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Merge branch 'master' of ssh://nickel.broadinstitute.org/humgen/gsa-scr1/gsa-engineering/git/unstable

This commit is contained in:
Ryan Poplin 2012-04-20 14:03:04 -04:00
parent a57295eb75 40a247e860
commit a1596791af
18 changed files with 856 additions and 398 deletions
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4
public/java/src/org/broadinstitute/sting/gatk/walkers/bqsr/ContextCovariate.java
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@ -125,8 +125,8 @@ public class ContextCovariate implements StandardCovariate {
*/ */
private BitSet contextWith(byte[] bases, int offset, int contextSize) { private BitSet contextWith(byte[] bases, int offset, int contextSize) {
BitSet result = null; BitSet result = null;
if (offset >= contextSize) { if (offset - contextSize + 1 >= 0) {
String context = new String(Arrays.copyOfRange(bases, offset - contextSize, offset)); String context = new String(Arrays.copyOfRange(bases, offset - contextSize + 1, offset + 1));
if (!context.contains("N")) if (!context.contains("N"))
result = BitSetUtils.bitSetFrom(context); result = BitSetUtils.bitSetFrom(context);
} }

2
public/java/src/org/broadinstitute/sting/gatk/walkers/bqsr/Datum.java 100755 → 100644
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@ -76,7 +76,7 @@ public class Datum {
final double doubleMismatches = (double) (numMismatches + SMOOTHING_CONSTANT); final double doubleMismatches = (double) (numMismatches + SMOOTHING_CONSTANT);
final double doubleObservations = (double) (numObservations + SMOOTHING_CONSTANT); final double doubleObservations = (double) (numObservations + SMOOTHING_CONSTANT);
double empiricalQual = -10 * Math.log10(doubleMismatches / doubleObservations); double empiricalQual = -10 * Math.log10(doubleMismatches / doubleObservations);
return Math.min(empiricalQual, (double) QualityUtils.MAX_QUAL_SCORE); return Math.min(empiricalQual, (double) QualityUtils.MAX_RECALIBRATED_Q_SCORE);
} }
byte empiricalQualByte() { byte empiricalQualByte() {

3
public/java/src/org/broadinstitute/sting/gatk/walkers/bqsr/RecalDataManager.java
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@ -31,7 +31,6 @@ import org.broadinstitute.sting.gatk.GenomeAnalysisEngine;
import org.broadinstitute.sting.gatk.report.GATKReport; import org.broadinstitute.sting.gatk.report.GATKReport;
import org.broadinstitute.sting.gatk.report.GATKReportTable; import org.broadinstitute.sting.gatk.report.GATKReportTable;
import org.broadinstitute.sting.utils.BaseUtils; import org.broadinstitute.sting.utils.BaseUtils;
import org.broadinstitute.sting.utils.QualityUtils;
import org.broadinstitute.sting.utils.Utils; import org.broadinstitute.sting.utils.Utils;
import org.broadinstitute.sting.utils.classloader.PluginManager; import org.broadinstitute.sting.utils.classloader.PluginManager;
import org.broadinstitute.sting.utils.collections.Pair; import org.broadinstitute.sting.utils.collections.Pair;
@ -152,7 +151,7 @@ public class RecalDataManager {
ArrayList<Covariate> optionalCovariatesToAdd = new ArrayList<Covariate>(); // initialize an empty array of optional covariates to create the first few tables ArrayList<Covariate> optionalCovariatesToAdd = new ArrayList<Covariate>(); // initialize an empty array of optional covariates to create the first few tables
for (Covariate covariate : requiredCovariates) { for (Covariate covariate : requiredCovariates) {
requiredCovariatesToAdd.add(covariate); requiredCovariatesToAdd.add(covariate);
final Map<BitSet, RecalDatum> recalTable = new HashMap<BitSet, RecalDatum>(QualityUtils.MAX_QUAL_SCORE); // initializing a new recal table for each required covariate (cumulatively) final Map<BitSet, RecalDatum> recalTable = new HashMap<BitSet, RecalDatum>(); // initializing a new recal table for each required covariate (cumulatively)
final BQSRKeyManager keyManager = new BQSRKeyManager(requiredCovariatesToAdd, optionalCovariatesToAdd); // initializing it's corresponding key manager final BQSRKeyManager keyManager = new BQSRKeyManager(requiredCovariatesToAdd, optionalCovariatesToAdd); // initializing it's corresponding key manager
tablesAndKeysMap.put(keyManager, recalTable); // adding the pair table+key to the map tablesAndKeysMap.put(keyManager, recalTable); // adding the pair table+key to the map
} }

4
public/java/src/org/broadinstitute/sting/gatk/walkers/bqsr/RecalDatum.java
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@ -74,7 +74,7 @@ public class RecalDatum extends Datum {
} }
public final void calcCombinedEmpiricalQuality() { public final void calcCombinedEmpiricalQuality() {
this.empiricalQuality = empiricalQualDouble(); // cache the value so we don't call log over and over again this.empiricalQuality = empiricalQualDouble(); // cache the value so we don't call log over and over again
} }
public final void calcEstimatedReportedQuality() { public final void calcEstimatedReportedQuality() {
@ -102,7 +102,7 @@ public class RecalDatum extends Datum {
@Override @Override
public String toString() { public String toString() {
return String.format("%d,%d,%d,%d", numObservations, numMismatches, (byte) Math.floor(getEmpiricalQuality()), (byte) Math.floor(getEstimatedQReported())); return String.format("%d,%d,%d", numObservations, numMismatches, (byte) Math.floor(getEmpiricalQuality()));
} }

11
public/java/src/org/broadinstitute/sting/gatk/walkers/genotyper/UnifiedArgumentCollection.java
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@ -55,13 +55,10 @@ public class UnifiedArgumentCollection {
@Argument(fullName = "pcr_error_rate", shortName = "pcr_error", doc = "The PCR error rate to be used for computing fragment-based likelihoods", required = false) @Argument(fullName = "pcr_error_rate", shortName = "pcr_error", doc = "The PCR error rate to be used for computing fragment-based likelihoods", required = false)
public Double PCR_error = DiploidSNPGenotypeLikelihoodsWithCorrectAlleleOrdering.DEFAULT_PCR_ERROR_RATE; public Double PCR_error = DiploidSNPGenotypeLikelihoodsWithCorrectAlleleOrdering.DEFAULT_PCR_ERROR_RATE;
/** @Argument(fullName = "genotyping_mode", shortName = "gt_mode", doc = "Specifies how to determine the alternate alleles to use for genotyping", required = false)
* Specifies how to determine the alternate allele to use for genotyping
*/
@Argument(fullName = "genotyping_mode", shortName = "gt_mode", doc = "Should we output confident genotypes (i.e. including ref calls) or just the variants?", required = false)
public GenotypeLikelihoodsCalculationModel.GENOTYPING_MODE GenotypingMode = GenotypeLikelihoodsCalculationModel.GENOTYPING_MODE.DISCOVERY; public GenotypeLikelihoodsCalculationModel.GENOTYPING_MODE GenotypingMode = GenotypeLikelihoodsCalculationModel.GENOTYPING_MODE.DISCOVERY;
@Argument(fullName = "output_mode", shortName = "out_mode", doc = "Should we output confident genotypes (i.e. including ref calls) or just the variants?", required = false) @Argument(fullName = "output_mode", shortName = "out_mode", doc = "Specifies which type of calls we should output", required = false)
public UnifiedGenotyperEngine.OUTPUT_MODE OutputMode = UnifiedGenotyperEngine.OUTPUT_MODE.EMIT_VARIANTS_ONLY; public UnifiedGenotyperEngine.OUTPUT_MODE OutputMode = UnifiedGenotyperEngine.OUTPUT_MODE.EMIT_VARIANTS_ONLY;
/** /**
@ -147,11 +144,11 @@ public class UnifiedArgumentCollection {
@Hidden @Hidden
@Argument(fullName = "indelGapContinuationPenalty", shortName = "indelGCP", doc = "Indel gap continuation penalty", required = false) @Argument(fullName = "indelGapContinuationPenalty", shortName = "indelGCP", doc = "Indel gap continuation penalty", required = false)
public double INDEL_GAP_CONTINUATION_PENALTY = 10.0; public byte INDEL_GAP_CONTINUATION_PENALTY = 10;
@Hidden @Hidden
@Argument(fullName = "indelGapOpenPenalty", shortName = "indelGOP", doc = "Indel gap open penalty", required = false) @Argument(fullName = "indelGapOpenPenalty", shortName = "indelGOP", doc = "Indel gap open penalty", required = false)
public double INDEL_GAP_OPEN_PENALTY = 45.0; public byte INDEL_GAP_OPEN_PENALTY = 45;
@Hidden @Hidden
@Argument(fullName = "indelHaplotypeSize", shortName = "indelHSize", doc = "Indel haplotype size", required = false) @Argument(fullName = "indelHaplotypeSize", shortName = "indelHSize", doc = "Indel haplotype size", required = false)

11
public/java/src/org/broadinstitute/sting/gatk/walkers/genotyper/UnifiedGenotyper.java
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@ -116,6 +116,8 @@ import java.util.*;
@ReadFilters( {BadMateFilter.class, MappingQualityUnavailableFilter.class} ) @ReadFilters( {BadMateFilter.class, MappingQualityUnavailableFilter.class} )
@Reference(window=@Window(start=-200,stop=200)) @Reference(window=@Window(start=-200,stop=200))
@By(DataSource.REFERENCE) @By(DataSource.REFERENCE)
// TODO -- When LocusIteratorByState gets cleaned up, we should enable multiple @By sources:
// TODO -- @By( {DataSource.READS, DataSource.REFERENCE_ORDERED_DATA} )
@Downsample(by=DownsampleType.BY_SAMPLE, toCoverage=250) @Downsample(by=DownsampleType.BY_SAMPLE, toCoverage=250)
public class UnifiedGenotyper extends LocusWalker<List<VariantCallContext>, UnifiedGenotyper.UGStatistics> implements TreeReducible<UnifiedGenotyper.UGStatistics>, AnnotatorCompatibleWalker { public class UnifiedGenotyper extends LocusWalker<List<VariantCallContext>, UnifiedGenotyper.UGStatistics> implements TreeReducible<UnifiedGenotyper.UGStatistics>, AnnotatorCompatibleWalker {
@ -155,6 +157,7 @@ public class UnifiedGenotyper extends LocusWalker<List<VariantCallContext>, Unif
@Argument(fullName = "debug_file", shortName = "debug_file", doc = "File to print all of the annotated and detailed debugging output", required = false) @Argument(fullName = "debug_file", shortName = "debug_file", doc = "File to print all of the annotated and detailed debugging output", required = false)
protected PrintStream verboseWriter = null; protected PrintStream verboseWriter = null;
@Hidden
@Argument(fullName = "metrics_file", shortName = "metrics", doc = "File to print any relevant callability metrics output", required = false) @Argument(fullName = "metrics_file", shortName = "metrics", doc = "File to print any relevant callability metrics output", required = false)
protected PrintStream metricsWriter = null; protected PrintStream metricsWriter = null;
@ -347,14 +350,6 @@ public class UnifiedGenotyper extends LocusWalker<List<VariantCallContext>, Unif
} }
public void onTraversalDone(UGStatistics sum) { public void onTraversalDone(UGStatistics sum) {
logger.info(String.format("Visited bases %d", sum.nBasesVisited));
logger.info(String.format("Callable bases %d", sum.nBasesCallable));
logger.info(String.format("Confidently called bases %d", sum.nBasesCalledConfidently));
logger.info(String.format("%% callable bases of all loci %3.3f", sum.percentCallableOfAll()));
logger.info(String.format("%% confidently called bases of all loci %3.3f", sum.percentCalledOfAll()));
logger.info(String.format("%% confidently called bases of callable loci %3.3f", sum.percentCalledOfCallable()));
logger.info(String.format("Actual calls made %d", sum.nCallsMade));
if ( metricsWriter != null ) { if ( metricsWriter != null ) {
metricsWriter.println(String.format("Visited bases %d", sum.nBasesVisited)); metricsWriter.println(String.format("Visited bases %d", sum.nBasesVisited));
metricsWriter.println(String.format("Callable bases %d", sum.nBasesCallable)); metricsWriter.println(String.format("Callable bases %d", sum.nBasesCallable));

