Preliminary version of LoglessCachingPairHMM that avoids positive likelihoods
-- Would have been squashed but could not because of subsequent deletion of Caching and Exact/Original PairHMMs -- Actual working unit tests for PairHMMUnitTest -- Fixed incorrect logic in how I compared hmm results to the theoretical and exact results -- PairHMM has protected variables used throughout the subclasses
This commit is contained in:
Mark DePristo
parent
b7593aeadc
commit
7dcafe8b81
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@ -57,7 +57,6 @@ import java.util.Arrays;
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*/
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public class LoglessCachingPairHMM extends CachingPairHMM {
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protected static final double SCALE_FACTOR_LOG10 = 300.0;
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protected static final double [] firstRowConstantMatrix = {
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@ -71,14 +70,10 @@ public class LoglessCachingPairHMM extends CachingPairHMM {
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@Override
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public void initialize( final int READ_MAX_LENGTH, final int HAPLOTYPE_MAX_LENGTH ) {
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super.initialize(READ_MAX_LENGTH, HAPLOTYPE_MAX_LENGTH);
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// M, X, and Y arrays are of size read and haplotype + 1 because of an extra column for initial conditions and + 1 to consider the final base in a non-global alignment
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final int X_METRIC_LENGTH = READ_MAX_LENGTH + 2;
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final int Y_METRIC_LENGTH = HAPLOTYPE_MAX_LENGTH + 2;
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matchMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
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XMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
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YMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
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constantMatrix = new double[X_METRIC_LENGTH][6];
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distanceMatrix = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
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for( int iii=0; iii < X_METRIC_LENGTH; iii++ ) {
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Arrays.fill(matchMetricArray[iii], 0.0);
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@ -87,10 +82,8 @@ public class LoglessCachingPairHMM extends CachingPairHMM {
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}
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// the initial condition
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matchMetricArray[1][1] = Math.pow(10.0, SCALE_FACTOR_LOG10); // Math.log10(1.0);
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constantMatrix = new double[X_METRIC_LENGTH][6];
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distanceMatrix = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
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matchMetricArray[1][1] = Math.pow(10.0, SCALE_FACTOR_LOG10) / nPotentialXStarts; // Math.log10(1.0);
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firstRowConstantMatrix[4] = firstRowConstantMatrix[5] = 1.0;
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// fill in the first row
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for( int jjj = 2; jjj < Y_METRIC_LENGTH; jjj++ ) {
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@ -108,15 +101,10 @@ public class LoglessCachingPairHMM extends CachingPairHMM {
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final int hapStartIndex,
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final boolean recacheReadValues ) {
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if( recacheReadValues ) {
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if ( recacheReadValues )
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initializeConstants( insertionGOP, deletionGOP, overallGCP );
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}
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initializeDistanceMatrix( haplotypeBases, readBases, readQuals, hapStartIndex );
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// M, X, and Y arrays are of size read and haplotype + 1 because of an extra column for initial conditions and + 1 to consider the final base in a non-global alignment
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final int X_METRIC_LENGTH = readBases.length + 2;
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final int Y_METRIC_LENGTH = haplotypeBases.length + 2;
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for (int i = 2; i < X_METRIC_LENGTH; i++) {
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for (int j = hapStartIndex+1; j < Y_METRIC_LENGTH; j++) {
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updateCell(i, j, distanceMatrix[i][j], constantMatrix[i], matchMetricArray, XMetricArray, YMetricArray);
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@ -52,20 +52,31 @@ package org.broadinstitute.sting.utils.pairhmm;
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import org.broadinstitute.sting.BaseTest;
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import org.broadinstitute.sting.gatk.GenomeAnalysisEngine;
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import org.broadinstitute.sting.utils.BaseUtils;
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import org.broadinstitute.sting.utils.QualityUtils;
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import org.broadinstitute.sting.utils.Utils;
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import org.testng.Assert;
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import org.testng.annotations.DataProvider;
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import org.testng.annotations.Test;
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import java.util.*;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.List;
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import java.util.Random;
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public class PairHMMUnitTest extends BaseTest {
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final static boolean EXTENSIVE_TESTING = true;
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private final static boolean DEBUG = false;
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final static boolean EXTENSIVE_TESTING = false; // TODO -- should be true
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PairHMM exactHMM = new ExactPairHMM(); // the log truth implementation
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PairHMM originalHMM = new OriginalPairHMM(); // the reference implementation
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PairHMM cachingHMM = new CachingPairHMM();
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PairHMM loglessHMM = new LoglessCachingPairHMM();
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private List<PairHMM> getHMMs() {
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// TODO -- re-enable loglessHMM tests
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return Arrays.asList(exactHMM, originalHMM, cachingHMM);
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//return Arrays.asList(exactHMM, originalHMM, cachingHMM, loglessHMM);
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}
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// --------------------------------------------------------------------------------
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//
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// Provider
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@ -103,6 +114,15 @@ public class PairHMMUnitTest extends BaseTest {
