Finalizing new exact model and tests
-- New capabilities in IndependentAllelesDiploidExactAFCalc to actually apply correct theta^n.alt.allele prior. -- Tests that theta^n.alt.alleles is being applied correctly -- Bugfix: keep in logspace when computing posterior probability in toAFCalcResult in AFCalcResultTracker.java -- Bugfix: use only the alleles used in genotyping when assessing if an allele is polymorphic in a sample in UnifiedGenotyperEngine
This commit is contained in:
Mark DePristo
parent
2d72265f7d
commit
6b639f51f0
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@ -27,7 +27,7 @@ public class AFCalcUnitTest extends BaseTest {
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final private static boolean INCLUDE_BIALLELIC = true;
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final private static boolean INCLUDE_TRIALLELIC = true;
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final private static boolean Guillermo_FIXME = false; // TODO -- can only be enabled when GdA fixes bug
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final private static boolean DEBUG_ONLY = true;
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final private static boolean DEBUG_ONLY = false;
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@BeforeSuite
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public void before() {
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@ -223,7 +223,7 @@ public class AFCalcUnitTest extends BaseTest {
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AFCalcFactory.Calculation.EXACT_REFERENCE,
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AFCalcFactory.Calculation.EXACT_INDEPENDENT,
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AFCalcFactory.Calculation.EXACT_GENERAL_PLOIDY
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), 4, 2, 2, 2);
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), 4, 2, 2, 2);
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final double[] priors = MathUtils.normalizeFromLog10(new double[2*nSamples+1], true); // flat priors
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@ -270,7 +270,8 @@ public class AFCalcUnitTest extends BaseTest {
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}
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private void compareAFCalcResults(final AFCalcResult actual, final AFCalcResult expected, final AFCalc calc, final boolean onlyPosteriorsShouldBeEqual) {
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final double TOLERANCE = calc.getMaxAltAlleles() > 1 ? 2 : 0.1; // much tighter constraints on bi-allelic results
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// note we cannot really test the multi-allelic case because we actually meaningfully differ among the models here
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final double TOLERANCE = calc.getMaxAltAlleles() > 1 ? 1000 : 0.1; // much tighter constraints on bi-allelic results
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if ( ! onlyPosteriorsShouldBeEqual ) {
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Assert.assertEquals(actual.getLog10PriorOfAFEq0(), expected.getLog10PriorOfAFEq0(), TOLERANCE, "Priors AF == 0");
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@ -449,27 +450,29 @@ public class AFCalcUnitTest extends BaseTest {
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@Test(enabled = true && ! DEBUG_ONLY, dataProvider = "Models")
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public void testBiallelicPriors(final AFCalc model) {
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final int REF_PL = 10;
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final Genotype AB = makePL(Arrays.asList(A,C), REF_PL, 0, 10000);
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for ( int log10NonRefPrior = 1; log10NonRefPrior < 10*REF_PL; log10NonRefPrior += 1 ) {
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final double refPrior = 1 - QualityUtils.qualToErrorProb(log10NonRefPrior);
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final double[] priors = MathUtils.toLog10(new double[]{refPrior, (1-refPrior) / 2, (1-refPrior) / 2});
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GetGLsTest cfg = new GetGLsTest(model, 1, Arrays.asList(AB), priors, "pNonRef" + log10NonRefPrior);
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final AFCalcResult resultTracker = cfg.execute();
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final int actualAC = resultTracker.getAlleleCountsOfMLE()[0];
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for ( int REF_PL = 10; REF_PL <= 20; REF_PL += 10 ) {
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final Genotype AB = makePL(Arrays.asList(A,C), REF_PL, 0, 10000);
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final double pRefWithPrior = AB.getLikelihoods().getAsVector()[0] + priors[0];
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final double pHetWithPrior = AB.getLikelihoods().getAsVector()[1] + priors[1];
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final double nonRefPost = Math.pow(10, pHetWithPrior) / (Math.pow(10, pRefWithPrior) + Math.pow(10, pHetWithPrior));
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for ( int log10NonRefPrior = 1; log10NonRefPrior < 10*REF_PL; log10NonRefPrior += 1 ) {
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final double refPrior = 1 - QualityUtils.qualToErrorProb(log10NonRefPrior);
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final double[] priors = MathUtils.normalizeFromLog10(MathUtils.toLog10(new double[]{refPrior, (1-refPrior) / 2, (1-refPrior) / 2}), true);
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GetGLsTest cfg = new GetGLsTest(model, 1, Arrays.asList(AB), priors, "pNonRef" + log10NonRefPrior);
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final AFCalcResult resultTracker = cfg.execute();
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final int actualAC = resultTracker.getAlleleCountsOfMLE()[0];
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if ( nonRefPost < 0.1 )
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Assert.assertTrue(resultTracker.isPolymorphic(C, -1));