424
public/java/src/org/broadinstitute/sting/gatk/walkers/indels/PairHMMIndelErrorModel.java
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@ -31,7 +31,9 @@ import net.sf.samtools.CigarOperator;
import org.broadinstitute.sting.gatk.contexts.ReferenceContext; import org.broadinstitute.sting.gatk.contexts.ReferenceContext;
import org.broadinstitute.sting.utils.Haplotype; import org.broadinstitute.sting.utils.Haplotype;
import org.broadinstitute.sting.utils.MathUtils; import org.broadinstitute.sting.utils.MathUtils;
import org.broadinstitute.sting.utils.PairHMM;
import org.broadinstitute.sting.utils.clipping.ReadClipper; import org.broadinstitute.sting.utils.clipping.ReadClipper;
import org.broadinstitute.sting.utils.exceptions.ReviewedStingException;
import org.broadinstitute.sting.utils.pileup.PileupElement; import org.broadinstitute.sting.utils.pileup.PileupElement;
import org.broadinstitute.sting.utils.pileup.ReadBackedPileup; import org.broadinstitute.sting.utils.pileup.ReadBackedPileup;
import org.broadinstitute.sting.utils.sam.GATKSAMRecord; import org.broadinstitute.sting.utils.sam.GATKSAMRecord;
@ -41,6 +43,7 @@ import org.broadinstitute.sting.utils.variantcontext.Allele;
import java.util.Arrays; import java.util.Arrays;
import java.util.HashMap; import java.util.HashMap;
import java.util.LinkedHashMap; import java.util.LinkedHashMap;
import java.util.Map;
public class PairHMMIndelErrorModel { public class PairHMMIndelErrorModel {
@ -60,12 +63,12 @@ public class PairHMMIndelErrorModel {
private static final int START_HRUN_GAP_IDX = 4; private static final int START_HRUN_GAP_IDX = 4;
private static final int MAX_HRUN_GAP_IDX = 20; private static final int MAX_HRUN_GAP_IDX = 20;
private static final double MIN_GAP_OPEN_PENALTY = 30.0; private static final byte MIN_GAP_OPEN_PENALTY = 30;
private static final double MIN_GAP_CONT_PENALTY = 10.0; private static final byte MIN_GAP_CONT_PENALTY = 10;
private static final double GAP_PENALTY_HRUN_STEP = 1.0; // each increase in hrun decreases gap penalty by this. private static final byte GAP_PENALTY_HRUN_STEP = 1; // each increase in hrun decreases gap penalty by this.
private final double[] GAP_OPEN_PROB_TABLE; private final byte[] GAP_OPEN_PROB_TABLE;
private final double[] GAP_CONT_PROB_TABLE; private final byte[] GAP_CONT_PROB_TABLE;
///////////////////////////// /////////////////////////////
// Private Member Variables // Private Member Variables
@ -86,42 +89,42 @@ public class PairHMMIndelErrorModel {
} }
} }
public PairHMMIndelErrorModel(double indelGOP, double indelGCP, boolean deb, boolean bandedLikelihoods) { public PairHMMIndelErrorModel(byte indelGOP, byte indelGCP, boolean deb, boolean bandedLikelihoods) {
this.DEBUG = deb; this.DEBUG = deb;
this.bandedLikelihoods = bandedLikelihoods; this.bandedLikelihoods = bandedLikelihoods;
// fill gap penalty table, affine naive model: // fill gap penalty table, affine naive model:
this.GAP_CONT_PROB_TABLE = new double[MAX_HRUN_GAP_IDX]; this.GAP_CONT_PROB_TABLE = new byte[MAX_HRUN_GAP_IDX];
this.GAP_OPEN_PROB_TABLE = new double[MAX_HRUN_GAP_IDX]; this.GAP_OPEN_PROB_TABLE = new byte[MAX_HRUN_GAP_IDX];
double gop = -indelGOP/10.0;
double gcp = -indelGCP/10.0;
for (int i = 0; i < START_HRUN_GAP_IDX; i++) { for (int i = 0; i < START_HRUN_GAP_IDX; i++) {
GAP_OPEN_PROB_TABLE[i] = gop; GAP_OPEN_PROB_TABLE[i] = indelGOP;
GAP_CONT_PROB_TABLE[i] = gcp; GAP_CONT_PROB_TABLE[i] = indelGCP;
} }
double step = GAP_PENALTY_HRUN_STEP/10.0; double step = GAP_PENALTY_HRUN_STEP/10.0;
double maxGOP = -MIN_GAP_OPEN_PENALTY/10.0; // phred to log prob // initialize gop and gcp to their default values
double maxGCP = -MIN_GAP_CONT_PENALTY/10.0; // phred to log prob byte gop = indelGOP;
byte gcp = indelGCP;
// all of the following is computed in QUal-space
for (int i=START_HRUN_GAP_IDX; i < MAX_HRUN_GAP_IDX; i++) { for (int i=START_HRUN_GAP_IDX; i < MAX_HRUN_GAP_IDX; i++) {
gop += step; gop -= GAP_PENALTY_HRUN_STEP;
if (gop > maxGOP) if (gop < MIN_GAP_OPEN_PENALTY)
gop = maxGOP; gop = MIN_GAP_OPEN_PENALTY;
gcp += step; gcp -= step;
if(gcp > maxGCP) if(gcp < MIN_GAP_CONT_PENALTY)
gcp = maxGCP; gcp = MIN_GAP_CONT_PENALTY;
GAP_OPEN_PROB_TABLE[i] = gop; GAP_OPEN_PROB_TABLE[i] = gop;
GAP_CONT_PROB_TABLE[i] = gcp; GAP_CONT_PROB_TABLE[i] = gcp;
} }
} }
static private void getContextHomopolymerLength(final byte[] refBytes, int[] hrunArray) { static private void getContextHomopolymerLength(final byte[] refBytes, final int[] hrunArray) {
// compute forward hrun length, example: // compute forward hrun length, example:
// AGGTGACCCCCCTGAGAG // AGGTGACCCCCCTGAGAG
// 001000012345000000 // 001000012345000000
@ -154,203 +157,9 @@ public class PairHMMIndelErrorModel {
} }
private void updateCell(final int indI, final int indJ, final int X_METRIC_LENGTH, final int Y_METRIC_LENGTH, byte[] readBases, byte[] readQuals, byte[] haplotypeBases, private void fillGapProbabilities(final int[] hrunProfile,
double[] currentGOP, double[] currentGCP, double[][] matchMetricArray, double[][] XMetricArray, double[][] YMetricArray) { final byte[] contextLogGapOpenProbabilities,
if (indI > 0 && indJ > 0) { final byte[] contextLogGapContinuationProbabilities) {
final int im1 = indI -1;
final int jm1 = indJ - 1;
// update current point
final byte x = readBases[im1];
final byte y = haplotypeBases[jm1];
final byte qual = readQuals[im1] < 1 ? 1 : (readQuals[im1] > MAX_CACHED_QUAL ? MAX_CACHED_QUAL : readQuals[im1]);
final double pBaseRead = (x == y)? baseMatchArray[(int)qual]:baseMismatchArray[(int)qual];
matchMetricArray[indI][indJ] = pBaseRead + MathUtils.approximateLog10SumLog10(new double[]{matchMetricArray[im1][jm1], XMetricArray[im1][jm1], YMetricArray[im1][jm1]});
final double c1 = indJ == Y_METRIC_LENGTH-1 ? END_GAP_COST : currentGOP[jm1];
final double d1 = indJ == Y_METRIC_LENGTH-1 ? END_GAP_COST : currentGCP[jm1];
XMetricArray[indI][indJ] = MathUtils.approximateLog10SumLog10(matchMetricArray[im1][indJ] + c1, XMetricArray[im1][indJ] + d1);
// update Y array
final double c2 = indI == X_METRIC_LENGTH-1 ? END_GAP_COST : currentGOP[jm1];
final double d2 = indI == X_METRIC_LENGTH-1 ? END_GAP_COST : currentGCP[jm1];
YMetricArray[indI][indJ] = MathUtils.approximateLog10SumLog10(matchMetricArray[indI][jm1] + c2, YMetricArray[indI][jm1] + d2);
}
}
private double computeReadLikelihoodGivenHaplotypeAffineGaps(byte[] haplotypeBases, byte[] readBases, byte[] readQuals,
double[] currentGOP, double[] currentGCP, int indToStart,
double[][] matchMetricArray, double[][] XMetricArray, double[][] YMetricArray) {
final int X_METRIC_LENGTH = readBases.length+1;
final int Y_METRIC_LENGTH = haplotypeBases.length+1;
if (indToStart == 0) {
// default initialization for all arrays
for (int i=0; i < X_METRIC_LENGTH; i++) {
Arrays.fill(matchMetricArray[i],Double.NEGATIVE_INFINITY);
Arrays.fill(YMetricArray[i],Double.NEGATIVE_INFINITY);
Arrays.fill(XMetricArray[i],Double.NEGATIVE_INFINITY);
}
for (int i=1; i < X_METRIC_LENGTH; i++) {
//initialize first column
XMetricArray[i][0] = END_GAP_COST*(i);
}
for (int j=1; j < Y_METRIC_LENGTH; j++) {
// initialize first row
YMetricArray[0][j] = END_GAP_COST*(j);
}
matchMetricArray[0][0]= END_GAP_COST;//Double.NEGATIVE_INFINITY;
XMetricArray[0][0]= YMetricArray[0][0] = 0;
}
if (bandedLikelihoods) {
final double DIAG_TOL = 20; // means that max - min element in diags have to be > this number for banding to take effect.
final int numDiags = X_METRIC_LENGTH + Y_METRIC_LENGTH -1;
final int elemsInDiag = Math.min(X_METRIC_LENGTH, Y_METRIC_LENGTH);
int idxWithMaxElement = 0;
for (int diag=indToStart; diag < numDiags; diag++) {
// compute default I and J start positions at edge of diagonals
int indI = 0;
int indJ = diag;
if (diag >= Y_METRIC_LENGTH ) {
indI = diag-(Y_METRIC_LENGTH-1);
indJ = Y_METRIC_LENGTH-1;
}
// first pass: from max element to edge
int idxLow = idxWithMaxElement;
// reset diag max value before starting
double maxElementInDiag = Double.NEGATIVE_INFINITY;
// set indI, indJ to correct values
indI += idxLow;
indJ -= idxLow;
if (indI >= X_METRIC_LENGTH || indJ < 0) {
idxLow--;
indI--;
indJ++;
}
for (int el = idxLow; el < elemsInDiag; el++) {
updateCell(indI, indJ, X_METRIC_LENGTH, Y_METRIC_LENGTH, readBases, readQuals, haplotypeBases,
currentGOP, currentGCP, matchMetricArray, XMetricArray, YMetricArray);
// update max in diagonal
final double bestMetric = MathUtils.max(matchMetricArray[indI][indJ], XMetricArray[indI][indJ], YMetricArray[indI][indJ]);
// check if we've fallen off diagonal value by threshold
if (bestMetric > maxElementInDiag) {
maxElementInDiag = bestMetric;
idxWithMaxElement = el;
}
else if (bestMetric < maxElementInDiag - DIAG_TOL && idxWithMaxElement > 0)
break; // done w/current diagonal
indI++;
if (indI >=X_METRIC_LENGTH )
break;
indJ--;
if (indJ <= 0)
break;
}
if (idxLow > 0) {
// now do second part in opposite direction
indI = 0;
indJ = diag;
if (diag >= Y_METRIC_LENGTH ) {
indI = diag-(Y_METRIC_LENGTH-1);
indJ = Y_METRIC_LENGTH-1;
}
indI += idxLow-1;
indJ -= idxLow-1;
for (int el = idxLow-1; el >= 0; el--) {
updateCell(indI, indJ, X_METRIC_LENGTH, Y_METRIC_LENGTH, readBases, readQuals, haplotypeBases,
currentGOP, currentGCP, matchMetricArray, XMetricArray, YMetricArray);
// update max in diagonal
final double bestMetric = MathUtils.max(matchMetricArray[indI][indJ], XMetricArray[indI][indJ], YMetricArray[indI][indJ]);
// check if we've fallen off diagonal value by threshold
if (bestMetric > maxElementInDiag) {
maxElementInDiag = bestMetric;
idxWithMaxElement = el;
}
else if (bestMetric < maxElementInDiag - DIAG_TOL)
break; // done w/current diagonal
indJ++;
if (indJ >= Y_METRIC_LENGTH )
break;
indI--;
if (indI <= 0)
break;
}
}
// if (DEBUG)
// System.out.format("Max:%4.1f el:%d\n",maxElementInDiag, idxWithMaxElement);
}
}
else {
// simplified rectangular version of update loop
for (int indI=1; indI < X_METRIC_LENGTH; indI++) {
for (int indJ=indToStart+1; indJ < Y_METRIC_LENGTH; indJ++) {
updateCell(indI, indJ, X_METRIC_LENGTH, Y_METRIC_LENGTH, readBases, readQuals, haplotypeBases,
currentGOP, currentGCP, matchMetricArray, XMetricArray, YMetricArray);
}
}
}
final int bestI = X_METRIC_LENGTH - 1, bestJ = Y_METRIC_LENGTH - 1;
final double bestMetric = MathUtils.approximateLog10SumLog10(new double[]{ matchMetricArray[bestI][bestJ], XMetricArray[bestI][bestJ], YMetricArray[bestI][bestJ] });
/*
if (DEBUG) {
PrintStream outx, outy, outm, outs;
double[][] sumMetrics = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
try {
outx = new PrintStream("datax.txt");
outy = new PrintStream("datay.txt");
outm = new PrintStream("datam.txt");
outs = new PrintStream("datas.txt");
double metrics[] = new double[3];
for (int indI=0; indI < X_METRIC_LENGTH; indI++) {
for (int indJ=0; indJ < Y_METRIC_LENGTH; indJ++) {
metrics[0] = matchMetricArray[indI][indJ];
metrics[1] = XMetricArray[indI][indJ];
metrics[2] = YMetricArray[indI][indJ];
//sumMetrics[indI][indJ] = MathUtils.softMax(metrics);
outx.format("%4.1f ", metrics[1]);
outy.format("%4.1f ", metrics[2]);
outm.format("%4.1f ", metrics[0]);
outs.format("%4.1f ", MathUtils.softMax(metrics));
}
outx.println(); outm.println();outy.println(); outs.println();
}
outm.close(); outx.close(); outy.close();
} catch (java.io.IOException e) { throw new UserException("bla");}
}
*/
return bestMetric;
}
private void fillGapProbabilities(int[] hrunProfile,
double[] contextLogGapOpenProbabilities, double[] contextLogGapContinuationProbabilities) {
// fill based on lookup table // fill based on lookup table
for (int i = 0; i < hrunProfile.length; i++) { for (int i = 0; i < hrunProfile.length; i++) {
if (hrunProfile[i] >= MAX_HRUN_GAP_IDX) { if (hrunProfile[i] >= MAX_HRUN_GAP_IDX) {
@ -372,27 +181,8 @@ public class PairHMMIndelErrorModel {
final int readCounts[] = new int[pileup.getNumberOfElements()]; final int readCounts[] = new int[pileup.getNumberOfElements()];
int readIdx=0; int readIdx=0;
LinkedHashMap<Allele,double[]> gapOpenProbabilityMap = new LinkedHashMap<Allele,double[]>();
LinkedHashMap<Allele,double[]> gapContProbabilityMap = new LinkedHashMap<Allele,double[]>();
// will context dependent probabilities based on homopolymer run. Probabilities are filled based on total complete haplotypes.
// todo -- refactor into separate function
for (Allele a: haplotypeMap.keySet()) {
Haplotype haplotype = haplotypeMap.get(a);
byte[] haplotypeBases = haplotype.getBases();
double[] contextLogGapOpenProbabilities = new double[haplotypeBases.length];
double[] contextLogGapContinuationProbabilities = new double[haplotypeBases.length];
// get homopolymer length profile for current haplotype
int[] hrunProfile = new int[haplotypeBases.length];
getContextHomopolymerLength(haplotypeBases,hrunProfile);
fillGapProbabilities(hrunProfile, contextLogGapOpenProbabilities, contextLogGapContinuationProbabilities);