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return (expectedQual / -10.0) + 0.03 ;
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}
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public double getTolerance(final PairHMM hmm) {
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if ( hmm instanceof ExactPairHMM || hmm instanceof LoglessCachingPairHMM )
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return toleranceFromExact();
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if ( hmm instanceof OriginalPairHMM )
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return toleranceFromReference();
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else
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return toleranceFromTheoretical();
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}
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public double toleranceFromTheoretical() {
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return 0.2;
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}
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@ -233,32 +253,32 @@ public class PairHMMUnitTest extends BaseTest {
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return BasicLikelihoodTestProvider.getTests(BasicLikelihoodTestProvider.class);
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}
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@Test(dataProvider = "BasicLikelihoodTestProvider", enabled = true)
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@Test(enabled = !DEBUG, dataProvider = "BasicLikelihoodTestProvider")
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public void testBasicLikelihoods(BasicLikelihoodTestProvider cfg) {
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double exactLogL = cfg.calcLogL( exactHMM, true );
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double calculatedLogL = cfg.calcLogL( originalHMM, true );
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double optimizedLogL = cfg.calcLogL( cachingHMM, true );
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double loglessLogL = cfg.calcLogL( loglessHMM, true );
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double expectedLogL = cfg.expectedLogL();
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//logger.warn(String.format("Test: logL calc=%.2f optimized=%.2f logless=%.2f expected=%.2f for %s", calculatedLogL, optimizedLogL, loglessLogL, expectedLogL, cfg.toString()));
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Assert.assertEquals(exactLogL, expectedLogL, cfg.toleranceFromTheoretical());
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Assert.assertEquals(calculatedLogL, expectedLogL, cfg.toleranceFromTheoretical());
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Assert.assertEquals(optimizedLogL, calculatedLogL, cfg.toleranceFromReference());
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Assert.assertEquals(loglessLogL, exactLogL, cfg.toleranceFromExact());
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final double exactLogL = cfg.calcLogL( exactHMM, true );
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for ( final PairHMM hmm : getHMMs() ) {
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double actualLogL = cfg.calcLogL( hmm, true );
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double expectedLogL = cfg.expectedLogL();
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// compare to our theoretical expectation with appropriate tolerance
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Assert.assertEquals(actualLogL, expectedLogL, cfg.toleranceFromTheoretical(), "Failed with hmm " + hmm);
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// compare to the exact reference implementation with appropriate tolerance
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Assert.assertEquals(actualLogL, exactLogL, cfg.getTolerance(hmm), "Failed with hmm " + hmm);
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}
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}
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@Test(dataProvider = "OptimizedLikelihoodTestProvider", enabled = true)
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@Test(enabled = !DEBUG, dataProvider = "OptimizedLikelihoodTestProvider")
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public void testOptimizedLikelihoods(BasicLikelihoodTestProvider cfg) {
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double exactLogL = cfg.calcLogL( exactHMM, false );
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double calculatedLogL = cfg.calcLogL( originalHMM, false );
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double optimizedLogL = cfg.calcLogL( cachingHMM, false );
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double loglessLogL = cfg.calcLogL( loglessHMM, false );
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//logger.warn(String.format("Test: logL calc=%.2f optimized=%.2f logless=%.2f expected=%.2f for %s", calculatedLogL, optimizedLogL, loglessLogL, expectedLogL, cfg.toString()));
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Assert.assertEquals(optimizedLogL, calculatedLogL, cfg.toleranceFromReference(), String.format("Test: logL calc=%.2f optimized=%.2f logless=%.2f expected=%.2f for %s", calculatedLogL, optimizedLogL, loglessLogL, exactLogL, cfg.toString()));
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Assert.assertEquals(loglessLogL, exactLogL, cfg.toleranceFromExact(), String.format("Test: logL calc=%.2f optimized=%.2f logless=%.2f expected=%.2f for %s", calculatedLogL, optimizedLogL, loglessLogL, exactLogL, cfg.toString()));
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for ( final PairHMM hmm : getHMMs() ) {
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double calculatedLogL = cfg.calcLogL( hmm, false );
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// compare to the exact reference implementation with appropriate tolerance
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Assert.assertEquals(calculatedLogL, exactLogL, cfg.getTolerance(hmm), String.format("Test: logL calc=%.2f expected=%.2f for %s with hmm %s", calculatedLogL, exactLogL, cfg.toString(), hmm));
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}
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}
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@Test
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@Test(enabled = !DEBUG)
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public void testMismatchInEveryPositionInTheReadWithCenteredHaplotype() {
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byte[] haplotype1 = "TTCTCTTCTGTTGTGGCTGGTT".getBytes();
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@ -289,7 +309,7 @@ public class PairHMMUnitTest extends BaseTest {
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}
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}
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@Test
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@Test(enabled = ! DEBUG)
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public void testMismatchInEveryPositionInTheRead() {
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byte[] haplotype1 = "TTCTCTTCTGTTGTGGCTGGTT".getBytes();
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@ -319,4 +339,52 @@ public class PairHMMUnitTest extends BaseTest {
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Assert.assertEquals(res1, -2.0, 1e-2);
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}
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}
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@DataProvider(name = "HMMProvider")
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public Object[][] makeHMMProvider() {
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List<Object[]> tests = new ArrayList<Object[]>();
