypeCalculationMo
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// We consider the EM stable when the MAF doesn't change more than 1/10N
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private static final double EM_STABILITY_METRIC = 0.1;
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// keep track of some metrics about our calls
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private CallMetrics callsMetrics = new CallMetrics();
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protected MultiSampleEMGenotypeCalculationModel() {}
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protected EMGenotypeCalculationModel() {}
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public boolean calculateGenotype(RefMetaDataTracker tracker, char ref, AlignmentContext context, DiploidGenotypePriors priors) {
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// keep track of the GenotpeLikelihoods for each sample, separated by strand
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HashMap<String, PerSampleGenotypeLikelihoods> GLs = new HashMap<String, PerSampleGenotypeLikelihoods>();
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// keep track of the GenotypeLikelihoods for each sample, separated by strand
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HashMap<String, UnifiedGenotypeLikelihoods> GLs = new HashMap<String, UnifiedGenotypeLikelihoods>();
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// keep track of the total counts of each base in the pileup
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int[] baseCounts = new int[4];
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@ -39,55 +42,76 @@ public class MultiSampleEMGenotypeCalculationModel extends GenotypeCalculationMo
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for (int i = 0; i < reads.size(); i++) {
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// set up the base data
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// get the read and offset
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SAMRecord read = reads.get(i);
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int offset = offsets.get(i);
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char base = read.getReadString().charAt(offset);
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// don't use bad bases
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int baseIndex = BaseUtils.simpleBaseToBaseIndex(base);
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if ( baseIndex == -1 ) {
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// skip deletions
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if ( offset == -1 ) {
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// are there too many deletions in the pileup?
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if ( ++deletionsInPile > maxDeletionsInPileup )
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return false;
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continue;
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}
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// get the base; don't use bad bases
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char base = read.getReadString().charAt(offset);
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int baseIndex = BaseUtils.simpleBaseToBaseIndex(base);
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if ( baseIndex == -1 )
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continue;
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// create the GL holder object if this is the first time we're seeing a base for this sample
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String readGroup = read.getAttribute("RG").toString(); // can't be null because those are filtered out
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String sample = read.getHeader().getReadGroup(readGroup).getSample();
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PerSampleGenotypeLikelihoods myGLs = GLs.get(sample);
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UnifiedGenotypeLikelihoods myGLs = GLs.get(sample);
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if ( myGLs == null ) {
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myGLs = new PerSampleGenotypeLikelihoods();
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myGLs = new UnifiedGenotypeLikelihoods(baseModel, new DiploidGenotypePriors(), defaultPlatform, VERBOSE);
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GLs.put(sample, myGLs);
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}
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// assign the base to the appropriate strand
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myGLs.addObservedBase(base, read, offset);
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myGLs.add(base, read, offset);
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// update the base counts
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baseCounts[baseIndex]++;
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totalObservedBases++;
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}
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// optimization: if all bases are ref, return
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if ( baseCounts[BaseUtils.simpleBaseToBaseIndex(ref)] == totalObservedBases )
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return true;
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// for now, we need to special-case single sample mode
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if ( samples.size() == 1 ) {
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UnifiedGenotypeLikelihoods UGL = GLs.get(samples.iterator().next());
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// if there were no good bases, the likelihoods object wouldn't exist
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if ( UGL == null )
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return false;
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// TODO -- Do we quit if there isn't X% of total samples represented in pileup?
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callsMetrics.nCalledBases++;
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UGL.setPriors(priors);
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SSGenotypeCall call = new SSGenotypeCall(context.getLocation(), ref, UGL.getGenotypeLikelihoods(), new ReadBackedPileup(ref, context));
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if ( GENOTYPE_MODE || call.isVariant(call.getReference()) ) {
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double confidence = (GENOTYPE_MODE ? call.getNegLog10PError() : call.toVariation().getNegLog10PError());
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if ( confidence >= LOD_THRESHOLD ) {
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callsMetrics.nConfidentCalls++;
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out.addGenotypeCall(call);
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} else {
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callsMetrics.nNonConfidentCalls++;
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}
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}
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return true;
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}
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callsMetrics.nCalledBases++;
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// Next, we need to create initial allele frequencies.