gapOpenProbabilityMap.put(a,contextLogGapOpenProbabilities);
gapContProbabilityMap.put(a,contextLogGapContinuationProbabilities);
}
PairHMM pairHMM = new PairHMM(bandedLikelihoods);
for (PileupElement p: pileup) { for (PileupElement p: pileup) {
// > 1 when the read is a consensus read representing multiple independent observations // > 1 when the read is a consensus read representing multiple independent observations
readCounts[readIdx] = p.getRepresentativeCount(); readCounts[readIdx] = p.getRepresentativeCount();
@ -406,14 +196,32 @@ public class PairHMMIndelErrorModel {
} }
} }
else { else {
if (DEBUG) {
System.out.format("Read Name:%s, aln start:%d aln stop:%d orig cigar:%s\n",p.getRead().getReadName(), p.getRead().getAlignmentStart(), p.getRead().getAlignmentEnd(), p.getRead().getCigarString());
}
// System.out.format("%d %s\n",p.getRead().getAlignmentStart(), p.getRead().getClass().getName()); // System.out.format("%d %s\n",p.getRead().getAlignmentStart(), p.getRead().getClass().getName());
GATKSAMRecord read = ReadClipper.hardClipAdaptorSequence(p.getRead()); GATKSAMRecord read = ReadClipper.hardClipAdaptorSequence(p.getRead());
if (read.isEmpty()) if (read.isEmpty())
continue; continue;
if(ReadUtils.is454Read(read)) { if (read.getUnclippedEnd() > ref.getWindow().getStop())
read = ReadClipper.hardClipByReferenceCoordinatesRightTail(read, ref.getWindow().getStop());
if (read.isEmpty())
continue; continue;
}
if (read.getUnclippedStart() < ref.getWindow().getStart())
read = ReadClipper.hardClipByReferenceCoordinatesLeftTail (read, ref.getWindow().getStart());
if (read.isEmpty())
continue;
// hard-clip low quality ends - this may introduce extra H elements in CIGAR string
read = ReadClipper.hardClipLowQualEnds(read,(byte)BASE_QUAL_THRESHOLD );
if (read.isEmpty())
continue;
// get bases of candidate haplotypes that overlap with reads // get bases of candidate haplotypes that overlap with reads
final int trailingBases = 3; final int trailingBases = 3;
@ -469,54 +277,56 @@ public class PairHMMIndelErrorModel {
unclippedReadBases = read.getReadBases(); unclippedReadBases = read.getReadBases();
unclippedReadQuals = read.getBaseQualities(); unclippedReadQuals = read.getBaseQualities();
// Do a stricter base clipping than provided by CIGAR string, since this one may be too conservative, final int extraOffset = Math.abs(eventLength);
// and may leave a string of Q2 bases still hanging off the reads.
for (int i=numStartSoftClippedBases; i < unclippedReadBases.length; i++) {
if (unclippedReadQuals[i] < BASE_QUAL_THRESHOLD)
numStartClippedBases++;
else
break;
} /**
for (int i=unclippedReadBases.length-numEndSoftClippedBases-1; i >= 0; i-- ){ * Compute genomic locations that candidate haplotypes will span.
if (unclippedReadQuals[i] < BASE_QUAL_THRESHOLD) * Read start and stop locations (variables readStart and readEnd) are the original unclipped positions from SAMRecord,
numEndClippedBases++; * adjusted by hard clips from Cigar string and by qual-based soft-clipping performed above.
else * We will propose haplotypes that overlap the read with some padding.
break; * True read start = readStart + numStartClippedBases - ReadUtils.getFirstInsertionOffset(read)
} * Last term is because if a read starts with an insertion then these bases are not accounted for in readStart.
* trailingBases is a padding constant(=3) and we additionally add abs(eventLength) to both sides of read to be able to
* differentiate context between two haplotypes
*/
long startLocationInRefForHaplotypes = Math.max(readStart + numStartClippedBases - trailingBases - ReadUtils.getFirstInsertionOffset(read)-extraOffset, 0);
long stopLocationInRefForHaplotypes = readEnd -numEndClippedBases + trailingBases + ReadUtils.getLastInsertionOffset(read)+extraOffset;
int extraOffset = Math.abs(eventLength); if (DEBUG)
System.out.format("orig Start:%d orig stop: %d\n", startLocationInRefForHaplotypes, stopLocationInRefForHaplotypes);
long start = Math.max(readStart + numStartClippedBases - trailingBases - ReadUtils.getFirstInsertionOffset(read)-extraOffset, 0);
long stop = readEnd -numEndClippedBases + trailingBases + ReadUtils.getLastInsertionOffset(read)+extraOffset;
// Variables start and stop are coordinates (inclusive) where we want to get the haplotype from.
int readLength = read.getReadLength()-numStartSoftClippedBases-numEndSoftClippedBases; int readLength = read.getReadLength()-numStartSoftClippedBases-numEndSoftClippedBases;
// check if start of read will be before start of reference context // check if start of read will be before start of reference context
if (start < ref.getWindow().getStart())// read starts before haplotype: read will have to be cut if (startLocationInRefForHaplotypes < ref.getWindow().getStart()) {
start = ref.getWindow().getStart(); // read starts before haplotype: read will have to be cut
//numStartClippedBases += ref.getWindow().getStart() - startLocationInRefForHaplotypes;
startLocationInRefForHaplotypes = ref.getWindow().getStart();
}
// check also if end of read will go beyond reference context // check also if end of read will go beyond reference context
if (stop > ref.getWindow().getStop()) if (stopLocationInRefForHaplotypes > ref.getWindow().getStop()) {
stop = ref.getWindow().getStop(); //numEndClippedBases += stopLocationInRefForHaplotypes - ref.getWindow().getStop();
stopLocationInRefForHaplotypes = ref.getWindow().getStop();
}
// if there's an insertion in the read, the read stop position will be less than start + read length, // if there's an insertion in the read, the read stop position will be less than start + read legnth,
// but we want to compute likelihoods in the whole region that a read might overlap // but we want to compute likelihoods in the whole region that a read might overlap
if (stop <= start + readLength) { if (stopLocationInRefForHaplotypes <= startLocationInRefForHaplotypes + readLength) {
stop = start + readLength-1; stopLocationInRefForHaplotypes = startLocationInRefForHaplotypes + readLength-1;
} }
// ok, we now figured out total number of clipped bases on both ends. // ok, we now figured out total number of clipped bases on both ends.
// Figure out where we want to place the haplotype to score read against // Figure out where we want to place the haplotype to score read against
/*
if (DEBUG) if (DEBUG)
System.out.format("numStartClippedBases: %d numEndClippedBases: %d WinStart:%d WinStop:%d start: %d stop: %d readLength: %d\n", System.out.format("numStartClippedBases: %d numEndClippedBases: %d WinStart:%d WinStop:%d start: %d stop: %d readLength: %d\n",
numStartClippedBases, numEndClippedBases, ref.getWindow().getStart(), ref.getWindow().getStop(), start, stop, read.getReadLength()); numStartClippedBases, numEndClippedBases, ref.getWindow().getStart(), ref.getWindow().getStop(), startLocationInRefForHaplotypes, stopLocationInRefForHaplotypes, read.getReadLength());
*/
LinkedHashMap<Allele,Double> readEl = new LinkedHashMap<Allele,Double>(); LinkedHashMap<Allele,Double> readEl = new LinkedHashMap<Allele,Double>();
/**
* Check if we'll end up with an empty read once all clipping is done
*/
if (numStartClippedBases + numEndClippedBases >= unclippedReadBases.length) { if (numStartClippedBases + numEndClippedBases >= unclippedReadBases.length) {
int j=0; int j=0;
for (Allele a: haplotypeMap.keySet()) { for (Allele a: haplotypeMap.keySet()) {
@ -537,69 +347,67 @@ public class PairHMMIndelErrorModel {
// initialize path metric and traceback memories for likelihood computation // initialize path metric and traceback memories for likelihood computation
double[][] matchMetricArray = null, XMetricArray = null, YMetricArray = null; double[][] matchMetricArray = null, XMetricArray = null, YMetricArray = null;
byte[] previousHaplotypeSeen = null; byte[] previousHaplotypeSeen = null;
double[] previousGOP = null; final byte[] contextLogGapOpenProbabilities = new byte[readBases.length];
double[] previousGCP = null; final byte[] contextLogGapContinuationProbabilities = new byte[readBases.length];
int startIdx;
// get homopolymer length profile for current haplotype
int[] hrunProfile = new int[readBases.length];
getContextHomopolymerLength(readBases,hrunProfile);
fillGapProbabilities(hrunProfile, contextLogGapOpenProbabilities, contextLogGapContinuationProbabilities);
for (Allele a: haplotypeMap.keySet()) { for (Allele a: haplotypeMap.keySet()) {
Haplotype haplotype = haplotypeMap.get(a); Haplotype haplotype = haplotypeMap.get(a);
if (stop > haplotype.getStopPosition())
stop = haplotype.getStopPosition();
if (start < haplotype.getStartPosition()) if (stopLocationInRefForHaplotypes > haplotype.getStopPosition())
start = haplotype.getStartPosition(); stopLocationInRefForHaplotypes = haplotype.getStopPosition();
// cut haplotype bases if (startLocationInRefForHaplotypes < haplotype.getStartPosition())
long indStart = start - haplotype.getStartPosition(); startLocationInRefForHaplotypes = haplotype.getStartPosition();
long indStop = stop - haplotype.getStartPosition();
final long indStart = startLocationInRefForHaplotypes - haplotype.getStartPosition();
final long indStop = stopLocationInRefForHaplotypes - haplotype.getStartPosition();
double readLikelihood; double readLikelihood;
if (DEBUG) if (DEBUG)
System.out.format("indStart: %d indStop: %d WinStart:%d WinStop:%d start: %d stop: %d readLength: %d C:%s\n", System.out.format("indStart: %d indStop: %d WinStart:%d WinStop:%d start: %d stop: %d readLength: %d C:%s\n",
indStart, indStop, ref.getWindow().getStart(), ref.getWindow().getStop(), start, stop, read.getReadLength(), read.getCigar().toString()); indStart, indStop, ref.getWindow().getStart(), ref.getWindow().getStop(), startLocationInRefForHaplotypes, stopLocationInRefForHaplotypes, read.getReadLength(), read.getCigar().toString());
if (indStart < 0 || indStop >= haplotype.getBases().length || indStart > indStop) {
// read spanned more than allowed reference context: we currently can't deal with this
readLikelihood =0;
} else
{
final byte[] haplotypeBases = Arrays.copyOfRange(haplotype.getBases(), final byte[] haplotypeBases = Arrays.copyOfRange(haplotype.getBases(),
(int)indStart, (int)indStop); (int)indStart, (int)indStop);
if (matchMetricArray == null) { final int X_METRIC_LENGTH = readBases.length+2;
final int X_METRIC_LENGTH = readBases.length+1; final int Y_METRIC_LENGTH = haplotypeBases.length+2;
final int Y_METRIC_LENGTH = haplotypeBases.length+1;
if (matchMetricArray == null) {
//no need to reallocate arrays for each new haplotype, as length won't change
matchMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH]; matchMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
XMetricArray = 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]; YMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
PairHMM.initializeArrays(matchMetricArray, XMetricArray, YMetricArray, X_METRIC_LENGTH);
} }
final double[] currentContextGOP = Arrays.copyOfRange(gapOpenProbabilityMap.get(a), (int)indStart, (int)indStop);
final double[] currentContextGCP = Arrays.copyOfRange(gapContProbabilityMap.get(a), (int)indStart, (int)indStop); int startIndexInHaplotype = 0;
if (previousHaplotypeSeen == null) if (previousHaplotypeSeen != null)
startIdx = 0; startIndexInHaplotype = computeFirstDifferingPosition(haplotypeBases, previousHaplotypeSeen);
else {
final int s1 = computeFirstDifferingPosition(haplotypeBases, previousHaplotypeSeen);
final int s2 = computeFirstDifferingPosition(currentContextGOP, previousGOP);
final int s3 = computeFirstDifferingPosition(currentContextGCP, previousGCP);
startIdx = Math.min(Math.min(s1, s2), s3);
}
previousHaplotypeSeen = haplotypeBases.clone(); previousHaplotypeSeen = haplotypeBases.clone();
previousGOP = currentContextGOP.clone();
previousGCP = currentContextGCP.clone();
readLikelihood = pairHMM.computeReadLikelihoodGivenHaplotype(haplotypeBases, readBases, readQuals,
contextLogGapOpenProbabilities, contextLogGapOpenProbabilities, contextLogGapContinuationProbabilities,
startIndexInHaplotype, matchMetricArray, XMetricArray, YMetricArray);
readLikelihood = computeReadLikelihoodGivenHaplotypeAffineGaps(haplotypeBases, readBases, readQuals,
currentContextGOP, currentContextGCP, startIdx, matchMetricArray, XMetricArray, YMetricArray);
if (DEBUG) { if (DEBUG) {
System.out.println("H:"+new String(haplotypeBases)); System.out.println("H:"+new String(haplotypeBases));
System.out.println("R:"+new String(readBases)); System.out.println("R:"+new String(readBases));
System.out.format("L:%4.2f\n",readLikelihood); System.out.format("L:%4.2f\n",readLikelihood);
System.out.format("StPos:%d\n", startIdx); System.out.format("StPos:%d\n", startIndexInHaplotype);
} }
}
readEl.put(a,readLikelihood); readEl.put(a,readLikelihood);
readLikelihoods[readIdx][j++] = readLikelihood; readLikelihoods[readIdx][j++] = readLikelihood;
} }