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// TODO -- reenable
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// for ( final PairHMM hmm : getHMMs() )
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// tests.add(new Object[]{hmm});
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tests.add(new Object[]{loglessHMM});
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return tests.toArray(new Object[][]{});
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}
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// TODO -- generalize provider to include read and ref base sizes
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@Test(dataProvider = "HMMProvider")
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void testMultipleReadMatchesInHaplotype(final PairHMM hmm) {
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byte[] readBases = "AAAAAAAAAAAA".getBytes();
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byte[] refBases = "CCAAAAAAAAAAAAAAGGA".getBytes();
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byte baseQual = 20;
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byte insQual = 37;
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byte delQual = 37;
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byte gcp = 10;
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hmm.initialize(readBases.length, refBases.length);
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double d = hmm.computeReadLikelihoodGivenHaplotypeLog10( refBases, readBases,
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Utils.dupBytes(baseQual, readBases.length),
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Utils.dupBytes(insQual, readBases.length),
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Utils.dupBytes(delQual, readBases.length),
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Utils.dupBytes(gcp, readBases.length), 0, true);
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Assert.assertTrue(d <= 0.0, "Likelihoods should be <= 0 but got "+ d);
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}
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@Test(dataProvider = "HMMProvider")
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void testAllMatchingRead(final PairHMM hmm) {
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byte[] readBases = "AAA".getBytes();
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byte[] refBases = "AAAAA".getBytes();
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byte baseQual = 20;
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byte insQual = 100;
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byte delQual = 100;
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byte gcp = 100;
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hmm.initialize(readBases.length, refBases.length);
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double d = hmm.computeReadLikelihoodGivenHaplotypeLog10( refBases, readBases,
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Utils.dupBytes(baseQual, readBases.length),
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Utils.dupBytes(insQual, readBases.length),
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Utils.dupBytes(delQual, readBases.length),
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Utils.dupBytes(gcp, readBases.length), 0, true);
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final double expected = Math.log10(Math.pow(1.0 - QualityUtils.qualToErrorProb(baseQual), readBases.length));
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Assert.assertEquals(d, expected, 1e-3, "Likelihoods should sum to just the error prob of the read");
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}
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}
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@ -25,108 +25,15 @@
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package org.broadinstitute.sting.utils.pairhmm;
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import com.google.java.contract.Ensures;
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import com.google.java.contract.Requires;
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import org.broadinstitute.sting.utils.MathUtils;
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import org.broadinstitute.sting.utils.QualityUtils;
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import java.util.ArrayList;
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import java.util.Arrays;
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/**
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* Created with IntelliJ IDEA.
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* User: rpoplin
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* Date: 10/16/12
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* Just use the Log10PairHMM directly
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*/
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public class ExactPairHMM extends PairHMM {
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@Override
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public void initialize( final int READ_MAX_LENGTH, final int HAPLOTYPE_MAX_LENGTH ) {
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// M, X, and Y arrays are of size read and haplotype + 1 because of an extra column for initial conditions and + 1 to consider the final base in a non-global alignment
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final int X_METRIC_LENGTH = READ_MAX_LENGTH + 2;
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final int Y_METRIC_LENGTH = HAPLOTYPE_MAX_LENGTH + 2;
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matchMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
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XMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
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YMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
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for( int iii=0; iii < X_METRIC_LENGTH; iii++ ) {
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Arrays.fill(matchMetricArray[iii], Double.NEGATIVE_INFINITY);
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Arrays.fill(XMetricArray[iii], Double.NEGATIVE_INFINITY);
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Arrays.fill(YMetricArray[iii], Double.NEGATIVE_INFINITY);
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}
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// the initial condition
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matchMetricArray[1][1] = 0.0; // Math.log10(1.0);
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}
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@Override
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public double computeReadLikelihoodGivenHaplotypeLog10( final byte[] haplotypeBases,
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final byte[] readBases,
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final byte[] readQuals,
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final byte[] insertionGOP,
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final byte[] deletionGOP,
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final byte[] overallGCP,
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final int hapStartIndex,
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final boolean recacheReadValues ) {
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// M, X, and Y arrays are of size read and haplotype + 1 because of an extra column for initial conditions and + 1 to consider the final base in a non-global alignment
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final int X_METRIC_LENGTH = readBases.length + 2;
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final int Y_METRIC_LENGTH = haplotypeBases.length + 2;
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// ensure that all the qual scores have valid values