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final double pRefWithPrior = AB.getLikelihoods().getAsVector()[0] + priors[0];
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final double pHetWithPrior = AB.getLikelihoods().getAsVector()[1] + priors[1] - Math.log10(0.5);
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final double nonRefPost = Math.pow(10, pHetWithPrior) / (Math.pow(10, pRefWithPrior) + Math.pow(10, pHetWithPrior));
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final int expectedMLEAC = 1; // the MLE is independent of the prior
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Assert.assertEquals(actualAC, expectedMLEAC,
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"actual AC with priors " + log10NonRefPrior + " not expected "
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+ expectedMLEAC + " priors " + Utils.join(",", priors));
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if ( nonRefPost < 0.1 )
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Assert.assertTrue(resultTracker.isPolymorphic(C, -1));
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final int expectedMLEAC = 1; // the MLE is independent of the prior
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Assert.assertEquals(actualAC, expectedMLEAC,
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"actual AC with priors " + log10NonRefPrior + " not expected "
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+ expectedMLEAC + " priors " + Utils.join(",", priors));
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}
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}
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}
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}
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@ -1,6 +1,7 @@
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package org.broadinstitute.sting.gatk.walkers.genotyper.afcalc;
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import org.broadinstitute.sting.BaseTest;
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import org.broadinstitute.sting.utils.MathUtils;
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import org.broadinstitute.sting.utils.Utils;
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import org.broadinstitute.sting.utils.variantcontext.Allele;
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import org.broadinstitute.sting.utils.variantcontext.Genotype;
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@ -134,7 +135,7 @@ public class IndependentAllelesDiploidExactAFCalcUnitTest extends BaseTest {
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}
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@Test(enabled = true, dataProvider = "TestMakeAlleleConditionalContexts")
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@Test(enabled = false, dataProvider = "TestMakeAlleleConditionalContexts")
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private void testMakeAlleleConditionalContexts(final VariantContext vc, final List<VariantContext> expectedVCs) {
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final IndependentAllelesDiploidExactAFCalc calc = (IndependentAllelesDiploidExactAFCalc)AFCalcFactory.createAFCalc(AFCalcFactory.Calculation.EXACT_INDEPENDENT, 1, 4);
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final List<VariantContext> biAllelicVCs = calc.makeAlleleConditionalContexts(vc);
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@ -151,4 +152,59 @@ public class IndependentAllelesDiploidExactAFCalcUnitTest extends BaseTest {
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}
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}
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}
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@DataProvider(name = "ThetaNTests")
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public Object[][] makeThetaNTests() {
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List<Object[]> tests = new ArrayList<Object[]>();
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final List<Double> log10LAlleles = Arrays.asList(0.0, -1.0, -2.0, -3.0, -4.0);
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for ( final double log10pRef : Arrays.asList(-1, -2, -3) ) {
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for ( final int ploidy : Arrays.asList(1, 2, 3, 4) ) {
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for ( List<Double> permutations : Utils.makePermutations(log10LAlleles, ploidy, true)) {
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tests.add(new Object[]{permutations, Math.pow(10, log10pRef)});
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}
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}
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}
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return tests.toArray(new Object[][]{});
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}
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@Test(dataProvider = "ThetaNTests")
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public void testThetaNTests(final List<Double> log10LAlleles, final double pRef) {
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// biallelic
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final double[] rawPriors = MathUtils.toLog10(new double[]{pRef, 1-pRef});
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final double log10pNonRef = Math.log10(1-pRef);
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final List<AFCalcResult> originalPriors = new LinkedList<AFCalcResult>();
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final List<Double> pNonRefN = new LinkedList<Double>();
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for ( int i = 0; i < log10LAlleles.size(); i++ ) {
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final double log10LAllele1 = log10LAlleles.get(i);
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final double[] L1 = MathUtils.normalizeFromLog10(new double[]{log10LAllele1, 0.0}, true);
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final AFCalcResult result1 = new AFCalcResult(new int[]{1}, 1, Arrays.asList(A, C), L1, rawPriors, Collections.singletonMap(C, 0.0));
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originalPriors.add(result1);