4
public/java/src/org/broadinstitute/sting/gatk/walkers/varianteval/stratifications/AlleleCount.java
View File

@ -20,10 +20,8 @@ import java.util.*;
public class AlleleCount extends VariantStratifier { public class AlleleCount extends VariantStratifier {
@Override @Override
public void initialize() { public void initialize() {
List<RodBinding<VariantContext>> evals = getVariantEvalWalker().getEvals();
// we can only work with a single eval VCF, and it must have genotypes // we can only work with a single eval VCF, and it must have genotypes
if ( evals.size() != 1 ) if ( getVariantEvalWalker().getEvals().size() != 1 && !getVariantEvalWalker().mergeEvals )
throw new UserException.BadArgumentValue("AlleleCount", "AlleleCount stratification only works with a single eval vcf"); throw new UserException.BadArgumentValue("AlleleCount", "AlleleCount stratification only works with a single eval vcf");
// There are 2 x n sample chromosomes for diploids // There are 2 x n sample chromosomes for diploids

8
public/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantDataManager.java
View File

@ -241,14 +241,6 @@ public class VariantDataManager {
value += -0.25 + 0.5 * GenomeAnalysisEngine.getRandomGenerator().nextDouble(); value += -0.25 + 0.5 * GenomeAnalysisEngine.getRandomGenerator().nextDouble();
} }
if (vc.isIndel() && annotationKey.equalsIgnoreCase("QD")) {
// normalize QD by event length for indel case
int eventLength = Math.abs(vc.getAlternateAllele(0).getBaseString().length() - vc.getReference().getBaseString().length()); // ignore multi-allelic complication here for now
if (eventLength > 0) { // sanity check
value /= (double)eventLength;
}
}
if( jitter && annotationKey.equalsIgnoreCase("HaplotypeScore") && MathUtils.compareDoubles(value, 0.0, 0.0001) == 0 ) { value = -0.2 + 0.4*GenomeAnalysisEngine.getRandomGenerator().nextDouble(); } if( jitter && annotationKey.equalsIgnoreCase("HaplotypeScore") && MathUtils.compareDoubles(value, 0.0, 0.0001) == 0 ) { value = -0.2 + 0.4*GenomeAnalysisEngine.getRandomGenerator().nextDouble(); }
if( jitter && annotationKey.equalsIgnoreCase("FS") && MathUtils.compareDoubles(value, 0.0, 0.001) == 0 ) { value = -0.2 + 0.4*GenomeAnalysisEngine.getRandomGenerator().nextDouble(); } if( jitter && annotationKey.equalsIgnoreCase("FS") && MathUtils.compareDoubles(value, 0.0, 0.001) == 0 ) { value = -0.2 + 0.4*GenomeAnalysisEngine.getRandomGenerator().nextDouble(); }
} catch( Exception e ) { } catch( Exception e ) {