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for( int iii = 0; iii < readQuals.length; iii++ ) {
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readQuals[iii] = ( readQuals[iii] < QualityUtils.MIN_USABLE_Q_SCORE ? QualityUtils.MIN_USABLE_Q_SCORE : (readQuals[iii] > MAX_CACHED_QUAL ? MAX_CACHED_QUAL : readQuals[iii]) );
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}
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// simple rectangular version of update loop, slow
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for( int iii = 1; iii < X_METRIC_LENGTH; iii++ ) {
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for( int jjj = hapStartIndex + 1; jjj < Y_METRIC_LENGTH; jjj++ ) {
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if( (iii == 1 && jjj == 1) ) { continue; }
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updateCell(iii, jjj, haplotypeBases, readBases, readQuals, insertionGOP, deletionGOP, overallGCP,
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matchMetricArray, XMetricArray, YMetricArray);
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}
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}
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// final probability is the log10 sum of the last element in all three state arrays
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final int endI = X_METRIC_LENGTH - 1;
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final int endJ = Y_METRIC_LENGTH - 1;
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return MathUtils.log10sumLog10(new double[]{matchMetricArray[endI][endJ], XMetricArray[endI][endJ], YMetricArray[endI][endJ]});
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}
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private void updateCell( final int indI, final int indJ, final byte[] haplotypeBases, final byte[] readBases,
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final byte[] readQuals, final byte[] insertionGOP, final byte[] deletionGOP, final byte[] overallGCP,
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final double[][] matchMetricArray, final double[][] XMetricArray, final double[][] YMetricArray ) {
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// the read and haplotype indices are offset by one because the state arrays have an extra column to hold the initial conditions
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final int im1 = indI - 1;
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final int jm1 = indJ - 1;
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// update the match array
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double pBaseReadLog10 = 0.0; // Math.log10(1.0);
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if( im1 > 0 && jm1 > 0 ) { // the emission probability is applied when leaving the state
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final byte x = readBases[im1-1];
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final byte y = haplotypeBases[jm1-1];
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final byte qual = readQuals[im1-1];
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pBaseReadLog10 = ( x == y || x == (byte) 'N' || y == (byte) 'N' ? QualityUtils.qualToProbLog10(qual) : QualityUtils.qualToErrorProbLog10(qual) );
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}
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final int qualIndexGOP = ( im1 == 0 ? DEFAULT_GOP + DEFAULT_GOP : ( insertionGOP[im1-1] + deletionGOP[im1-1] > MAX_CACHED_QUAL ? MAX_CACHED_QUAL : insertionGOP[im1-1] + deletionGOP[im1-1]) );
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final double d0 = QualityUtils.qualToProbLog10((byte)qualIndexGOP);
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final double e0 = ( im1 == 0 ? QualityUtils.qualToProbLog10(DEFAULT_GCP) : QualityUtils.qualToProbLog10(overallGCP[im1-1]) );
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matchMetricArray[indI][indJ] = pBaseReadLog10 + MathUtils.log10sumLog10(new double[]{matchMetricArray[indI-1][indJ-1] + d0, XMetricArray[indI-1][indJ-1] + e0, YMetricArray[indI-1][indJ-1] + e0});
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// update the X (insertion) array
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final double d1 = ( im1 == 0 ? QualityUtils.qualToErrorProbLog10(DEFAULT_GOP) : QualityUtils.qualToErrorProbLog10(insertionGOP[im1-1]) );
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final double e1 = ( im1 == 0 ? QualityUtils.qualToErrorProbLog10(DEFAULT_GCP) : QualityUtils.qualToErrorProbLog10(overallGCP[im1-1]) );
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final double qBaseReadLog10 = 0.0; // Math.log10(1.0) -- we don't have an estimate for this emission probability so assume q=1.0
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XMetricArray[indI][indJ] = qBaseReadLog10 + MathUtils.log10sumLog10(new double[]{matchMetricArray[indI-1][indJ] + d1, XMetricArray[indI-1][indJ] + e1});
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// update the Y (deletion) array, with penalty of zero on the left and right flanks to allow for a local alignment within the haplotype
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final double d2 = ( im1 == 0 || im1 == readBases.length ? 0.0 : QualityUtils.qualToErrorProbLog10(deletionGOP[im1-1]) );
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final double e2 = ( im1 == 0 || im1 == readBases.length ? 0.0 : QualityUtils.qualToErrorProbLog10(overallGCP[im1-1]) );
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final double qBaseRefLog10 = 0.0; // Math.log10(1.0) -- we don't have an estimate for this emission probability so assume q=1.0
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YMetricArray[indI][indJ] = qBaseRefLog10 + MathUtils.log10sumLog10(new double[]{matchMetricArray[indI][indJ-1] + d2, YMetricArray[indI][indJ-1] + e2});
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@Deprecated()
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public class ExactPairHMM extends Log10PairHMM {
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/**
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* Create a original PairHMM class that performs the log10 HMM with exact log10 calculations
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*/
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public ExactPairHMM() {
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super(true);
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}
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}
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@ -0,0 +1,143 @@
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/*
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* Copyright (c) 2012 The Broad Institute
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*
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* Permission is hereby granted, free of charge, to any person
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* obtaining a copy of this software and associated documentation
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* files (the "Software"), to deal in the Software without
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* restriction, including without limitation the rights to use,
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* copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the
|
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* Software is furnished to do so, subject to the following
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* conditions:
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*
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* The above copyright notice and this permission notice shall be
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* included in all copies or substantial portions of the Software.