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// An intelligent guess would be the observed base ratios (plus some small number to account for sampling issues).
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// TODO --- This needs to be broken out into a separate model as we might want to split up the calculation for each minor allele
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double[] alleleFrequencies = new double[4];
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for (int i = 0; i < 4; i++)
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alleleFrequencies[i] = ((double)baseCounts[i] + DiploidGenotypePriors.HUMAN_HETEROZYGOSITY) / (double)totalObservedBases;
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DiploidGenotypePriors AFPriors = calculateAlleleFreqBasedPriors(alleleFrequencies);
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for ( PerSampleGenotypeLikelihoods SGL : GLs.values() )
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SGL.createGLs(AFPriors);
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for ( UnifiedGenotypeLikelihoods UGL : GLs.values() )
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UGL.setPriors(AFPriors);
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// debugging output
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for (int i = 0; i < 4; i++)
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@ -106,8 +130,8 @@ public class MultiSampleEMGenotypeCalculationModel extends GenotypeCalculationMo
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// calculate the posterior-weighted allele frequencies and modify the priors accordingly
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double[] newAlleleFrequencies = getPosteriorWeightedFrequencies(GLs.values());
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AFPriors = calculateAlleleFreqBasedPriors(newAlleleFrequencies);
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for ( PerSampleGenotypeLikelihoods SGL : GLs.values() )
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SGL.setPriors(AFPriors);
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for ( UnifiedGenotypeLikelihoods UGL : GLs.values() )
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UGL.setPriors(AFPriors);
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// determine whether we're stable
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double AF_delta = 0.0;
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@ -127,6 +151,13 @@ public class MultiSampleEMGenotypeCalculationModel extends GenotypeCalculationMo
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if (true)
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throw new RuntimeException("DEBUGGING");
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// compute actual priors: theta / MAF
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double pF = computeThetaOverMAF(ref, alleleFrequencies, GLs.size());
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// the posteriors from the EM loop are the population likelihoods here
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// TODO -- finish me
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/*
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ClassicGenotypeLikelihoods[] G = em_result.genotype_likelihoods;
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pD = Compute_pD(G, em_result.sample_weights);
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@ -152,23 +183,21 @@ public class MultiSampleEMGenotypeCalculationModel extends GenotypeCalculationMo
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*/
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// apply prior of theta / MAF
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// It turns out that the appropriate prior is theta, for any sample size from 1 to ~1,000
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//return new SSGenotypeCall(context.getLocation(), ref,gl, pileup);
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return true;
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}
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double[] getPosteriorWeightedFrequencies(Collection<PerSampleGenotypeLikelihoods> SGLs) {
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double[] getPosteriorWeightedFrequencies(Collection<UnifiedGenotypeLikelihoods> UGLs) {
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double[] newAlleleLikelihoods = new double[4];
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for ( PerSampleGenotypeLikelihoods SGL : SGLs ) {
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for ( UnifiedGenotypeLikelihoods UGL : UGLs ) {
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// calculate the posterior weighted frequencies for this sample
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double[] personalAllelePosteriors = new double[4];
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double sum = 0;
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for ( DiploidGenotype g : DiploidGenotype.values() ) {
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double posterior = Math.pow(10, SGL.totalGL.getPosterior(g));