259
public/java/src/org/broadinstitute/sting/utils/PairHMM.java 100644
View File

@ -0,0 +1,259 @@
/*
* Copyright (c) 2012, The Broad Institute
*
* Permission is hereby granted, free of charge, to any person
* obtaining a copy of this software and associated documentation
* files (the "Software"), to deal in the Software without
* restriction, including without limitation the rights to use,
* copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following
* conditions:
*
* The above copyright notice and this permission notice shall be
* included in all copies or substantial portions of the Software.
* 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;
import com.google.java.contract.Ensures;
import com.google.java.contract.Requires;
import java.util.*;
/**
* 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 PairHMM {
private static final int MAX_CACHED_QUAL = (int)Byte.MAX_VALUE;
private static final byte DEFAULT_GOP = (byte) 45;
private static final byte DEFAULT_GCP = (byte) 10;
private static final double BANDING_TOLERANCE = 22.0;
private static final int BANDING_CLUSTER_WINDOW = 12;
private final boolean noBanded;
public PairHMM() {
noBanded = false;
}
public PairHMM( final boolean noBanded ) {
this.noBanded = noBanded;
}
public static void initializeArrays(final double[][] matchMetricArray, final double[][] XMetricArray, final double[][] YMetricArray,
final int X_METRIC_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);
}
@Requires({"readBases.length == readQuals.length","readBases.length == insertionGOP.length","readBases.length == deletionGOP.length","readBases.length == overallGCP.length"})
@Ensures({"!Double.isInfinite(result)", "!Double.isNaN(result)"}) // Result should be a proper log10 probability
public double computeReadLikelihoodGivenHaplotype( final byte[] haplotypeBases, final byte[] readBases, final byte[] readQuals,
final byte[] insertionGOP, final byte[] deletionGOP, final byte[] overallGCP ) {
// 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;
// initial arrays to hold the probabilities of being in the match, insertion and deletion cases
final double[][] matchMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
final double[][] XMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
final double[][] YMetricArray = new double[X_METRIC_LENGTH][Y_METRIC_LENGTH];
initializeArrays(matchMetricArray, XMetricArray, YMetricArray, X_METRIC_LENGTH);
return computeReadLikelihoodGivenHaplotype(haplotypeBases, readBases, readQuals, insertionGOP, deletionGOP, overallGCP, 0, matchMetricArray, XMetricArray, YMetricArray);
}
@Requires({"readBases.length == readQuals.length","readBases.length == insertionGOP.length","readBases.length == deletionGOP.length","readBases.length == overallGCP.length"})
@Ensures({"!Double.isInfinite(result)", "!Double.isNaN(result)"}) // Result should be a proper log10 probability
public double computeReadLikelihoodGivenHaplotype( final byte[] haplotypeBases, final byte[] readBases, final byte[] readQuals,
final byte[] insertionGOP, final byte[] deletionGOP, final byte[] overallGCP, final int hapStartIndex,
final double[][] matchMetricArray, final double[][] XMetricArray, final double[][] YMetricArray ) {
// 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]) );
}
if( false ) {
final ArrayList<Integer> workQueue = new ArrayList<Integer>(); // holds a queue of starting work location (indices along the diagonal). Will be sorted each step
final ArrayList<Integer> workToBeAdded = new ArrayList<Integer>();
final ArrayList<Double> calculatedValues = new ArrayList<Double>();
final int numDiags = X_METRIC_LENGTH + Y_METRIC_LENGTH - 1;
workQueue.add( 1 ); // Always start a new thread at the baseline because of partially repeating sequences that match better in the latter half of the haplotype
for(int diag = 3; diag < numDiags; diag++) { // diag = 3 is the (1,2) element of the metric arrays. (1,1) is the initial condition and is purposefully skipped over
//Collections.sort(workQueue); // no need to sort because elements are guaranteed to be in ascending order
int el = 1;
for( int work : workQueue ) {
// choose the appropriate diagonal baseline location
int iii = 0;
int jjj = diag;
if( diag > Y_METRIC_LENGTH ) {
iii = diag - Y_METRIC_LENGTH;
jjj = Y_METRIC_LENGTH;
}
// move to the starting work location along the diagonal
iii += work;
jjj -= work;
while( iii >= X_METRIC_LENGTH || jjj <= 0 ) {
iii--;
jjj++;
work--;
}
if( !detectClusteredStartLocations(workToBeAdded, work ) ) {
workToBeAdded.add(work); // keep this thread going once it has started
}
if( work >= el - 3 ) {
// step along the diagonal in the forward direction, updating the match matrices and looking for a drop off from the maximum observed value
double maxElement = Double.NEGATIVE_INFINITY;
for( el = work; el < numDiags + 1; el++ ) {
updateCell(iii, jjj, haplotypeBases, readBases, readQuals,
insertionGOP, deletionGOP, overallGCP, matchMetricArray, XMetricArray, YMetricArray);
final double bestMetric = MathUtils.max(matchMetricArray[iii][jjj], XMetricArray[iii][jjj], YMetricArray[iii][jjj]);
calculatedValues.add(bestMetric);
if( bestMetric > maxElement ) {
maxElement = bestMetric;
} else if( maxElement - bestMetric > BANDING_TOLERANCE ) {
break;
}
if( ++iii >= X_METRIC_LENGTH ) { // don't walk off the edge of the matrix
break;
}
if( --jjj <= 0 ) { // don't walk off the edge of the matrix
break;
}
}
// find a local maximum to start a new band in the work queue
double localMaxElement = Double.NEGATIVE_INFINITY;
int localMaxElementIndex = 0;
for(int kkk = calculatedValues.size()-1; kkk >= 1; kkk--) {
final double bestMetric = calculatedValues.get(kkk);
if( bestMetric > localMaxElement ) {
localMaxElement = bestMetric;
localMaxElementIndex = kkk;
} else if( localMaxElement - bestMetric > BANDING_TOLERANCE * 0.5 ) { // find a local maximum
if( !detectClusteredStartLocations(workToBeAdded, work + localMaxElementIndex ) ) {
workToBeAdded.add( work + localMaxElementIndex );
}
break;
}
}
calculatedValues.clear();
// reset iii and jjj to the appropriate diagonal baseline location
iii = 0;
jjj = diag;
if( diag > Y_METRIC_LENGTH ) {
iii = diag - Y_METRIC_LENGTH;
jjj = Y_METRIC_LENGTH;
}
// move to the starting work location along the diagonal
iii += work-1;
jjj -= work-1;
// step along the diagonal in the reverse direction, updating the match matrices and looking for a drop off from the maximum observed value
for( int traceBack = work - 1; traceBack > 0 && iii > 0 && jjj < Y_METRIC_LENGTH; traceBack--,iii--,jjj++ ) {
updateCell(iii, jjj, haplotypeBases, readBases, readQuals,
insertionGOP, deletionGOP, overallGCP, matchMetricArray, XMetricArray, YMetricArray);
final double bestMetric = MathUtils.max(matchMetricArray[iii][jjj], XMetricArray[iii][jjj], YMetricArray[iii][jjj]);
if( bestMetric > maxElement ) {
maxElement = bestMetric;
} else if( maxElement - bestMetric > BANDING_TOLERANCE ) {
break;
}
}
}
}
workQueue.clear();
workQueue.addAll(workToBeAdded);
workToBeAdded.clear();
}
} else {
// 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);
}
// private function used by the banded approach to ensure the proposed bands are sufficiently distinct from each other
private boolean detectClusteredStartLocations( final ArrayList<Integer> list, int loc ) {
for(int x : list) {
if( Math.abs(x-loc) <= BANDING_CLUSTER_WINDOW ) {
return true;
}
}
return false;
}
}

1
public/java/src/org/broadinstitute/sting/utils/QualityUtils.java
View File

@ -9,6 +9,7 @@ import net.sf.samtools.SAMUtils;
* @author Kiran Garimella * @author Kiran Garimella
*/ */
public class QualityUtils { public class QualityUtils {
public final static byte MAX_RECALIBRATED_Q_SCORE = 50;
public final static byte MAX_QUAL_SCORE = SAMUtils.MAX_PHRED_SCORE; public final static byte MAX_QUAL_SCORE = SAMUtils.MAX_PHRED_SCORE;
public final static double ERROR_RATE_OF_MAX_QUAL_SCORE = qualToErrorProbRaw(MAX_QUAL_SCORE); public final static double ERROR_RATE_OF_MAX_QUAL_SCORE = qualToErrorProbRaw(MAX_QUAL_SCORE);

9
public/java/src/org/broadinstitute/sting/utils/recalibration/BaseRecalibration.java
View File

@ -68,9 +68,9 @@ public class BaseRecalibration {
/** /**
* This constructor only exists for testing purposes. * This constructor only exists for testing purposes.
* *
* @param quantizationInfo * @param quantizationInfo the quantization info object
* @param keysAndTablesMap * @param keysAndTablesMap the map of key managers and recalibration tables
* @param requestedCovariates * @param requestedCovariates the list of requested covariates
*/ */
protected BaseRecalibration(QuantizationInfo quantizationInfo, LinkedHashMap<BQSRKeyManager, Map<BitSet, RecalDatum>> keysAndTablesMap, ArrayList<Covariate> requestedCovariates) { protected BaseRecalibration(QuantizationInfo quantizationInfo, LinkedHashMap<BQSRKeyManager, Map<BitSet, RecalDatum>> keysAndTablesMap, ArrayList<Covariate> requestedCovariates) {
this.quantizationInfo = quantizationInfo; this.quantizationInfo = quantizationInfo;
@ -179,9 +179,8 @@ public class BaseRecalibration {
} }
double recalibratedQual = qualFromRead + globalDeltaQ + deltaQReported + deltaQCovariates; // calculate the recalibrated qual using the BQSR formula double recalibratedQual = qualFromRead + globalDeltaQ + deltaQReported + deltaQCovariates; // calculate the recalibrated qual using the BQSR formula
recalibratedQual = QualityUtils.boundQual((int) Math.round(recalibratedQual), QualityUtils.MAX_QUAL_SCORE); // recalibrated quality is bound between 1 and MAX_QUAL recalibratedQual = QualityUtils.boundQual((int) Math.round(recalibratedQual), QualityUtils.MAX_RECALIBRATED_Q_SCORE); // recalibrated quality is bound between 1 and MAX_QUAL
return quantizationInfo.getQuantizedQuals().get((int) recalibratedQual); // return the quantized version of the recalibrated quality return quantizationInfo.getQuantizedQuals().get((int) recalibratedQual); // return the quantized version of the recalibrated quality
} }

4
public/java/test/org/broadinstitute/sting/gatk/walkers/bqsr/ContextCovariateUnitTest.java
View File

@ -39,8 +39,8 @@ public class ContextCovariateUnitTest {
private void verifyCovariateArray(BitSet[] values, int contextSize, String bases) { private void verifyCovariateArray(BitSet[] values, int contextSize, String bases) {
for (int i = 0; i < values.length; i++) { for (int i = 0; i < values.length; i++) {
String expectedContext = null; String expectedContext = null;
if (i >= contextSize) { if (i - contextSize + 1 >= 0) {
String context = bases.substring(i - contextSize, i); String context = bases.substring(i - contextSize + 1, i + 1);
if (!context.contains("N")) if (!context.contains("N"))
expectedContext = context; expectedContext = context;
} }

36
public/java/test/org/broadinstitute/sting/gatk/walkers/genotyper/UnifiedGenotyperIntegrationTest.java
View File