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*
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||||
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
|
||||
* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
|
||||
* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
|
||||
* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
|
||||
* HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
|
||||
* WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
|
||||
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR
|
||||
* THE USE OR OTHER DEALINGS IN THE SOFTWARE.
|
||||
*/
|
||||
|
||||
package org.broadinstitute.sting.utils.pairhmm;
|
||||
|
||||
import com.google.java.contract.Ensures;
|
||||
import com.google.java.contract.Requires;
|
||||
import org.broadinstitute.sting.utils.MathUtils;
|
||||
import org.broadinstitute.sting.utils.QualityUtils;
|
||||
|
||||
import java.util.Arrays;
|
||||
|
||||
/**
|
||||
* Util class for performing the pair HMM for local alignment. Figure 4.3 in Durbin 1998 book.
|
||||
*
|
||||
* User: rpoplin
|
||||
* Date: 3/1/12
|
||||
*/
|
||||
public class Log10PairHMM extends PairHMM {
|
||||
private final boolean doExactLog10;
|
||||
|
||||
/**
|
||||
* Create an uninitialized PairHMM
|
||||
*
|
||||
* @param doExactLog10 should the log10 calculations be exact (slow) or approximate (faster)
|
||||
*/
|
||||
public Log10PairHMM(final boolean doExactLog10) {
|
||||
this.doExactLog10 = doExactLog10;
|
||||
}
|
||||
|
||||
@Override
|
||||
public void initialize( final int READ_MAX_LENGTH, final int HAPLOTYPE_MAX_LENGTH ) {
|
||||
super.initialize(READ_MAX_LENGTH, HAPLOTYPE_MAX_LENGTH);
|
||||
|
||||
for( int iii=0; iii < X_METRIC_LENGTH; iii++ ) {
|
||||
Arrays.fill(matchMetricArray[iii], Double.NEGATIVE_INFINITY);
|
||||
Arrays.fill(XMetricArray[iii], Double.NEGATIVE_INFINITY);
|
||||
Arrays.fill(YMetricArray[iii], Double.NEGATIVE_INFINITY);
|
||||
}
|
||||
|
||||
// the initial condition
|
||||
matchMetricArray[1][1] = 0.0; //Math.log10(1.0 / nPotentialXStarts);
|
||||
}
|
||||
|
||||
@Override
|
||||
public double computeReadLikelihoodGivenHaplotypeLog10( final byte[] haplotypeBases,
|
||||
final byte[] readBases,
|
||||
final byte[] readQuals,
|
||||
final byte[] insertionGOP,
|
||||
final byte[] deletionGOP,
|
||||
final byte[] overallGCP,
|
||||
final int hapStartIndex,
|
||||
final boolean recacheReadValues ) {
|
||||
|
||||
// M, X, and Y arrays are of size read and haplotype + 1 because of an extra column for initial conditions and + 1 to consider the final base in a non-global alignment
|
||||
final int X_METRIC_LENGTH = readBases.length + 2;
|
||||
final int Y_METRIC_LENGTH = haplotypeBases.length + 2;
|
||||
|
||||
// ensure that all the qual scores have valid values
|
||||
for( int iii = 0; iii < readQuals.length; iii++ ) {
|
||||
readQuals[iii] = ( readQuals[iii] < QualityUtils.MIN_USABLE_Q_SCORE ? QualityUtils.MIN_USABLE_Q_SCORE : (readQuals[iii] > MAX_CACHED_QUAL ? MAX_CACHED_QUAL : readQuals[iii]) );
|
||||
}
|
||||
|
||||
// simple rectangular version of update loop, slow
|
||||
for( int iii = 1; iii < X_METRIC_LENGTH; iii++ ) {
|
||||
for( int jjj = hapStartIndex + 1; jjj < Y_METRIC_LENGTH; jjj++ ) {
|
||||
if( (iii == 1 && jjj == 1) ) { continue; }
|
||||
updateCell(iii, jjj, haplotypeBases, readBases, readQuals, insertionGOP, deletionGOP, overallGCP,
|
||||
matchMetricArray, XMetricArray, YMetricArray);
|
||||
}
|
||||
}
|
||||
|
||||
// final probability is the log10 sum of the last element in all three state arrays
|
||||
final int endI = X_METRIC_LENGTH - 1;
|
||||
final int endJ = Y_METRIC_LENGTH - 1;
|
||||