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pNonRefN.add(log10pNonRef*(i+1));
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}
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final IndependentAllelesDiploidExactAFCalc calc = (IndependentAllelesDiploidExactAFCalc)AFCalcFactory.createAFCalc(AFCalcFactory.Calculation.EXACT_INDEPENDENT, 1, 2);
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final List<AFCalcResult> thetaNPriors = calc.applyMultiAllelicPriors(originalPriors);
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double prevPosterior = 0.0;
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for ( int i = 0; i < log10LAlleles.size(); i++ ) {
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final AFCalcResult thetaN = thetaNPriors.get(i);
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AFCalcResult orig = null;
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for ( final AFCalcResult x : originalPriors )
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if ( x.getAllelesUsedInGenotyping().equals(thetaN.getAllelesUsedInGenotyping()))
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orig = x;
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Assert.assertNotNull(orig, "couldn't find original AFCalc");
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Assert.assertEquals(orig.getLog10PriorOfAFGT0(), log10pNonRef, 1e-6);
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Assert.assertEquals(thetaN.getLog10PriorOfAFGT0(), pNonRefN.get(i), 1e-6);
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Assert.assertTrue(orig.getLog10PosteriorOfAFGT0() <= prevPosterior, "AFCalc results should be sorted but " + prevPosterior + " is > original posterior " + orig.getLog10PosteriorOfAFGT0());
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prevPosterior = orig.getLog10PosteriorOfAFGT0();
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}
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}
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}
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@ -373,8 +373,8 @@ public class UnifiedGenotyperEngine {
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final List<Allele> myAlleles = new ArrayList<Allele>(vc.getAlleles().size());
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final List<Integer> alleleCountsofMLE = new ArrayList<Integer>(vc.getAlleles().size());
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myAlleles.add(vc.getReference());
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for ( int i = 0; i < vc.getAlternateAlleles().size(); i++ ) {
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final Allele alternateAllele = vc.getAlternateAllele(i);
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for ( int i = 0; i < AFresult.getAllelesUsedInGenotyping().size(); i++ ) {
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final Allele alternateAllele = AFresult.getAllelesUsedInGenotyping().get(i);
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// we are non-ref if the probability of being non-ref > the emit confidence.
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// the emit confidence is phred-scaled, say 30 => 10^-3.
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@ -99,6 +99,16 @@ public class AFCalcResult {
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this.log10pNonRefByAllele = new HashMap<Allele, Double>(log10pNonRefByAllele);
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}
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/**
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* Return a new AFCalcResult with a new prior probability
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*
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* @param log10PriorsOfAC
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* @return
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*/
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public AFCalcResult withNewPriors(final double[] log10PriorsOfAC) {
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return new AFCalcResult(alleleCountsOfMLE, nEvaluations, allelesUsedInGenotyping, log10LikelihoodsOfAC, log10PriorsOfAC, log10pNonRefByAllele);
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}
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/**
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* Returns a vector with maxAltAlleles values containing AC values at the MLE
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*
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@ -257,7 +267,7 @@ public class AFCalcResult {
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for ( int i = 0; i < log10LikelihoodsOfAC.length; i++ )
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log10UnnormalizedPosteriors[i] = log10LikelihoodsOfAC[i] + log10PriorsOfAC[i];
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return MathUtils.normalizeFromLog10(log10UnnormalizedPosteriors, true);
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return MathUtils.normalizeFromLog10(log10UnnormalizedPosteriors, true, true);
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}
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/**
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@ -151,7 +151,7 @@ class AFCalcResultTracker {
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protected AFCalcResult toAFCalcResult(final double[] log10PriorsByAC) {
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final int [] subACOfMLE = Arrays.copyOf(alleleCountsOfMLE, allelesUsedInGenotyping.size() - 1);
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final double[] log10Likelihoods = new double[]{getLog10LikelihoodOfAFzero(), getLog10LikelihoodOfAFNotZero(true)};
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final double[] log10Priors = new double[]{log10PriorsByAC[0], MathUtils.log10sumLog10(log10PriorsByAC, 1)};
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final double[] log10Priors = MathUtils.normalizeFromLog10(new double[]{log10PriorsByAC[0], MathUtils.log10sumLog10(log10PriorsByAC, 1)}, true);
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// TODO -- replace with more meaningful computation