@ -30,7 +30,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
public void testMultiSamplePilot1() { public void testMultiSamplePilot1() {
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
baseCommand + " -I " + validationDataLocation + "low_coverage_CEU.chr1.10k-11k.bam -o %s -L 1:10,022,000-10,025,000", 1, baseCommand + " -I " + validationDataLocation + "low_coverage_CEU.chr1.10k-11k.bam -o %s -L 1:10,022,000-10,025,000", 1,
Arrays.asList("d3191b2f10139c969501990ffdf29082")); Arrays.asList("9b08dc6800ba11bc6d9f6ccf392a60fe"));
executeTest("test MultiSample Pilot1", spec); executeTest("test MultiSample Pilot1", spec);
} }
@ -54,7 +54,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
public void testSingleSamplePilot2() { public void testSingleSamplePilot2() {
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
baseCommand + " -I " + validationDataLocation + "NA12878.1kg.p2.chr1_10mb_11_mb.SLX.bam -o %s -L 1:10,000,000-10,100,000", 1, baseCommand + " -I " + validationDataLocation + "NA12878.1kg.p2.chr1_10mb_11_mb.SLX.bam -o %s -L 1:10,000,000-10,100,000", 1,
Arrays.asList("7c7288170c6aadae555a44e79ca5bf19")); Arrays.asList("d275e0f75368dbff012ea8655dce3444"));
executeTest("test SingleSample Pilot2", spec); executeTest("test SingleSample Pilot2", spec);
} }
@ -62,7 +62,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
public void testMultipleSNPAlleles() { public void testMultipleSNPAlleles() {
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
"-T UnifiedGenotyper -R " + b37KGReference + " -nosl -NO_HEADER -glm BOTH --dbsnp " + b37dbSNP129 + " -I " + validationDataLocation + "multiallelic.snps.bam -o %s -L " + validationDataLocation + "multiallelic.snps.intervals", 1, "-T UnifiedGenotyper -R " + b37KGReference + " -nosl -NO_HEADER -glm BOTH --dbsnp " + b37dbSNP129 + " -I " + validationDataLocation + "multiallelic.snps.bam -o %s -L " + validationDataLocation + "multiallelic.snps.intervals", 1,
Arrays.asList("c956f0ea0e5f002288a09f4bc4af1319")); Arrays.asList("e948543b83bfd0640fcb994d72f8e234"));
executeTest("test Multiple SNP alleles", spec); executeTest("test Multiple SNP alleles", spec);
} }
@ -80,7 +80,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
// //
// -------------------------------------------------------------------------------------------------------------- // --------------------------------------------------------------------------------------------------------------
private final static String COMPRESSED_OUTPUT_MD5 = "2158eb918abb95225ea5372fcd9c9236"; private final static String COMPRESSED_OUTPUT_MD5 = "1e3c897794e5763a8720807686707b18";
@Test @Test
public void testCompressedOutput() { public void testCompressedOutput() {
@ -101,7 +101,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
// Note that we need to turn off any randomization for this to work, so no downsampling and no annotations // Note that we need to turn off any randomization for this to work, so no downsampling and no annotations
String md5 = "834e85f6af4ad4a143b913dfc7defb08"; String md5 = "06d11ed89f02f08911e100df0f7db7a4";
WalkerTest.WalkerTestSpec spec1 = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec1 = new WalkerTest.WalkerTestSpec(
baseCommand + " -dt NONE -G none -I " + validationDataLocation + "NA12878.1kg.p2.chr1_10mb_11_mb.SLX.bam -o %s -L 1:10,000,000-10,075,000", 1, baseCommand + " -dt NONE -G none -I " + validationDataLocation + "NA12878.1kg.p2.chr1_10mb_11_mb.SLX.bam -o %s -L 1:10,000,000-10,075,000", 1,
@ -200,8 +200,8 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
@Test @Test
public void testHeterozyosity() { public void testHeterozyosity() {
HashMap<Double, String> e = new HashMap<Double, String>(); HashMap<Double, String> e = new HashMap<Double, String>();
e.put( 0.01, "d5879f1c277035060434d79a441b31ca" ); e.put( 0.01, "d07e5ca757fbcb1c03f652f82265c2f8" );
e.put( 1.0 / 1850, "13f80245bab2321b92d27eebd5c2fc33" ); e.put( 1.0 / 1850, "d1fb9186e6f39f2bcf5d0edacd8f7fe2" );
for ( Map.Entry<Double, String> entry : e.entrySet() ) { for ( Map.Entry<Double, String> entry : e.entrySet() ) {
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
@ -225,7 +225,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
" -o %s" + " -o %s" +
" -L 1:10,000,000-10,100,000", " -L 1:10,000,000-10,100,000",
1, 1,
Arrays.asList("8c134a6e0abcc70d2ed3216d5f8e0100")); Arrays.asList("623be1fd8b63a01bfe35ac864d5199fe"));
executeTest(String.format("test multiple technologies"), spec); executeTest(String.format("test multiple technologies"), spec);
} }
@ -244,7 +244,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
" -L 1:10,000,000-10,100,000" + " -L 1:10,000,000-10,100,000" +
" -baq CALCULATE_AS_NECESSARY", " -baq CALCULATE_AS_NECESSARY",
1, 1,
Arrays.asList("34baad3177712f6cd0b476f4c578e08f")); Arrays.asList("40ea10c0238c3be2991d31ae72476884"));
executeTest(String.format("test calling with BAQ"), spec); executeTest(String.format("test calling with BAQ"), spec);
} }
@ -263,7 +263,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
" -o %s" + " -o %s" +
" -L 1:10,000,000-10,500,000", " -L 1:10,000,000-10,500,000",
1, 1,
Arrays.asList("4bf4f819a39a73707cae60fe30478742")); Arrays.asList("c9b0bd900a4ec949adfbd28909581eeb"));
executeTest(String.format("test indel caller in SLX"), spec); executeTest(String.format("test indel caller in SLX"), spec);
} }
@ -278,7 +278,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
" -minIndelCnt 1" + " -minIndelCnt 1" +
" -L 1:10,000,000-10,100,000", " -L 1:10,000,000-10,100,000",
1, 1,
Arrays.asList("ae08fbd6b0618cf3ac1be763ed7b41ca")); Arrays.asList("6b7c8691c527facf9884c2517d943f2f"));
executeTest(String.format("test indel caller in SLX with low min allele count"), spec); executeTest(String.format("test indel caller in SLX with low min allele count"), spec);
} }
@ -291,7 +291,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
" -o %s" + " -o %s" +
" -L 1:10,000,000-10,500,000", " -L 1:10,000,000-10,500,000",
1, 1,
Arrays.asList("120600f2bfa3a47bd93b50f768f98d5b")); Arrays.asList("d72603aa33a086d64d4dddfd2995552f"));
executeTest(String.format("test indel calling, multiple technologies"), spec); executeTest(String.format("test indel calling, multiple technologies"), spec);
} }
@ -301,7 +301,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
baseCommandIndels + " --genotyping_mode GENOTYPE_GIVEN_ALLELES -alleles " + validationDataLocation + "indelAllelesForUG.vcf -I " + validationDataLocation + baseCommandIndels + " --genotyping_mode GENOTYPE_GIVEN_ALLELES -alleles " + validationDataLocation + "indelAllelesForUG.vcf -I " + validationDataLocation +
"pilot2_daughters.chr20.10k-11k.bam -o %s -L 20:10,000,000-10,100,000", 1, "pilot2_daughters.chr20.10k-11k.bam -o %s -L 20:10,000,000-10,100,000", 1,
Arrays.asList("2e75d2766235eab23091a67ea2947d13")); Arrays.asList("4a59fe207949b7d043481d7c1b786573"));
executeTest("test MultiSample Pilot2 indels with alleles passed in", spec); executeTest("test MultiSample Pilot2 indels with alleles passed in", spec);
} }
@ -311,7 +311,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
baseCommandIndels + " --output_mode EMIT_ALL_SITES --genotyping_mode GENOTYPE_GIVEN_ALLELES -alleles " baseCommandIndels + " --output_mode EMIT_ALL_SITES --genotyping_mode GENOTYPE_GIVEN_ALLELES -alleles "
+ validationDataLocation + "indelAllelesForUG.vcf -I " + validationDataLocation + + validationDataLocation + "indelAllelesForUG.vcf -I " + validationDataLocation +
"pilot2_daughters.chr20.10k-11k.bam -o %s -L 20:10,000,000-10,100,000", 1, "pilot2_daughters.chr20.10k-11k.bam -o %s -L 20:10,000,000-10,100,000", 1,
Arrays.asList("5057bd7d07111e8b1085064782eb6c80")); Arrays.asList("a8a9ccf30bddee94bb1d300600794ee7"));
executeTest("test MultiSample Pilot2 indels with alleles passed in and emitting all sites", spec); executeTest("test MultiSample Pilot2 indels with alleles passed in and emitting all sites", spec);
} }
@ -319,13 +319,13 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
public void testMultiSampleIndels() { public void testMultiSampleIndels() {
WalkerTest.WalkerTestSpec spec1 = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec1 = new WalkerTest.WalkerTestSpec(
baseCommandIndels + " -I " + validationDataLocation + "low_coverage_CEU.chr1.10k-11k.bam -o %s -L 1:10450700-10551000", 1, baseCommandIndels + " -I " + validationDataLocation + "low_coverage_CEU.chr1.10k-11k.bam -o %s -L 1:10450700-10551000", 1,
Arrays.asList("c0f9ca3ceab90ebd38cc0eec9441d71f")); Arrays.asList("0b388936022539530f565da14d5496d3"));
List<File> result = executeTest("test MultiSample Pilot1 CEU indels", spec1).getFirst(); List<File> result = executeTest("test MultiSample Pilot1 CEU indels", spec1).getFirst();
WalkerTest.WalkerTestSpec spec2 = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec2 = new WalkerTest.WalkerTestSpec(
baseCommandIndels + " --genotyping_mode GENOTYPE_GIVEN_ALLELES -alleles " + result.get(0).getAbsolutePath() + " -I " + validationDataLocation + baseCommandIndels + " --genotyping_mode GENOTYPE_GIVEN_ALLELES -alleles " + result.get(0).getAbsolutePath() + " -I " + validationDataLocation +
"low_coverage_CEU.chr1.10k-11k.bam -o %s -L 1:10450700-10551000", 1, "low_coverage_CEU.chr1.10k-11k.bam -o %s -L 1:10450700-10551000", 1,
Arrays.asList("0240f34e71f137518be233c9890a5349")); Arrays.asList("537dd9b4174dc356fb13d8d3098ad602"));
executeTest("test MultiSample Pilot1 CEU indels using GENOTYPE_GIVEN_ALLELES", spec2); executeTest("test MultiSample Pilot1 CEU indels using GENOTYPE_GIVEN_ALLELES", spec2);
} }
@ -368,7 +368,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
public void testMinIndelFraction0() { public void testMinIndelFraction0() {
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
assessMinIndelFraction + " -minIndelFrac 0.0", 1, assessMinIndelFraction + " -minIndelFrac 0.0", 1,
Arrays.asList("53758e66e3a3188bd9c78d2329d41962")); Arrays.asList("973178b97efd2daacc9e45c414275d59"));
executeTest("test minIndelFraction 0.0", spec); executeTest("test minIndelFraction 0.0", spec);
} }
@ -376,7 +376,7 @@ public class UnifiedGenotyperIntegrationTest extends WalkerTest {
public void testMinIndelFraction25() { public void testMinIndelFraction25() {
WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec( WalkerTest.WalkerTestSpec spec = new WalkerTest.WalkerTestSpec(
assessMinIndelFraction + " -minIndelFrac 0.25", 1, assessMinIndelFraction + " -minIndelFrac 0.25", 1,
Arrays.asList("3aa39b1f6f3b1eb051765f9c21f6f461")); Arrays.asList("220facd2eb0923515d1d8ab874055564"));
executeTest("test minIndelFraction 0.25", spec); executeTest("test minIndelFraction 0.25", spec);
} }

77
public/java/test/org/broadinstitute/sting/gatk/walkers/varianteval/VariantEvalIntegrationTest.java
View File

@ -34,6 +34,8 @@ public class VariantEvalIntegrationTest extends WalkerTest {
private static String variantEvalTestDataRoot = validationDataLocation + "VariantEval"; private static String variantEvalTestDataRoot = validationDataLocation + "VariantEval";
private static String fundamentalTestVCF = variantEvalTestDataRoot + "/" + "FundamentalsTest.annotated.db.subset.snps_and_indels.vcf"; private static String fundamentalTestVCF = variantEvalTestDataRoot + "/" + "FundamentalsTest.annotated.db.subset.snps_and_indels.vcf";
private static String fundamentalTestSNPsVCF = variantEvalTestDataRoot + "/" + "FundamentalsTest.annotated.db.subset.final.vcf"; private static String fundamentalTestSNPsVCF = variantEvalTestDataRoot + "/" + "FundamentalsTest.annotated.db.subset.final.vcf";
private static String fundamentalTestSNPsSplit1of2VCF = variantEvalTestDataRoot + "/" + "FundamentalsTest.annotated.db.subset.final.split_1_of_2.vcf";
private static String fundamentalTestSNPsSplit2of2VCF = variantEvalTestDataRoot + "/" + "FundamentalsTest.annotated.db.subset.final.split_2_of_2.vcf";
private static String fundamentalTestSNPsOneSampleVCF = variantEvalTestDataRoot + "/" + "FundamentalsTest.annotated.db.subset.final.NA12045.vcf"; private static String fundamentalTestSNPsOneSampleVCF = variantEvalTestDataRoot + "/" + "FundamentalsTest.annotated.db.subset.final.NA12045.vcf";
private static String cmdRoot = "-T VariantEval" + private static String cmdRoot = "-T VariantEval" +
@ -437,24 +439,69 @@ public class VariantEvalIntegrationTest extends WalkerTest {
@Test @Test
public void testAlleleCountStrat() { public void testAlleleCountStrat() {
WalkerTestSpec spec = new WalkerTestSpec( WalkerTestSpec spec = new WalkerTestSpec(
buildCommandLine( buildCommandLine(
"-T VariantEval", "-T VariantEval",
"-R " + b37KGReference, "-R " + b37KGReference,
"--dbsnp " + b37dbSNP132, "--dbsnp " + b37dbSNP132,
"--eval " + fundamentalTestSNPsVCF, "--eval " + fundamentalTestSNPsVCF,
"-noEV", "-noEV",
"-EV CountVariants", "-EV CountVariants",
"-noST", "-noST",
"-ST AlleleCount", "-ST AlleleCount",
"-L " + fundamentalTestSNPsVCF, "-L " + fundamentalTestSNPsVCF,
"-o %s" "-o %s"
), ),
1, 1,
Arrays.asList("1198bfea6183bd43219071a84c79a386") Arrays.asList("1198bfea6183bd43219071a84c79a386")
); );
executeTest("testAlleleCountStrat", spec); executeTest("testAlleleCountStrat", spec);
} }
@Test
public void testMultipleEvalTracksAlleleCountWithMerge() {
WalkerTestSpec spec = new WalkerTestSpec(
buildCommandLine(
"-T VariantEval",
"-R " + b37KGReference,
"--dbsnp " + b37dbSNP132,
"--eval " + fundamentalTestSNPsSplit1of2VCF,
"--eval " + fundamentalTestSNPsSplit2of2VCF,
"--mergeEvals",
"-noEV",
"-EV CountVariants",
"-noST",
"-ST AlleleCount",
"-L " + fundamentalTestSNPsVCF,
"-o %s"
),
1,
Arrays.asList("1198bfea6183bd43219071a84c79a386")
);
executeTest("testMultipleEvalTracksAlleleCountWithMerge", spec);
}
@Test
public void testMultipleEvalTracksAlleleCountWithoutMerge() {
WalkerTestSpec spec = new WalkerTestSpec(
buildCommandLine(
"-T VariantEval",
"-R " + b37KGReference,
"--dbsnp " + b37dbSNP132,
"--eval " + fundamentalTestSNPsSplit1of2VCF,
"--eval " + fundamentalTestSNPsSplit2of2VCF,
//"--mergeEvals", No merge with AC strat ==> error
"-noEV",
"-EV CountVariants",
"-noST",
"-ST AlleleCount",
"-L " + fundamentalTestSNPsVCF
),
0,
UserException.class
);
executeTest("testMultipleEvalTracksAlleleCountWithoutMerge", spec);
}
@Test @Test
public void testIntervalStrat() { public void testIntervalStrat() {
WalkerTestSpec spec = new WalkerTestSpec( WalkerTestSpec spec = new WalkerTestSpec(