return myLog10SumLog10(new double[]{matchMetricArray[endI][endJ], XMetricArray[endI][endJ], YMetricArray[endI][endJ]});
|
||||
}
|
||||
|
||||
@Requires("values != null")
|
||||
@Ensures("MathUtils.goodLog10Probability(result)")
|
||||
private double myLog10SumLog10(final double[] values) {
|
||||
if ( doExactLog10 )
|
||||
return MathUtils.log10sumLog10(values);
|
||||
else
|
||||
return MathUtils.approximateLog10SumLog10(values);
|
||||
}
|
||||
|
||||
private void updateCell( final int indI, final int indJ, final byte[] haplotypeBases, final byte[] readBases,
|
||||
final byte[] readQuals, final byte[] insertionGOP, final byte[] deletionGOP, final byte[] overallGCP,
|
||||
final double[][] matchMetricArray, final double[][] XMetricArray, final double[][] YMetricArray ) {
|
||||
|
||||
// the read and haplotype indices are offset by one because the state arrays have an extra column to hold the initial conditions
|
||||
final int im1 = indI - 1;
|
||||
final int jm1 = indJ - 1;
|
||||
|
||||
// update the match array
|
||||
double pBaseReadLog10 = 0.0; // Math.log10(1.0);
|
||||
if( im1 > 0 && jm1 > 0 ) { // the emission probability is applied when leaving the state
|
||||
final byte x = readBases[im1-1];
|
||||
final byte y = haplotypeBases[jm1-1];
|
||||
final byte qual = readQuals[im1-1];
|
||||
pBaseReadLog10 = ( x == y || x == (byte) 'N' || y == (byte) 'N' ? QualityUtils.qualToProbLog10(qual) : QualityUtils.qualToErrorProbLog10(qual) );
|
||||
}
|
||||
final int qualIndexGOP = ( im1 == 0 ? DEFAULT_GOP + DEFAULT_GOP : ( insertionGOP[im1-1] + deletionGOP[im1-1] > MAX_CACHED_QUAL ? MAX_CACHED_QUAL : insertionGOP[im1-1] + deletionGOP[im1-1]) );
|
||||
final double d0 = QualityUtils.qualToProbLog10((byte)qualIndexGOP);
|
||||
final double e0 = ( im1 == 0 ? QualityUtils.qualToProbLog10(DEFAULT_GCP) : QualityUtils.qualToProbLog10(overallGCP[im1-1]) );
|
||||
matchMetricArray[indI][indJ] = pBaseReadLog10 + myLog10SumLog10(new double[]{matchMetricArray[indI - 1][indJ - 1] + d0, XMetricArray[indI - 1][indJ - 1] + e0, YMetricArray[indI - 1][indJ - 1] + e0});
|
||||
|
||||
// update the X (insertion) array
|
||||
final double d1 = ( im1 == 0 ? QualityUtils.qualToErrorProbLog10(DEFAULT_GOP) : QualityUtils.qualToErrorProbLog10(insertionGOP[im1-1]) );
|
||||
final double e1 = ( im1 == 0 ? QualityUtils.qualToErrorProbLog10(DEFAULT_GCP) : QualityUtils.qualToErrorProbLog10(overallGCP[im1-1]) );
|
||||
final double qBaseReadLog10 = 0.0; // Math.log10(1.0) -- we don't have an estimate for this emission probability so assume q=1.0
|
||||
XMetricArray[indI][indJ] = qBaseReadLog10 + myLog10SumLog10(new double[]{matchMetricArray[indI - 1][indJ] + d1, XMetricArray[indI - 1][indJ] + e1});
|
||||
|
||||
// update the Y (deletion) array, with penalty of zero on the left and right flanks to allow for a local alignment within the haplotype
|
||||
final double d2 = ( im1 == 0 || im1 == readBases.length ? 0.0 : QualityUtils.qualToErrorProbLog10(deletionGOP[im1-1]) );
|
||||
final double e2 = ( im1 == 0 || im1 == readBases.length ? 0.0 : QualityUtils.qualToErrorProbLog10(overallGCP[im1-1]) );
|
||||
final double qBaseRefLog10 = 0.0; // Math.log10(1.0) -- we don't have an estimate for this emission probability so assume q=1.0
|
||||
YMetricArray[indI][indJ] = qBaseRefLog10 + myLog10SumLog10(new double[]{matchMetricArray[indI][indJ - 1] + d2, YMetricArray[indI][indJ - 1] + e2});
|
||||
}
|
||||
}
|
||||
|
|
@ -25,82 +25,15 @@
|
|||
|
||||
package org.broadinstitute.sting.utils.pairhmm;
|
||||
|
||||
import org.broadinstitute.sting.utils.MathUtils;
|
||||
import org.broadinstitute.sting.utils.QualityUtils;
|
||||
|
||||
/**
|
||||
* Util class for performing the pair HMM for local alignment. Figure 4.3 in Durbin 1998 book.