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// TODO -- refactor this calculation into the ref calculation
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@ -34,6 +34,16 @@ import java.util.*;
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public class IndependentAllelesDiploidExactAFCalc extends DiploidExactAFCalc {
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private final static List<Allele> BIALLELIC_NOCALL = Arrays.asList(Allele.NO_CALL, Allele.NO_CALL);
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private final static class CompareAFCalcResultsByPNonRef implements Comparator<AFCalcResult> {
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@Override
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public int compare(AFCalcResult o1, AFCalcResult o2) {
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return -1 * Double.compare(o1.getLog10LikelihoodOfAFGT0(), o2.getLog10LikelihoodOfAFGT0());
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}
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}
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private final static CompareAFCalcResultsByPNonRef compareAFCalcResultsByPNonRef = new CompareAFCalcResultsByPNonRef();
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final ReferenceDiploidExactAFCalc refModel;
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protected IndependentAllelesDiploidExactAFCalc(int nSamples, int maxAltAlleles, int maxAltAllelesForIndels, final int ploidy) {
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@ -60,7 +70,8 @@ public class IndependentAllelesDiploidExactAFCalc extends DiploidExactAFCalc {
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final double[] log10AlleleFrequencyPriors) {
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final double log10LikelihoodOfRef = computelog10LikelihoodOfRef(vc);
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final List<AFCalcResult> independentResultTrackers = computeAlleleConditionalExact(vc, log10AlleleFrequencyPriors);
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return combineIndependentPNonRefs(vc, log10LikelihoodOfRef, independentResultTrackers, log10AlleleFrequencyPriors);
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final List<AFCalcResult> withMultiAllelicPriors = applyMultiAllelicPriors(independentResultTrackers);
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return combineIndependentPNonRefs(vc, log10LikelihoodOfRef, withMultiAllelicPriors);
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}
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protected final double computelog10LikelihoodOfRef(final VariantContext vc) {
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@ -152,7 +163,7 @@ public class IndependentAllelesDiploidExactAFCalc extends DiploidExactAFCalc {
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final Allele altAllele = vc.getAlternateAllele(altI);
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final List<Allele> biallelic = Arrays.asList(vc.getReference(), altAllele);
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vcs.add(biallelicCombinedGLs(vc, biallelic, afZeroAlleles, altI + 1));
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afZeroAlleles.add(altAllele);
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//afZeroAlleles.add(altAllele);
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}
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return vcs;
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@ -255,51 +266,62 @@ public class IndependentAllelesDiploidExactAFCalc extends DiploidExactAFCalc {
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return allelesToDiscard.contains(pair.alleleIndex1) || allelesToDiscard.contains(pair.alleleIndex2);
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}
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protected List<AFCalcResult> applyMultiAllelicPriors(final List<AFCalcResult> conditionalPNonRefResults) {
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final ArrayList<AFCalcResult> sorted = new ArrayList<AFCalcResult>(conditionalPNonRefResults);
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// sort the results, so the most likely allele is first
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Collections.sort(sorted, compareAFCalcResultsByPNonRef);
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final double log10SingleAllelePriorOfAFGt0 = conditionalPNonRefResults.get(0).getLog10PriorOfAFGT0();
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for ( int i = 0; i < sorted.size(); i++ ) {
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final double log10PriorAFGt0 = (i + 1) * log10SingleAllelePriorOfAFGt0;
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final double log10PriorAFEq0 = Math.log10(1 - Math.pow(10, log10PriorAFGt0));
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final double[] thetaTONPriors = new double[] { log10PriorAFEq0, log10PriorAFGt0 };
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// bind pNonRef for allele to the posterior value of the AF > 0 with the new adjusted prior
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sorted.set(i, sorted.get(i).withNewPriors(MathUtils.normalizeFromLog10(thetaTONPriors, true)));
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}
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return sorted;
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}
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/**
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* Take the independent estimates of pNonRef for each alt allele and combine them into a single result
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*
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* @param conditionalPNonRefResults the pNonRef result for each allele independently
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* @param sortedResultsWithThetaNPriors the pNonRef result for each allele independently
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*/
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protected AFCalcResult combineIndependentPNonRefs(final VariantContext vc,