6
public/java/test/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrationWalkersIntegrationTest.java
View File

@ -73,9 +73,9 @@ public class VariantRecalibrationWalkersIntegrationTest extends WalkerTest {
} }
VRTest indel = new VRTest("combined.phase1.chr20.raw.indels.sites.vcf", VRTest indel = new VRTest("combined.phase1.chr20.raw.indels.sites.vcf",
"6d7ee4cb651c8b666e4a4523363caaff", // tranches "da4458d05f6396f5c4ab96f274e5ccdc", // tranches
"ee5b408c8434a594496118875690c438", // recal file "cf380d9b0ae04c8918be8425f82035b4", // recal file
"5d7e07d8813db96ba3f3dfe4737f83d1"); // cut VCF "b00e5e5a6807df8ed1682317948e8a6d"); // cut VCF
@DataProvider(name = "VRIndelTest") @DataProvider(name = "VRIndelTest")
public Object[][] createData2() { public Object[][] createData2() {

367
public/java/test/org/broadinstitute/sting/utils/PairHMMUnitTest.java 100644
View File

@ -0,0 +1,367 @@
/*
* Copyright (c) 2012, The Broad Institute
*
* Permission is hereby granted, free of charge, to any person
* obtaining a copy of this software and associated documentation
* files (the "Software"), to deal in the Software without
* restriction, including without limitation the rights to use,
* copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following
* conditions:
*
* The above copyright notice and this permission notice shall be
* included in all copies or substantial portions of the Software.
* 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.
*/
// our package
package org.broadinstitute.sting.utils;
// the imports for unit testing.
import org.broadinstitute.sting.BaseTest;
import org.testng.Assert;
import org.testng.annotations.DataProvider;
import org.testng.annotations.Test;
import java.util.*;
public class PairHMMUnitTest extends BaseTest {
final static boolean EXTENSIVE_TESTING = true;
PairHMM hmm = new PairHMM( false ); // reference implementation
PairHMM bandedHMM = new PairHMM( true ); // algorithm with banding
// --------------------------------------------------------------------------------
//
// Provider
//
// --------------------------------------------------------------------------------
private class BasicLikelihoodTestProvider extends TestDataProvider {
final String ref, read;
final byte[] refBasesWithContext, readBasesWithContext;
final int baseQual, insQual, delQual, gcp;
final int expectedQual;
final static String CONTEXT = "ACGTAATGACGATTGCA";
final static String LEFT_FLANK = "GATTTATCATCGAGTCTGC";
final static String RIGHT_FLANK = "CATGGATCGTTATCAGCTATCTCGAGGGATTCACTTAACAGTTTTA";
public BasicLikelihoodTestProvider(final String ref, final String read, final int baseQual, final int insQual, final int delQual, final int expectedQual, final int gcp) {
this(ref, read, baseQual, insQual, delQual, expectedQual, gcp, false, false);
}
public BasicLikelihoodTestProvider(final String ref, final String read, final int baseQual, final int insQual, final int delQual, final int expectedQual, final int gcp, final boolean left, final boolean right) {
super(BasicLikelihoodTestProvider.class, String.format("ref=%s read=%s b/i/d/c quals = %d/%d/%d/%d l/r flank = %b/%b e[qual]=%d", ref, read, baseQual, insQual, delQual, gcp, left, right, expectedQual));
this.baseQual = baseQual;
this.delQual = delQual;
this.insQual = insQual;
this.gcp = gcp;
this.read = read;
this.ref = ref;
this.expectedQual = expectedQual;
refBasesWithContext = asBytes(ref, left, right);
readBasesWithContext = asBytes(read, false, false);
}
public double expectedLogL() {
return expectedQual / -10.0;
}
public double tolerance() {
return 0.1; // TODO FIXME arbitrary
}
public double calcLogL() {
double logL = hmm.computeReadLikelihoodGivenHaplotype(
refBasesWithContext, readBasesWithContext,
qualAsBytes(baseQual, false), qualAsBytes(insQual, true), qualAsBytes(delQual, true),
qualAsBytes(gcp, false));
return logL;
}
private final byte[] asBytes(final String bases, final boolean left, final boolean right) {
return ( (left ? LEFT_FLANK : "") + CONTEXT + bases + CONTEXT + (right ? RIGHT_FLANK : "")).getBytes();
}
private byte[] qualAsBytes(final int phredQual, final boolean doGOP) {
final byte phredQuals[] = new byte[readBasesWithContext.length];
// initialize everything to MASSIVE_QUAL so it cannot be moved by HMM
Arrays.fill(phredQuals, (byte)100);
// update just the bases corresponding to the provided micro read with the quality scores
if( doGOP ) {
phredQuals[0 + CONTEXT.length()] = (byte)phredQual;
} else {
for ( int i = 0; i < read.length(); i++)
phredQuals[i + CONTEXT.length()] = (byte)phredQual;
}
return phredQuals;
}
}
final Random random = new Random(87865573);
private class BandedLikelihoodTestProvider extends TestDataProvider {
final String ref, read;
final byte[] refBasesWithContext, readBasesWithContext;
final int baseQual, insQual, delQual, gcp;
final int expectedQual;
final static String LEFT_CONTEXT = "ACGTAATGACGCTACATGTCGCCAACCGTC";
final static String RIGHT_CONTEXT = "TACGGCTTCATATAGGGCAATGTGTGTGGCAAAA";
final static String LEFT_FLANK = "GATTTATCATCGAGTCTGTT";
final static String RIGHT_FLANK = "CATGGATCGTTATCAGCTATCTCGAGGGATTCACTTAACAGTTTCCGTA";
final byte[] baseQuals, insQuals, delQuals, gcps;
public BandedLikelihoodTestProvider(final String ref, final String read, final int baseQual, final int insQual, final int delQual, final int expectedQual, final int gcp) {
this(ref, read, baseQual, insQual, delQual, expectedQual, gcp, false, false);
}
public BandedLikelihoodTestProvider(final String ref, final String read, final int baseQual, final int insQual, final int delQual, final int expectedQual, final int gcp, final boolean left, final boolean right) {
super(BandedLikelihoodTestProvider.class, String.format("BANDED: ref=%s read=%s b/i/d/c quals = %d/%d/%d/%d l/r flank = %b/%b e[qual]=%d", ref, read, baseQual, insQual, delQual, gcp, left, right, expectedQual));
this.baseQual = baseQual;
this.delQual = delQual;
this.insQual = insQual;
this.gcp = gcp;
this.read = read;
this.ref = ref;
this.expectedQual = expectedQual;
refBasesWithContext = asBytes(ref, left, right);
readBasesWithContext = asBytes(read, false, false);
baseQuals = qualAsBytes(baseQual);
insQuals = qualAsBytes(insQual);
delQuals = qualAsBytes(delQual);
gcps = qualAsBytes(gcp, false);
}
public double expectedLogL() {
double logL = hmm.computeReadLikelihoodGivenHaplotype(
refBasesWithContext, readBasesWithContext,
baseQuals, insQuals, delQuals, gcps);
return logL;
}
public double tolerance() {
return 0.2; // TODO FIXME arbitrary
}
public double calcLogL() {
double logL = bandedHMM.computeReadLikelihoodGivenHaplotype(
refBasesWithContext, readBasesWithContext,
baseQuals, insQuals, delQuals, gcps);
return logL;
}
private final byte[] asBytes(final String bases, final boolean left, final boolean right) {
return ( (left ? LEFT_FLANK : "") + LEFT_CONTEXT + bases + RIGHT_CONTEXT + (right ? RIGHT_FLANK : "")).getBytes();
}
private byte[] qualAsBytes(final int phredQual) {
return qualAsBytes(phredQual, true);
}
private byte[] qualAsBytes(final int phredQual, final boolean addRandom) {
final byte phredQuals[] = new byte[readBasesWithContext.length];
Arrays.fill(phredQuals, (byte)phredQual);
if(addRandom) {
for( int iii = 0; iii < phredQuals.length; iii++) {
phredQuals[iii] = (byte) ((int) phredQuals[iii] + (random.nextInt(7) - 3));
}
}
return phredQuals;
}
}
@DataProvider(name = "BasicLikelihoodTestProvider")
public Object[][] makeBasicLikelihoodTests() {
// context on either side is ACGTTGCA REF ACGTTGCA
// test all combinations
final List<Integer> baseQuals = EXTENSIVE_TESTING ? Arrays.asList(10, 20, 30, 40, 50) : Arrays.asList(30);
final List<Integer> indelQuals = EXTENSIVE_TESTING ? Arrays.asList(20, 30, 40, 50) : Arrays.asList(40);
final List<Integer> gcps = EXTENSIVE_TESTING ? Arrays.asList(10, 20, 30) : Arrays.asList(10);
final List<Integer> sizes = EXTENSIVE_TESTING ? Arrays.asList(2,3,4,5,7,8,9,10,20) : Arrays.asList(2);
for ( final int baseQual : baseQuals ) {
for ( final int indelQual : indelQuals ) {
for ( final int gcp : gcps ) {
// test substitutions
for ( final byte refBase : BaseUtils.BASES ) {
for ( final byte readBase : BaseUtils.BASES ) {
final String ref = new String(new byte[]{refBase});
final String read = new String(new byte[]{readBase});
final int expected = refBase == readBase ? 0 : baseQual;
new BasicLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp);
}
}
// test insertions and deletions
for ( final int size : sizes ) {
for ( final byte base : BaseUtils.BASES ) {
final int expected = indelQual + (size - 2) * gcp;
for ( boolean insertionP : Arrays.asList(true, false)) {
final String small = Utils.dupString((char)base, 1);
final String big = Utils.dupString((char)base, size);
final String ref = insertionP ? small : big;
final String read = insertionP ? big : small;
new BasicLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp);
new BasicLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp, true, false);
new BasicLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp, false, true);
new BasicLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp, true, true);
}
}
}
}
}
}
return BasicLikelihoodTestProvider.getTests(BasicLikelihoodTestProvider.class);
}
@Test(dataProvider = "BasicLikelihoodTestProvider", enabled = true)
public void testBasicLikelihoods(BasicLikelihoodTestProvider cfg) {
double calculatedLogL = cfg.calcLogL();
double expectedLogL = cfg.expectedLogL();
logger.warn(String.format("Test: logL calc=%.2f expected=%.2f for %s", calculatedLogL, expectedLogL, cfg.toString()));
Assert.assertEquals(calculatedLogL, expectedLogL, cfg.tolerance());
}
@DataProvider(name = "BandedLikelihoodTestProvider")
public Object[][] makeBandedLikelihoodTests() {
// context on either side is ACGTTGCA REF ACGTTGCA
// test all combinations
final List<Integer> baseQuals = EXTENSIVE_TESTING ? Arrays.asList(25, 30, 40, 50) : Arrays.asList(30);
final List<Integer> indelQuals = EXTENSIVE_TESTING ? Arrays.asList(30, 40, 50) : Arrays.asList(40);
final List<Integer> gcps = EXTENSIVE_TESTING ? Arrays.asList(10, 12) : Arrays.asList(10);
final List<Integer> sizes = EXTENSIVE_TESTING ? Arrays.asList(2,3,4,5,7,8,9,10,20) : Arrays.asList(2);
for ( final int baseQual : baseQuals ) {
for ( final int indelQual : indelQuals ) {
for ( final int gcp : gcps ) {
// test substitutions
for ( final byte refBase : BaseUtils.BASES ) {
for ( final byte readBase : BaseUtils.BASES ) {
final String ref = new String(new byte[]{refBase});
final String read = new String(new byte[]{readBase});
final int expected = refBase == readBase ? 0 : baseQual;
new BandedLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp);
}
}
// test insertions and deletions
for ( final int size : sizes ) {
for ( final byte base : BaseUtils.BASES ) {
final int expected = indelQual + (size - 2) * gcp;
for ( boolean insertionP : Arrays.asList(true, false)) {
final String small = Utils.dupString((char)base, 1);
final String big = Utils.dupString((char)base, size);
final String ref = insertionP ? small : big;
final String read = insertionP ? big : small;
new BandedLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp);
new BandedLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp, true, false);
new BandedLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp, false, true);
new BandedLikelihoodTestProvider(ref, read, baseQual, indelQual, indelQual, expected, gcp, true, true);
}
}
}
}
}
}
return BandedLikelihoodTestProvider.getTests(BandedLikelihoodTestProvider.class);
}
@Test(dataProvider = "BandedLikelihoodTestProvider", enabled = true)
public void testBandedLikelihoods(BandedLikelihoodTestProvider cfg) {
double calculatedLogL = cfg.calcLogL();
double expectedLogL = cfg.expectedLogL();
logger.warn(String.format("Test: logL calc=%.2f expected=%.2f for %s", calculatedLogL, expectedLogL, cfg.toString()));
Assert.assertEquals(calculatedLogL, expectedLogL, cfg.tolerance());
}
@Test
public void testMismatchInEveryPositionInTheReadWithCenteredHaplotype() {
byte[] haplotype1 = "TTCTCTTCTGTTGTGGCTGGTT".getBytes();
final int offset = 2;
byte[] gop = new byte[haplotype1.length - 2 * offset];
Arrays.fill(gop, (byte) 80);
byte[] gcp = new byte[haplotype1.length - 2 * offset];
Arrays.fill(gcp, (byte) 80);
for( int k = 0; k < haplotype1.length - 2 * offset; k++ ) {
byte[] quals = new byte[haplotype1.length - 2 * offset];
Arrays.fill(quals, (byte) 90);
// one read mismatches the haplotype
quals[k] = 20;
byte[] mread = Arrays.copyOfRange(haplotype1,offset,haplotype1.length-offset);
// change single base at position k to C. If it's a C, change to T
mread[k] = ( mread[k] == (byte)'C' ? (byte)'T' : (byte)'C');
double res1 = hmm.computeReadLikelihoodGivenHaplotype(
haplotype1, mread,
quals, gop, gop,
gcp);
System.out.format("H:%s\nR: %s\n Pos:%d Result:%4.2f\n",new String(haplotype1), new String(mread), k,res1);
Assert.assertEquals(res1, -2.0, 1e-2);
}
}
@Test
public void testMismatchInEveryPositionInTheRead() {
byte[] haplotype1 = "TTCTCTTCTGTTGTGGCTGGTT".getBytes();
final int offset = 2;
byte[] gop = new byte[haplotype1.length - offset];
Arrays.fill(gop, (byte) 80);
byte[] gcp = new byte[haplotype1.length - offset];
Arrays.fill(gcp, (byte) 80);
for( int k = 0; k < haplotype1.length - offset; k++ ) {
byte[] quals = new byte[haplotype1.length - offset];
Arrays.fill(quals, (byte) 90);
// one read mismatches the haplotype
quals[k] = 20;
byte[] mread = Arrays.copyOfRange(haplotype1,offset,haplotype1.length);
// change single base at position k to C. If it's a C, change to T
mread[k] = ( mread[k] == (byte)'C' ? (byte)'T' : (byte)'C');
double res1 = hmm.computeReadLikelihoodGivenHaplotype(
haplotype1, mread,
quals, gop, gop,
gcp);
System.out.format("H:%s\nR: %s\n Pos:%d Result:%4.2f\n",new String(haplotype1), new String(mread), k,res1);
Assert.assertEquals(res1, -2.0, 1e-2);
}
}
}