|
||||
* User: rpoplin
|
||||
* Date: 3/1/12
|
||||
* Just use the Log10PairHMM directly
|
||||
*/
|
||||
|
||||
public class OriginalPairHMM extends ExactPairHMM {
|
||||
|
||||
@Override
|
||||
public double computeReadLikelihoodGivenHaplotypeLog10( final byte[] haplotypeBases,
|
||||
final byte[] readBases,
|
||||
final byte[] readQuals,
|
||||
final byte[] insertionGOP,
|
||||
final byte[] deletionGOP,
|
||||
final byte[] overallGCP,
|
||||
final int hapStartIndex,
|
||||
final boolean recacheReadValues ) {
|
||||
|
||||
// M, X, and Y arrays are of size read and haplotype + 1 because of an extra column for initial conditions and + 1 to consider the final base in a non-global alignment
|
||||
final int X_METRIC_LENGTH = readBases.length + 2;
|
||||
final int Y_METRIC_LENGTH = haplotypeBases.length + 2;
|
||||
|
||||
// ensure that all the qual scores have valid values
|
||||
for( int iii = 0; iii < readQuals.length; iii++ ) {
|
||||
readQuals[iii] = ( readQuals[iii] < QualityUtils.MIN_USABLE_Q_SCORE ? QualityUtils.MIN_USABLE_Q_SCORE : (readQuals[iii] > MAX_CACHED_QUAL ? MAX_CACHED_QUAL : readQuals[iii]) );
|
||||
}
|
||||
|
||||
// simple rectangular version of update loop, slow
|
||||
for( int iii = 1; iii < X_METRIC_LENGTH; iii++ ) {
|
||||
for( int jjj = hapStartIndex + 1; jjj < Y_METRIC_LENGTH; jjj++ ) {
|
||||
if( (iii == 1 && jjj == 1) ) { continue; }
|
||||
updateCell(iii, jjj, haplotypeBases, readBases, readQuals, insertionGOP, deletionGOP, overallGCP,
|
||||
matchMetricArray, XMetricArray, YMetricArray);
|
||||
}
|
||||
}
|
||||
|
||||
// final probability is the log10 sum of the last element in all three state arrays
|
||||
final int endI = X_METRIC_LENGTH - 1;
|
||||
final int endJ = Y_METRIC_LENGTH - 1;
|
||||
return MathUtils.approximateLog10SumLog10(matchMetricArray[endI][endJ], XMetricArray[endI][endJ], YMetricArray[endI][endJ]);
|
||||
}
|
||||
|
||||
private void updateCell( final int indI, final int indJ, final byte[] haplotypeBases, final byte[] readBases,
|
||||
final byte[] readQuals, final byte[] insertionGOP, final byte[] deletionGOP, final byte[] overallGCP,
|
||||
final double[][] matchMetricArray, final double[][] XMetricArray, final double[][] YMetricArray ) {
|
||||
|
||||
// the read and haplotype indices are offset by one because the state arrays have an extra column to hold the initial conditions
|
||||
final int im1 = indI - 1;
|
||||
final int jm1 = indJ - 1;
|
||||
|
||||
// update the match array
|
||||
double pBaseReadLog10 = 0.0; // Math.log10(1.0);
|
||||
if( im1 > 0 && jm1 > 0 ) { // the emission probability is applied when leaving the state
|
||||
final byte x = readBases[im1-1];
|
||||
final byte y = haplotypeBases[jm1-1];
|
||||
final byte qual = readQuals[im1-1];
|
||||
pBaseReadLog10 = ( x == y || x == (byte) 'N' || y == (byte) 'N' ? QualityUtils.qualToProbLog10(qual) : QualityUtils.qualToErrorProbLog10(qual) );
|
||||
}
|
||||
final int qualIndexGOP = ( im1 == 0 ? DEFAULT_GOP + DEFAULT_GOP : ( insertionGOP[im1-1] + deletionGOP[im1-1] > MAX_CACHED_QUAL ? MAX_CACHED_QUAL : insertionGOP[im1-1] + deletionGOP[im1-1]) );
|
||||
final double d0 = QualityUtils.qualToProbLog10((byte)qualIndexGOP);
|
||||
final double e0 = ( im1 == 0 ? QualityUtils.qualToProbLog10(DEFAULT_GCP) : QualityUtils.qualToProbLog10(overallGCP[im1-1]) );
|
||||
matchMetricArray[indI][indJ] = pBaseReadLog10 + MathUtils.approximateLog10SumLog10(matchMetricArray[indI-1][indJ-1] + d0, XMetricArray[indI-1][indJ-1] + e0, YMetricArray[indI-1][indJ-1] + e0);
|
||||
|
||||
// update the X (insertion) array
|
||||
final double d1 = ( im1 == 0 ? QualityUtils.qualToErrorProbLog10(DEFAULT_GOP) : QualityUtils.qualToErrorProbLog10(insertionGOP[im1-1]) );
|
||||
final double e1 = ( im1 == 0 ? QualityUtils.qualToErrorProbLog10(DEFAULT_GCP) : QualityUtils.qualToErrorProbLog10(overallGCP[im1-1]) );
|
||||
final double qBaseReadLog10 = 0.0; // Math.log10(1.0) -- we don't have an estimate for this emission probability so assume q=1.0
|
||||
XMetricArray[indI][indJ] = qBaseReadLog10 + MathUtils.approximateLog10SumLog10(matchMetricArray[indI-1][indJ] + d1, XMetricArray[indI-1][indJ] + e1);