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double posterior = Math.pow(10, UGL.getGenotypeLikelihoods().getPosterior(g));
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personalAllelePosteriors[BaseUtils.simpleBaseToBaseIndex(g.base1)] += posterior;
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personalAllelePosteriors[BaseUtils.simpleBaseToBaseIndex(g.base2)] += posterior;
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sum += 2.0 * posterior;
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@ -210,43 +239,34 @@ public class MultiSampleEMGenotypeCalculationModel extends GenotypeCalculationMo
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return new DiploidGenotypePriors(alleleFreqPriors);
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}
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private class PerSampleGenotypeLikelihoods {
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private double computeThetaOverMAF(char ref, double[] alleleFrequencies, int samplesAtLocus) {
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double MAF;
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Integer[] sortedIndexes = Utils.SortPermutation(alleleFrequencies);
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if ( sortedIndexes[3] != BaseUtils.simpleBaseToBaseIndex(ref) )
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MAF = alleleFrequencies[sortedIndexes[3]];
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else
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MAF = alleleFrequencies[sortedIndexes[2]];
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GenotypeLikelihoods forwardStrandGL;
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GenotypeLikelihoods reverseStrandGL;
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GenotypeLikelihoods totalGL;
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int expectedChrs = (int)(2.0 * (double)samplesAtLocus * MAF);
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public PerSampleGenotypeLikelihoods() {
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forwardStrandGL = GenotypeLikelihoodsFactory.makeGenotypeLikelihoods(baseModel, new DiploidGenotypePriors(), defaultPlatform);
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forwardStrandGL.setVerbose(VERBOSE);
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reverseStrandGL = GenotypeLikelihoodsFactory.makeGenotypeLikelihoods(baseModel, new DiploidGenotypePriors(), defaultPlatform);
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reverseStrandGL.setVerbose(VERBOSE);
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}
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// TODO -- we need to use the priors from the UnifiedArgumentCollection
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return DiploidGenotypePriors.HUMAN_HETEROZYGOSITY / (double)expectedChrs;
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}
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public void addObservedBase(char base, SAMRecord read, int offset) {
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if ( !read.getReadNegativeStrandFlag() )
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forwardStrandGL.add(base, read.getBaseQualities()[offset], read, offset);
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else
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reverseStrandGL.add(base, read.getBaseQualities()[offset], read, offset);
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}
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public void createGLs(DiploidGenotypePriors priors) {
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setPriors(priors);
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/**
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* A class to keep track of some basic metrics about our calls
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*/
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private class CallMetrics {
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long nConfidentCalls = 0;
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long nNonConfidentCalls = 0;
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long nCalledBases = 0;
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// GL_i = GL+_i + GL-_i
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totalGL = GenotypeLikelihoods.combineLikelihoods(forwardStrandGL, reverseStrandGL);
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totalGL.setVerbose(VERBOSE);
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if ( VERBOSE )
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totalGL.validate();
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}
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CallMetrics() {}
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public void setPriors(DiploidGenotypePriors priors) {
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if ( forwardStrandGL != null )
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forwardStrandGL.setPriors(priors);