24
public/java/test/org/broadinstitute/sting/utils/recalibration/BaseRecalibrationUnitTest.java
View File

@ -24,10 +24,6 @@ public class BaseRecalibrationUnitTest {
private org.broadinstitute.sting.gatk.walkers.recalibration.RecalDataManager dataManager; private org.broadinstitute.sting.gatk.walkers.recalibration.RecalDataManager dataManager;
private LinkedHashMap<BQSRKeyManager, Map<BitSet, RecalDatum>> keysAndTablesMap; private LinkedHashMap<BQSRKeyManager, Map<BitSet, RecalDatum>> keysAndTablesMap;
private BQSRKeyManager rgKeyManager;
private BQSRKeyManager qsKeyManager;
private BQSRKeyManager cvKeyManager;
private ReadGroupCovariate rgCovariate; private ReadGroupCovariate rgCovariate;
private QualityScoreCovariate qsCovariate; private QualityScoreCovariate qsCovariate;
private ContextCovariate cxCovariate; private ContextCovariate cxCovariate;
@ -60,13 +56,13 @@ public class BaseRecalibrationUnitTest {
rgCovariate = new ReadGroupCovariate(); rgCovariate = new ReadGroupCovariate();
rgCovariate.initialize(RAC); rgCovariate.initialize(RAC);
requiredCovariates.add(rgCovariate); requiredCovariates.add(rgCovariate);
rgKeyManager = new BQSRKeyManager(requiredCovariates, optionalCovariates); BQSRKeyManager rgKeyManager = new BQSRKeyManager(requiredCovariates, optionalCovariates);
keysAndTablesMap.put(rgKeyManager, new HashMap<BitSet, RecalDatum>()); keysAndTablesMap.put(rgKeyManager, new HashMap<BitSet, RecalDatum>());
qsCovariate = new QualityScoreCovariate(); qsCovariate = new QualityScoreCovariate();
qsCovariate.initialize(RAC); qsCovariate.initialize(RAC);
requiredCovariates.add(qsCovariate); requiredCovariates.add(qsCovariate);
qsKeyManager = new BQSRKeyManager(requiredCovariates, optionalCovariates); BQSRKeyManager qsKeyManager = new BQSRKeyManager(requiredCovariates, optionalCovariates);
keysAndTablesMap.put(qsKeyManager, new HashMap<BitSet, RecalDatum>()); keysAndTablesMap.put(qsKeyManager, new HashMap<BitSet, RecalDatum>());
cxCovariate = new ContextCovariate(); cxCovariate = new ContextCovariate();
@ -75,7 +71,7 @@ public class BaseRecalibrationUnitTest {
cyCovariate = new CycleCovariate(); cyCovariate = new CycleCovariate();
cyCovariate.initialize(RAC); cyCovariate.initialize(RAC);
optionalCovariates.add(cyCovariate); optionalCovariates.add(cyCovariate);
cvKeyManager = new BQSRKeyManager(requiredCovariates, optionalCovariates); BQSRKeyManager cvKeyManager = new BQSRKeyManager(requiredCovariates, optionalCovariates);
keysAndTablesMap.put(cvKeyManager, new HashMap<BitSet, RecalDatum>()); keysAndTablesMap.put(cvKeyManager, new HashMap<BitSet, RecalDatum>());
@ -108,7 +104,7 @@ public class BaseRecalibrationUnitTest {
updateCovariateWithKeySet(mapEntry.getValue(), key, newDatum); updateCovariateWithKeySet(mapEntry.getValue(), key, newDatum);
} }
} }
dataManager.generateEmpiricalQualities(1, QualityUtils.MAX_QUAL_SCORE); dataManager.generateEmpiricalQualities(1, QualityUtils.MAX_RECALIBRATED_Q_SCORE);
List<Byte> quantizedQuals = new ArrayList<Byte>(); List<Byte> quantizedQuals = new ArrayList<Byte>();
List<Long> qualCounts = new ArrayList<Long>(); List<Long> qualCounts = new ArrayList<Long>();
@ -179,7 +175,7 @@ public class BaseRecalibrationUnitTest {
BitSet key = entry.getKey(); BitSet key = entry.getKey();
RecalDatum datum = entry.getValue(); RecalDatum datum = entry.getValue();
List<Object> keySet = keyManager.keySetFrom(key); List<Object> keySet = keyManager.keySetFrom(key);
System.out.println(String.format("%s => %s", Utils.join(",", keySet), datum)); System.out.println(String.format("%s => %s", Utils.join(",", keySet), datum) + "," + datum.getEstimatedQReported());
} }
System.out.println(); System.out.println();
} }
@ -187,9 +183,9 @@ public class BaseRecalibrationUnitTest {
} }
private static void printNestedHashMap(Map<Object,Object> table, String output) { private static void printNestedHashMap(Map table, String output) {
for (Object key : table.keySet()) { for (Object key : table.keySet()) {
String ret = ""; String ret;
if (output.isEmpty()) if (output.isEmpty())
ret = "" + key; ret = "" + key;
else else
@ -199,7 +195,7 @@ public class BaseRecalibrationUnitTest {
if (next instanceof org.broadinstitute.sting.gatk.walkers.recalibration.RecalDatum) if (next instanceof org.broadinstitute.sting.gatk.walkers.recalibration.RecalDatum)
System.out.println(ret + " => " + next); System.out.println(ret + " => " + next);
else else
printNestedHashMap((Map<Object, Object>) next, "" + ret); printNestedHashMap((Map) next, "" + ret);
} }
} }
@ -269,7 +265,7 @@ public class BaseRecalibrationUnitTest {
} }
final double newQuality = qualFromRead + globalDeltaQ + deltaQReported + deltaQCovariates; final double newQuality = qualFromRead + globalDeltaQ + deltaQReported + deltaQCovariates;
return QualityUtils.boundQual((int) Math.round(newQuality), QualityUtils.MAX_QUAL_SCORE); return QualityUtils.boundQual((int) Math.round(newQuality), QualityUtils.MAX_RECALIBRATED_Q_SCORE);
// Verbose printouts used to validate with old recalibrator // Verbose printouts used to validate with old recalibrator
//if(key.contains(null)) { //if(key.contains(null)) {
@ -289,6 +285,6 @@ public class BaseRecalibrationUnitTest {
final double doubleMismatches = (double) (errors + smoothing); final double doubleMismatches = (double) (errors + smoothing);
final double doubleObservations = (double) ( observations + smoothing ); final double doubleObservations = (double) ( observations + smoothing );
double empiricalQual = -10 * Math.log10(doubleMismatches / doubleObservations); double empiricalQual = -10 * Math.log10(doubleMismatches / doubleObservations);
return Math.min(QualityUtils.MAX_QUAL_SCORE, empiricalQual); return Math.min(QualityUtils.MAX_RECALIBRATED_Q_SCORE, empiricalQual);
} }
} }