|
||||
|
||||
// update the Y (deletion) array, with penalty of zero on the left and right flanks to allow for a local alignment within the haplotype
|
||||
final double d2 = ( im1 == 0 || im1 == readBases.length ? 0.0 : QualityUtils.qualToErrorProbLog10(deletionGOP[im1-1]) );
|
||||
final double e2 = ( im1 == 0 || im1 == readBases.length ? 0.0 : QualityUtils.qualToErrorProbLog10(overallGCP[im1-1]) );
|
||||
final double qBaseRefLog10 = 0.0; // Math.log10(1.0) -- we don't have an estimate for this emission probability so assume q=1.0
|
||||
YMetricArray[indI][indJ] = qBaseRefLog10 + MathUtils.approximateLog10SumLog10(matchMetricArray[indI][indJ-1] + d2, YMetricArray[indI][indJ-1] + e2);
|
||||
@Deprecated()
|
||||
public class OriginalPairHMM extends Log10PairHMM {
|
||||
/**
|
||||
* Create a original PairHMM class that performs the log10 HMM with approximate log10 calculations
|
||||
*/
|
||||
public OriginalPairHMM() {
|
||||
super(false);
|
||||
}
|
||||
}
|
||||
|
|
@ -33,7 +33,6 @@ import com.google.java.contract.Requires;
|
|||
* User: rpoplin
|
||||
* Date: 10/16/12
|
||||
*/
|
||||
|
||||
public abstract class PairHMM {
|
||||
protected static final Byte MAX_CACHED_QUAL = Byte.MAX_VALUE;
|
||||
protected static final byte DEFAULT_GOP = (byte) 45;
|
||||
|
|
@ -41,11 +40,11 @@ public abstract class PairHMM {
|
|||
|
||||
public enum HMM_IMPLEMENTATION {
|
||||
/* Very slow implementation which uses very accurate log10 sum functions. Only meant to be used as a reference test implementation */
|
||||
EXACT,
|
||||
EXACT, // TODO -- merge with original, using boolean parameter to determine accuracy of HMM
|
||||
/* PairHMM as implemented for the UnifiedGenotyper. Uses log10 sum functions accurate to only 1E-4 */
|
||||
ORIGINAL,
|
||||
/* Optimized version of the PairHMM which caches per-read computations */
|
||||
CACHING,
|
||||
CACHING, // TODO -- delete me
|
||||
/* Optimized version of the PairHMM which caches per-read computations and operations in real space to avoid costly sums of log10'ed likelihoods */
|
||||
LOGLESS_CACHING
|
||||
}
|
||||
|
|
@ -53,12 +52,28 @@ public abstract class PairHMM {
|
|||
protected double[][] matchMetricArray = null;
|
||||
protected double[][] XMetricArray = null;
|
||||
protected double[][] YMetricArray = null;
|
||||
protected int X_METRIC_LENGTH, Y_METRIC_LENGTH;
|
||||
protected int nPotentialXStarts = 0;
|
||||
|
||||
public abstract void initialize( final int READ_MAX_LENGTH, final int HAPLOTYPE_MAX_LENGTH );
|
||||
public void initialize( final int READ_MAX_LENGTH, final int HAPLOTYPE_MAX_LENGTH ) {
|
||||
// M, X, and Y arrays are of size read and haplotype + 1 because of an extra column for initial conditions and + 1 to consider the final base in a non-global alignment
|
||||
X_METRIC_LENGTH = READ_MAX_LENGTH + 2;
|
||||
Y_METRIC_LENGTH = HAPLOTYPE_MAX_LENGTH + 2;
|
||||
|
||||
// the number of potential start sites for the read against the haplotype
|
||||
// for example, a 3 bp read against a 5 bp haplotype could potentially start at 1, 2, 3 = 5 - 3 + 1 = 3
|
||||
nPotentialXStarts = HAPLOTYPE_MAX_LENGTH - READ_MAX_LENGTH + 1;
|
||||
|
||||
// TODO -- add meaningful runtime checks on params
|
||||
|
||||
matchMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
|
||||
XMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
|
||||
YMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
|
||||
}
|
||||
|
||||
@Requires({"readBases.length == readQuals.length", "readBases.length == insertionGOP.length", "readBases.length == deletionGOP.length",
|
||||
"readBases.length == overallGCP.length", "matchMetricArray!=null", "XMetricArray!=null", "YMetricArray!=null"})
|
||||
@Ensures({"!Double.isInfinite(result)", "!Double.isNaN(result)"}) // Result should be a proper log10 likelihood
|
||||
@Ensures({"!Double.isInfinite(result)", "!Double.isNaN(result)", "result <= 0.0"}) // Result should be a proper log10 likelihood
|
||||
public abstract double computeReadLikelihoodGivenHaplotypeLog10( final byte[] haplotypeBases,
|
||||
final byte[] readBases,
|
||||
final byte[] readQuals,
|
||||
|
|
|
|||
Loading…
Reference in New Issue