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if ( reverseStrandGL != null )
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reverseStrandGL.setPriors(priors);
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if ( totalGL != null )
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totalGL.setPriors(priors);
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public String toString() {
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return String.format("SSG: %d confident and %d non-confident calls were made at %d bases",
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nConfidentCalls, nNonConfidentCalls, nCalledBases);
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}
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}
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}
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@ -14,9 +14,8 @@ import java.util.*;
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public abstract class GenotypeCalculationModel implements Cloneable {
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public enum Model {
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SINGLE_SAMPLE,
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MULTI_SAMPLE_EM,
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MULTI_SAMPLE_ALL_MAFS
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EM,
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ALL_MAFS
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}
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protected BaseMismatchModel baseModel;
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@ -58,14 +58,11 @@ public class GenotypeCalculationModelFactory {
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Logger logger) {
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GenotypeCalculationModel gcm;
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switch ( UAC.genotypeModel ) {
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case SINGLE_SAMPLE:
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gcm = new SingleSampleGenotypeCalculationModel();
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case EM:
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gcm = new EMGenotypeCalculationModel();
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break;
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case MULTI_SAMPLE_EM:
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gcm = new MultiSampleEMGenotypeCalculationModel();
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break;
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case MULTI_SAMPLE_ALL_MAFS:
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gcm = new MultiSampleAllMAFsGenotypeCalculationModel();
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case ALL_MAFS:
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gcm = new AllMAFsGenotypeCalculationModel();
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break;
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default: throw new RuntimeException("Unexpected GenotypeCalculationModel " + UAC.genotypeModel);
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}
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@ -78,32 +78,6 @@ public abstract class GenotypeLikelihoods implements Cloneable {
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initialize();
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}
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public static GenotypeLikelihoods combineLikelihoods(GenotypeLikelihoods gl1, GenotypeLikelihoods gl2) {
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if ( gl1 == null )
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return gl2;
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if ( gl2 == null )
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return gl1;
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// GL = GL_i + GL_j
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GenotypeLikelihoods gl;
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try {
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gl = (GenotypeLikelihoods)gl1.clone();
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} catch (CloneNotSupportedException e) {
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throw new StingException(e.getMessage());
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}
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assert(gl1.likelihoods.length == gl1.posteriors.length);
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assert(gl1.likelihoods.length == gl2.likelihoods.length);
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assert(gl1.posteriors.length == gl2.posteriors.length);
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for (int i = 0; i < gl1.likelihoods.length; i++) {
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gl.likelihoods[i] += gl2.likelihoods[i];
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gl.posteriors[i] += gl2.posteriors[i];
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}
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return gl;
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}