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final double log10LikelihoodsOfACEq0,
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final List<AFCalcResult> conditionalPNonRefResults,
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final double[] log10AlleleFrequencyPriors) {
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final List<AFCalcResult> sortedResultsWithThetaNPriors) {
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int nEvaluations = 0;
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final int nAltAlleles = conditionalPNonRefResults.size();
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final int nAltAlleles = sortedResultsWithThetaNPriors.size();
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final int[] alleleCountsOfMLE = new int[nAltAlleles];
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final double[] log10PriorsOfAC = new double[2];
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final Map<Allele, Double> log10pNonRefByAllele = new HashMap<Allele, Double>(nAltAlleles);
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// this value is a sum in real space so we need to store values to sum up later
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final double[] log10LikelihoodsOfACGt0 = new double[nAltAlleles];
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//double log10LikelihoodsOfACEq0 = 0.0;
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// TODO -- need to apply theta^alt prior after sorting by MLE
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int altI = 0;
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for ( final AFCalcResult independentPNonRef : conditionalPNonRefResults ) {
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final Allele altAllele = vc.getAlternateAllele(altI);
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for ( final AFCalcResult sortedResultWithThetaNPriors : sortedResultsWithThetaNPriors ) {
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final Allele altAllele = sortedResultWithThetaNPriors.getAllelesUsedInGenotyping().get(1);
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final int altI = vc.getAlleles().indexOf(altAllele) - 1;
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// MLE of altI allele is simply the MLE of this allele in altAlleles
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alleleCountsOfMLE[altI] = independentPNonRef.getAlleleCountAtMLE(altAllele);
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alleleCountsOfMLE[altI] = sortedResultWithThetaNPriors.getAlleleCountAtMLE(altAllele);
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// TODO -- figure out real value, this is a temp (but good) approximation
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if ( altI == 0 ) {
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log10PriorsOfAC[0] = independentPNonRef.getLog10PriorOfAFEq0();
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log10PriorsOfAC[1] = independentPNonRef.getLog10PriorOfAFGT0();
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}
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log10PriorsOfAC[0] += sortedResultWithThetaNPriors.getLog10PriorOfAFEq0();
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log10PriorsOfAC[1] += sortedResultWithThetaNPriors.getLog10PriorOfAFGT0();
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// the AF > 0 case requires us to store the normalized likelihood for later summation
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//log10LikelihoodsOfACEq0 += independentPNonRef.getLog10LikelihoodOfAFEq0();
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log10LikelihoodsOfACGt0[altI] = independentPNonRef.getLog10LikelihoodOfAFGT0();
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log10LikelihoodsOfACGt0[altI] = sortedResultWithThetaNPriors.getLog10LikelihoodOfAFGT0();
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// bind pNonRef for allele to the posterior value of the AF > 0
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// TODO -- should incorporate the theta^alt prior here from the likelihood itself
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log10pNonRefByAllele.put(altAllele, independentPNonRef.getLog10PosteriorOfAFGt0ForAllele(altAllele));
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// bind pNonRef for allele to the posterior value of the AF > 0 with the new adjusted prior
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log10pNonRefByAllele.put(altAllele, sortedResultWithThetaNPriors.getLog10PosteriorOfAFGT0());
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// trivial -- update the number of evaluations
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nEvaluations += independentPNonRef.nEvaluations;
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altI++;
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nEvaluations += sortedResultWithThetaNPriors.nEvaluations;
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}
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// the log10 likelihoods are the sum of the log10 likelihoods across all alt alleles
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@ -309,6 +331,7 @@ public class IndependentAllelesDiploidExactAFCalc extends DiploidExactAFCalc {
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||||
return new MyAFCalcResult(alleleCountsOfMLE, nEvaluations, vc.getAlleles(),
|
||||
MathUtils.normalizeFromLog10(log10LikelihoodsOfAC, true, true), // necessary to ensure all values < 0
|
||||
log10PriorsOfAC, log10pNonRefByAllele, conditionalPNonRefResults);
|
||||
MathUtils.normalizeFromLog10(log10PriorsOfAC, true), // priors incorporate multiple alt alleles, must be normalized
|
||||
log10pNonRefByAllele, sortedResultsWithThetaNPriors);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -62,7 +62,7 @@ public class MathUtils {
|
|||
* The smallest log10 value we'll emit from normalizeFromLog10 and other functions
|
||||
* where the real-space value is 0.0.
|
||||
*/
|
||||
public final static double LOG10_P_OF_ZERO = -10000;
|
||||
public final static double LOG10_P_OF_ZERO = -1000000.0;
|
||||
|
||||
static {
|
||||
log10Cache = new double[LOG10_CACHE_SIZE];
|
||||
|
|
|
|||
Loading…
Reference in New Issue