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/**
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* Cloning of the object
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* @return
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@ -1,75 +0,0 @@
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package org.broadinstitute.sting.gatk.walkers.genotyper;
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import org.broadinstitute.sting.gatk.contexts.AlignmentContext;
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import org.broadinstitute.sting.gatk.refdata.RefMetaDataTracker;
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import org.broadinstitute.sting.utils.*;
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import org.broadinstitute.sting.utils.genotype.GenotypeWriter;
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import org.apache.log4j.Logger;
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import java.util.Set;
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public class SingleSampleGenotypeCalculationModel extends GenotypeCalculationModel {
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private CallResult callsMetrics = new CallResult();
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protected SingleSampleGenotypeCalculationModel() {}
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public void initialize(BaseMismatchModel baseModel,
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Set<String> samples,
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EmpiricalSubstitutionGenotypeLikelihoods.SequencerPlatform platform,
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GenotypeWriter out,
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Logger logger,
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boolean genotypeMode,
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double lod,
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int maxDeletions,
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boolean verbose) {
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super.initialize(baseModel, samples, platform, out, logger, genotypeMode, lod, maxDeletions, verbose);
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// check that this truly is a single-sample bam
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if ( samples.size() > 1 )
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throw new StingException("Single-sample genotype calculation model used on multi-sample bam... aborting");
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}
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public boolean calculateGenotype(RefMetaDataTracker tracker, char ref, AlignmentContext context, DiploidGenotypePriors priors) {
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GenotypeLikelihoods gl = GenotypeLikelihoodsFactory.makeGenotypeLikelihoods(baseModel, priors, defaultPlatform);
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gl.setVerbose(VERBOSE);
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ReadBackedPileup pileup = new ReadBackedPileup(ref, context);
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// check that there aren't too many deletions in the pileup
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pileup.setIncludeDeletionsInPileupString(true);
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if ( Utils.countOccurrences(BasicPileup.DELETION_CHAR, pileup.getBases()) > maxDeletionsInPileup )
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return false;
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gl.add(pileup, true);
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gl.validate();
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SSGenotypeCall call = new SSGenotypeCall(context.getLocation(), ref, gl, pileup);
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callsMetrics.nCalledBases++;
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if ( GENOTYPE_MODE || call.isVariant(call.getReference()) ) {
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double confidence = (GENOTYPE_MODE ? call.getNegLog10PError() : call.toVariation().getNegLog10PError());
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if ( confidence >= LOD_THRESHOLD ) {
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callsMetrics.nConfidentCalls++;
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//System.out.printf("Call %s%n", call);
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out.addGenotypeCall(call);
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} else
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callsMetrics.nNonConfidentCalls++;
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}
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return true;
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}
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public class CallResult {
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long nConfidentCalls = 0;
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long nNonConfidentCalls = 0;
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long nCalledBases = 0;
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CallResult() {}
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public String toString() {
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return String.format("SSG: %d confident and %d non-confident calls were made at %d bases",
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nConfidentCalls, nNonConfidentCalls, nCalledBases);
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}
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}
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}
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@ -40,8 +40,8 @@ import java.io.File;
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public class UnifiedArgumentCollection {
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// control the various models to be used
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@Argument(fullName = "genotypeModel", shortName = "gm", doc = "Genotype calculation model to employ -- SINGLE_SAMPLE and MULTI_SAMPLE_EM are the recommended choices, but it's possible to select MULTI_SAMPLE_ALL_MAFs", required = true)
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public GenotypeCalculationModel.Model genotypeModel = null;
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@Argument(fullName = "genotypeModel", shortName = "gm", doc = "Genotype calculation model to employ -- EM is the default choice; the ALL_MAFS model is experimental", required = false)
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public GenotypeCalculationModel.Model genotypeModel = GenotypeCalculationModel.Model.EM;
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@Argument(fullName = "baseModel", shortName = "bm", doc = "Base substitution model to employ -- EMPIRICAL is the recommended default, but it's possible to select the ONE_STATE and THREE_STATE models for comparison purposes", required = false)
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public BaseMismatchModel baseModel = BaseMismatchModel.EMPIRICAL;
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@ -71,7 +71,8 @@ public class UnifiedArgumentCollection {
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@Argument(fullName = "maxCoverage", shortName = "maxCoverage", doc = "Maximum reads at this locus for it to be callable; to disable, provide value < 1 [default:10,000]", required = false)
|
||||
public Integer MAX_READS_IN_PILEUP = 10000;
|
||||
|
||||
|
||||
//@Argument(fullName = "disableCache", doc = "[ADVANCED] If true, we won't use the caching system. This argument is for testing purposes only", required = false)
|
||||
//public boolean disableCache = false;
|
||||
//public boolean disableCache = false;
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -5,21 +5,20 @@ import org.junit.Test;
|
|||
|
||||
import java.util.Arrays;
|
||||
import java.util.HashMap;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
|
||||
public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
||||
public static String baseTestString() {
|
||||
return "-T SingleSampleGenotyper -R /broad/1KG/reference/human_b36_both.fasta -I /humgen/gsa-scr1/GATK_Data/Validation_Data/NA12878.1kg.p2.chr1_10mb_11_mb.SLX.bam -varout %s";
|
||||
return "-T UnifiedGenotyper -R /broad/1KG/reference/human_b36_both.fasta -I /humgen/gsa-scr1/GATK_Data/Validation_Data/NA12878.1kg.p2.chr1_10mb_11_mb.SLX.bam -varout %s";
|
||||
}
|
||||
|
||||
public static String testGeliLod5() {
|
||||
return baseTestString() + " --variant_output_format GELI -lod 5";
|
||||
}
|
||||
|
||||
private static String OneMb1StateMD5 = "ca300adf2442d8874b4f13819547a7fb";
|
||||
private static String OneMb3StateMD5 = "45caee5f71a30c7175c7389b594369b1";
|
||||
private static String OneMbEmpiricalMD5 = "c8602b745b5c024f09938a9f87f923cf";
|
||||
private static String OneMb1StateMD5 = "cba4436066b5d88a461cc3eba74ad944";
|
||||
private static String OneMb3StateMD5 = "799dde914dd4afbffca9502b7f284780";
|
||||
private static String OneMbEmpiricalMD5 = "2b99b3c667c8ac94e8268b17e6979073";
|
||||
|
||||
// private static String oneMbMD5(BaseMismatchModel m) {
|
||||
// switch (m) {
|
||||
|
|
@ -43,14 +42,14 @@ public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
|||
@Test
|
||||
public void testMultiTechnologies() {
|
||||
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
|
||||
"-T SingleSampleGenotyper" +
|
||||
"-T UnifiedGenotyper" +
|
||||
" -R /broad/1KG/reference/human_b36_both.fasta" +
|
||||
" -I /humgen/gsa-scr1/GATK_Data/Validation_Data/NA12878.1kg.p2.chr1_10mb_11_mb.allTechs.bam" +
|
||||
" -varout %s" +
|
||||
" -L 1:10,000,000-10,100,000" +
|
||||
" -m empirical",
|
||||
" -bm empirical",
|
||||
1,
|
||||
Arrays.asList("09f7ea954a44e68b80726147aee10944"));
|
||||
Arrays.asList("0a923f676111b9bc27ccb1a9b97eafcc"));
|
||||
|
||||
executeTest(String.format("testMultiTechnologies"), spec);
|
||||
}
|
||||
|
|
@ -60,6 +59,7 @@ public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
|||
// testing the cache
|
||||
//
|
||||
// --------------------------------------------------------------------------------------------------------------
|
||||
/*
|
||||
@Test
|
||||
public void testCache() {
|
||||
for ( BaseMismatchModel model : BaseMismatchModel.values() ) {
|
||||
|
|
@ -70,11 +70,12 @@ public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
|||
List<String> withoutCache = executeTest("empirical1MbTest", withoutCacheSpec ).getSecond();
|
||||
|
||||
WalkerTest.WalkerTestSpec withCacheSpec = new WalkerTest.WalkerTestSpec(
|
||||
testGeliLod5() + " -L 1:10,000,000-10,100,000 -m " + model.toString(), 1,
|
||||
testGeliLod5() + " -L 1:10,000,000-10,100,000 -bm " + model.toString(), 1,
|
||||
withoutCache);
|
||||
executeTest(String.format("testCache[%s]", model), withCacheSpec );
|
||||
}
|
||||
}
|
||||
*/
|
||||
|
||||
// --------------------------------------------------------------------------------------------------------------
|
||||
//
|
||||
|
|
@ -84,8 +85,8 @@ public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
|||
@Test
|
||||
public void genotypeTest() {
|
||||
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
|
||||
testGeliLod5() + " -L 1:10,000,000-10,100,000 -m empirical --genotype", 1,
|
||||
Arrays.asList("b4c6d84ea14f9c34b04b799d3edd199a"));
|
||||
testGeliLod5() + " -L 1:10,000,000-10,100,000 -bm empirical --genotype", 1,
|
||||
Arrays.asList("436c0e3365f61bf1d06eb630c025e51b"));
|
||||
executeTest("genotypeTest", spec);
|
||||
}
|
||||
|
||||
|
|
@ -97,14 +98,14 @@ public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
|||
|
||||
@Test
|
||||
public void oneState100bpTest() {
|
||||
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec( testGeliLod5() + " -L 1:10,000,000-10,000,100 -m one_state", 1, Arrays.asList("3cd402d889c015be4a318123468f4262"));
|
||||
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec( testGeliLod5() + " -L 1:10,000,000-10,000,100 -bm one_state", 1, Arrays.asList("3cd402d889c015be4a318123468f4262"));
|
||||
executeTest("oneState100bpTest", spec);
|
||||
}
|
||||
|
||||
@Test
|
||||
public void oneState1MbTest() {
|
||||
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
|
||||
testGeliLod5() + " -L 1:10,000,000-11,000,000 -m one_state",
|
||||
testGeliLod5() + " -L 1:10,000,000-11,000,000 -bm one_state",
|
||||
1, Arrays.asList(OneMb1StateMD5));
|
||||
executeTest("oneState1MbTest", spec);
|
||||
}
|
||||
|
|
@ -112,7 +113,7 @@ public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
|||
@Test
|
||||
public void threeState1MbTest() {
|
||||
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
|
||||
testGeliLod5() + " -L 1:10,000,000-11,000,000 -m three_state", 1,
|
||||
testGeliLod5() + " -L 1:10,000,000-11,000,000 -bm three_state", 1,
|
||||
Arrays.asList(OneMb3StateMD5));
|
||||
executeTest("threeState1MbTest", spec);
|
||||
}
|
||||
|
|
@ -120,7 +121,7 @@ public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
|||
@Test
|
||||
public void empirical1MbTest() {
|
||||
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
|
||||
testGeliLod5() + " -L 1:10,000,000-11,000,000 -m empirical", 1,
|
||||
testGeliLod5() + " -L 1:10,000,000-11,000,000 -bm empirical", 1,
|
||||
Arrays.asList(OneMbEmpiricalMD5));
|
||||
executeTest("empirical1MbTest", spec);
|
||||
}
|
||||
|
|
@ -144,12 +145,12 @@ public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
|||
@Test
|
||||
public void testLOD() {
|
||||
HashMap<Double, String> e = new HashMap<Double, String>();
|
||||
e.put( 10.0, "3c6c40551c42f693736dab5e29f7a76c" );
|
||||
e.put( 3.0, "5c82a81f5919b29058f9ca031c00b7ef" );
|
||||
e.put( 10.0, "3ec7815482112e0b9b4487ec69a52b67" );
|
||||
e.put( 3.0, "20da42fdce2e1c97d9c8d4935d31125d" );
|
||||
|
||||
for ( Map.Entry<Double, String> entry : e.entrySet() ) {
|
||||
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
|
||||
baseTestString() + " --variant_output_format GELI -L 1:10,000,000-11,000,000 -m EMPIRICAL -lod " + entry.getKey(), 1,
|
||||
baseTestString() + " --variant_output_format GELI -L 1:10,000,000-11,000,000 -bm EMPIRICAL -lod " + entry.getKey(), 1,
|
||||
Arrays.asList(entry.getValue()));
|
||||
executeTest("testLOD", spec);
|
||||
}
|
||||
|
|
@ -163,13 +164,13 @@ public class SingleSampleGenotyperIntegrationTest extends WalkerTest {
|
|||
@Test
|
||||
public void testHeterozyosity() {
|
||||
HashMap<Double, String> e = new HashMap<Double, String>();
|
||||
e.put( 0.01, "c6fc697d31cfda563145138126561c77" );
|
||||
e.put( 0.0001, "1a1466b7599c60fad75d0513a0c8496e" );
|
||||
e.put( 1.0 / 1850, "5758dbcdea158fb053fcea22b06befe8" );
|
||||
|
||||
e.put( 0.01, "e7494e6a62bd91ca02537c327a104395" );
|
||||
e.put( 0.0001, "1d51c711353d0db5b54dd0d2a7899c49" );
|
||||
e.put( 1.0 / 1850, "873f558a2c07ec40635e35d275b12d69" );
|
||||
|
||||
for ( Map.Entry<Double, String> entry : e.entrySet() ) {
|
||||
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
|
||||
testGeliLod5() + " -L 1:10,000,000-11,000,000 -m EMPIRICAL --heterozygosity " + entry.getKey(), 1,
|
||||
testGeliLod5() + " -L 1:10,000,000-11,000,000 -bm EMPIRICAL --heterozygosity " + entry.getKey(), 1,
|
||||
Arrays.asList(entry.getValue()));
|
||||
executeTest(String.format("testHeterozyosity[%s]", entry.getKey()), spec);
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue