@Test
public void substractComplexExample() {
GenomeLoc e = genomeLocParser.createGenomeLoc(contigOneName, 1, 20);
mSortedSet.add(e);
GenomeLoc r1 = genomeLocParser.createGenomeLoc(contigOneName, 3, 5);
GenomeLoc r2 = genomeLocParser.createGenomeLoc(contigOneName, 10, 12);
GenomeLoc r3 = genomeLocParser.createGenomeLoc(contigOneName, 16, 18);
GenomeLocSortedSet toExclude =
new GenomeLocSortedSet(genomeLocParser, Arrays.asList(r1, r2, r3));
GenomeLocSortedSet remaining = mSortedSet.subtractRegions(toExclude);
// logger.debug("Initial " + mSortedSet);
// logger.debug("Exclude " + toExclude);
// logger.debug("Remaining " + remaining);
assertEquals(mSortedSet.coveredSize(), 20);
assertEquals(toExclude.coveredSize(), 9);
assertEquals(remaining.coveredSize(), 11);
Iterator<GenomeLoc> it = remaining.iterator();
GenomeLoc p1 = it.next();
GenomeLoc p2 = it.next();
GenomeLoc p3 = it.next();
GenomeLoc p4 = it.next();
assertEquals(genomeLocParser.createGenomeLoc(contigOneName, 1, 2), p1);
assertEquals(genomeLocParser.createGenomeLoc(contigOneName, 6, 9), p2);
assertEquals(genomeLocParser.createGenomeLoc(contigOneName, 13, 15), p3);
assertEquals(genomeLocParser.createGenomeLoc(contigOneName, 19, 20), p4);
}
@Test
public void testSizeBeforeLoc() {
GenomeLoc r1 = genomeLocParser.createGenomeLoc(contigOneName, 3, 5);
GenomeLoc r2 = genomeLocParser.createGenomeLoc(contigOneName, 10, 12);
GenomeLoc r3 = genomeLocParser.createGenomeLoc(contigOneName, 16, 18);
mSortedSet.addAll(Arrays.asList(r1, r2, r3));
testSizeBeforeLocX(2, 0);
testSizeBeforeLocX(3, 0);
testSizeBeforeLocX(4, 1);
testSizeBeforeLocX(5, 2);
testSizeBeforeLocX(6, 3);
testSizeBeforeLocX(10, 3);
testSizeBeforeLocX(11, 4);
testSizeBeforeLocX(12, 5);
testSizeBeforeLocX(13, 6);
testSizeBeforeLocX(15, 6);
testSizeBeforeLocX(16, 6);
testSizeBeforeLocX(17, 7);
testSizeBeforeLocX(18, 8);
testSizeBeforeLocX(19, 9);
testSizeBeforeLocX(50, 9);
testSizeBeforeLocX(50, (int) mSortedSet.coveredSize());
}
@Test(expectedExceptions = IllegalArgumentException.class)
public void addThrowsException() {
assertTrue(mSortedSet.size() == 0);
GenomeLoc g = genomeLocParser.createGenomeLoc(contigOneName, 1, 50);
mSortedSet.add(g);
GenomeLoc f = genomeLocParser.createGenomeLoc(contigOneName, 30, 80);
mSortedSet.add(f);
}
/**
* create a list of genomic locations, given a reference sequence
*
* @param dict the sequence dictionary to create a collection from
* @return the GenomeLocSet of all references sequences as GenomeLoc's
*/
public static GenomeLocSortedSet createSetFromSequenceDictionary(SAMSequenceDictionary dict) {
GenomeLocParser parser = new GenomeLocParser(dict);
GenomeLocSortedSet returnSortedSet = new GenomeLocSortedSet(parser);
for (SAMSequenceRecord record : dict.getSequences()) {
returnSortedSet.add(
parser.createGenomeLoc(record.getSequenceName(), 1, record.getSequenceLength()));
}
return returnSortedSet;
}
@Test
public void addRegion() {
assertTrue(mSortedSet.size() == 0);
GenomeLoc g = genomeLocParser.createGenomeLoc(contigOneName, 1, 50);
mSortedSet.add(g);
GenomeLoc f = genomeLocParser.createGenomeLoc(contigOneName, 30, 80);
mSortedSet.addRegion(f);
assertTrue(mSortedSet.size() == 1);
}
@Test
public void deleteAllByRegion() {
GenomeLoc e = genomeLocParser.createGenomeLoc(contigOneName, 1, 100);
mSortedSet.add(e);
for (int x = 1; x < 101; x++) {
GenomeLoc del = genomeLocParser.createGenomeLoc(contigOneName, x, x);
mSortedSet = mSortedSet.subtractRegions(new GenomeLocSortedSet(genomeLocParser, del));
}
assertTrue(mSortedSet.isEmpty());
}
@Test
public void addRegionsOutOfOrder() {
final String contigTwoName = header.getSequenceDictionary().getSequence(2).getSequenceName();
assertTrue(mSortedSet.size() == 0);
GenomeLoc g = genomeLocParser.createGenomeLoc(contigTwoName, 1, 50);
mSortedSet.add(g);
GenomeLoc f = genomeLocParser.createGenomeLoc(contigOneName, 30, 80);
mSortedSet.addRegion(f);
assertTrue(mSortedSet.size() == 2);
assertTrue(mSortedSet.toList().get(0).getContig().equals(contigOneName));
assertTrue(mSortedSet.toList().get(1).getContig().equals(contigTwoName));
}
@Test
public void deleteSomeByRegion() {
GenomeLoc e = genomeLocParser.createGenomeLoc(contigOneName, 1, 100);
mSortedSet.add(e);
for (int x = 1; x < 50; x++) {
GenomeLoc del = genomeLocParser.createGenomeLoc(contigOneName, x, x);
mSortedSet = mSortedSet.subtractRegions(new GenomeLocSortedSet(genomeLocParser, del));
}
assertTrue(!mSortedSet.isEmpty());
assertTrue(mSortedSet.size() == 1);
GenomeLoc loc = mSortedSet.iterator().next();
assertTrue(loc.getStop() == 100);
assertTrue(loc.getStart() == 50);
}
@Test
public void mergingOverlappingAbove() {
GenomeLoc e = genomeLocParser.createGenomeLoc(contigOneName, 0, 50);
GenomeLoc g = genomeLocParser.createGenomeLoc(contigOneName, 49, 100);
assertTrue(mSortedSet.size() == 0);
mSortedSet.add(g);
assertTrue(mSortedSet.size() == 1);
mSortedSet.addRegion(e);
assertTrue(mSortedSet.size() == 1);
Iterator<GenomeLoc> iter = mSortedSet.iterator();
GenomeLoc loc = iter.next();
assertEquals(loc.getStart(), 0);
assertEquals(loc.getStop(), 100);
assertEquals(loc.getContigIndex(), 1);
}
@Test
public void testAdd() {
GenomeLoc g = genomeLocParser.createGenomeLoc(contigOneName, 0, 0);
assertTrue(mSortedSet.size() == 0);
mSortedSet.add(g);
assertTrue(mSortedSet.size() == 1);
}
@Test(expectedExceptions = IllegalArgumentException.class)
public void testAddDuplicate() {
assertTrue(mSortedSet.size() == 0);
GenomeLoc g = genomeLocParser.createGenomeLoc(contigOneName, 0, 0);
mSortedSet.add(g);
assertTrue(mSortedSet.size() == 1);
mSortedSet.add(g);
}
/**
* return a deep copy of this collection.
*
* @return a new GenomeLocSortedSet, identical to the current GenomeLocSortedSet.
*/
public GenomeLocSortedSet clone() {
GenomeLocSortedSet ret = new GenomeLocSortedSet(genomeLocParser);
for (GenomeLoc loc : this.mArray) {
// ensure a deep copy
ret.mArray.add(
genomeLocParser.createGenomeLoc(loc.getContig(), loc.getStart(), loc.getStop()));
}
return ret;
}
@Test
public void deleteSuperRegion() {
GenomeLoc e = genomeLocParser.createGenomeLoc(contigOneName, 10, 20);
GenomeLoc g = genomeLocParser.createGenomeLoc(contigOneName, 70, 100);
mSortedSet.add(g);
mSortedSet.addRegion(e);
assertTrue(mSortedSet.size() == 2);
// now delete a region
GenomeLoc d = genomeLocParser.createGenomeLoc(contigOneName, 15, 75);
mSortedSet = mSortedSet.subtractRegions(new GenomeLocSortedSet(genomeLocParser, d));
Iterator<GenomeLoc> iter = mSortedSet.iterator();
GenomeLoc loc = iter.next();
assertTrue(loc.getStart() == 10);
assertTrue(loc.getStop() == 14);
assertTrue(loc.getContigIndex() == 1);
loc = iter.next();
assertTrue(loc.getStart() == 76);
assertTrue(loc.getStop() == 100);
assertTrue(loc.getContigIndex() == 1);
}
@DataProvider(name = "GetOverlapping")
public Object[][] makeGetOverlappingTest() throws Exception {
final GenomeLocParser genomeLocParser =
new GenomeLocParser(new CachingIndexedFastaSequenceFile(new File(b37KGReference)));
List<Object[]> tests = new ArrayList<Object[]>();
final GenomeLoc prev1 = genomeLocParser.createGenomeLoc("19", 1, 10);
final GenomeLoc prev2 = genomeLocParser.createGenomeLoc("19", 20, 50);
final GenomeLoc post1 = genomeLocParser.createGenomeLoc("21", 1, 10);
final GenomeLoc post2 = genomeLocParser.createGenomeLoc("21", 20, 50);
final int chr20Length = genomeLocParser.getContigs().getSequence("20").getSequenceLength();
for (final int regionStart : Arrays.asList(1, 10, chr20Length - 10, chr20Length)) {
for (final int regionSize : Arrays.asList(1, 10, 100)) {
final GenomeLoc region =
genomeLocParser.createGenomeLocOnContig("20", regionStart, regionStart + regionSize);
final GenomeLoc spanning =
genomeLocParser.createGenomeLocOnContig("20", regionStart - 10, region.getStop() + 10);
final GenomeLoc before_into =
genomeLocParser.createGenomeLocOnContig("20", regionStart - 10, regionStart + 1);
final GenomeLoc middle =
genomeLocParser.createGenomeLocOnContig("20", regionStart + 1, regionStart + 2);
final GenomeLoc middle_past =
genomeLocParser.createGenomeLocOnContig(
"20", region.getStop() - 1, region.getStop() + 10);
final List<GenomeLoc> potentials = new LinkedList<GenomeLoc>();
potentials.add(region);
if (spanning != null) potentials.add(spanning);
if (before_into != null) potentials.add(before_into);
if (middle != null) potentials.add(middle);
if (middle_past != null) potentials.add(middle_past);
for (final int n : Arrays.asList(1, 2, 3)) {
for (final List<GenomeLoc> regions : Utils.makePermutations(potentials, n, false)) {
tests.add(new Object[] {new GenomeLocSortedSet(genomeLocParser, regions), region});
tests.add(
new Object[] {
new GenomeLocSortedSet(genomeLocParser, Utils.append(regions, prev1)), region
});
tests.add(
new Object[] {
new GenomeLocSortedSet(genomeLocParser, Utils.append(regions, prev1, prev2)),
region
});
tests.add(
new Object[] {
new GenomeLocSortedSet(genomeLocParser, Utils.append(regions, post1)), region
});
tests.add(
new Object[] {
new GenomeLocSortedSet(genomeLocParser, Utils.append(regions, post1, post2)),
region
});
tests.add(
new Object[] {
new GenomeLocSortedSet(genomeLocParser, Utils.append(regions, prev1, post1)),
region
});
tests.add(
new Object[] {
new GenomeLocSortedSet(
genomeLocParser, Utils.append(regions, prev1, prev2, post1, post2)),
region
});
}
}
}
}
return tests.toArray(new Object[][] {});
}
private void testSizeBeforeLocX(int pos, int size) {
GenomeLoc test = genomeLocParser.createGenomeLoc(contigOneName, pos, pos);
assertEquals(
mSortedSet.sizeBeforeLoc(test), size, String.format("X pos=%d size=%d", pos, size));
}
@Test
public void overlap() {
for (int i = 1; i < 6; i++) {
final int start = i * 10;
mSortedSet.add(genomeLocParser.createGenomeLoc(contigOneName, start, start + 1));
}
// test matches in and around interval
assertFalse(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 9, 9)));
assertTrue(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 10, 10)));
assertTrue(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 11, 11)));
assertFalse(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 12, 12)));
// test matches spanning intervals
assertTrue(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 14, 20)));
assertTrue(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 11, 15)));
assertTrue(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 30, 40)));
assertTrue(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 51, 53)));
// test miss
assertFalse(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 12, 19)));
// test exact match after miss
assertTrue(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 40, 41)));
// test matches at beginning of intervals
assertFalse(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 5, 6)));
assertTrue(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 0, 10)));
// test matches at end of intervals
assertFalse(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 52, 53)));
assertTrue(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 51, 53)));
assertFalse(mSortedSet.overlaps(genomeLocParser.createGenomeLoc(contigOneName, 52, 53)));
}
/**
* Read in a list of ExactCall objects from reader, keeping only those with starts in startsToKeep
* or all sites (if this is empty)
*
* @param reader a just-opened reader sitting at the start of the file
* @param startsToKeep a list of start position of the calls to keep, or empty if all calls should
* be kept
* @param parser a genome loc parser to create genome locs
* @return a list of ExactCall objects in reader
* @throws IOException
*/
public static List<ExactCall> readExactLog(
final BufferedReader reader, final List<Integer> startsToKeep, GenomeLocParser parser)
throws IOException {
if (reader == null) throw new IllegalArgumentException("reader cannot be null");
if (startsToKeep == null) throw new IllegalArgumentException("startsToKeep cannot be null");
if (parser == null) throw new IllegalArgumentException("GenomeLocParser cannot be null");
List<ExactCall> calls = new LinkedList<ExactCall>();
// skip the header line
reader.readLine();
// skip the first "type" line
reader.readLine();
while (true) {
final VariantContextBuilder builder = new VariantContextBuilder();
final List<Allele> alleles = new ArrayList<Allele>();
final List<Genotype> genotypes = new ArrayList<Genotype>();
final double[] posteriors = new double[2];
final double[] priors = MathUtils.normalizeFromLog10(new double[] {0.5, 0.5}, true);
final List<Integer> mle = new ArrayList<Integer>();
final Map<Allele, Double> log10pNonRefByAllele = new HashMap<Allele, Double>();
long runtimeNano = -1;
GenomeLoc currentLoc = null;
while (true) {
final String line = reader.readLine();
if (line == null) return calls;
final String[] parts = line.split("\t");
final GenomeLoc lineLoc = parser.parseGenomeLoc(parts[0]);
final String variable = parts[1];
final String key = parts[2];
final String value = parts[3];
if (currentLoc == null) currentLoc = lineLoc;
if (variable.equals("type")) {
if (startsToKeep.isEmpty() || startsToKeep.contains(currentLoc.getStart())) {
builder.alleles(alleles);
final int stop = currentLoc.getStart() + alleles.get(0).length() - 1;
builder.chr(currentLoc.getContig()).start(currentLoc.getStart()).stop(stop);
builder.genotypes(genotypes);
final int[] mleInts = ArrayUtils.toPrimitive(mle.toArray(new Integer[] {}));
final AFCalcResult result =
new AFCalcResult(mleInts, 1, alleles, posteriors, priors, log10pNonRefByAllele);
calls.add(new ExactCall(builder.make(), runtimeNano, result));
}
break;
} else if (variable.equals("allele")) {
final boolean isRef = key.equals("0");
alleles.add(Allele.create(value, isRef));
} else if (variable.equals("PL")) {
final GenotypeBuilder gb = new GenotypeBuilder(key);
gb.PL(GenotypeLikelihoods.fromPLField(value).getAsPLs());
genotypes.add(gb.make());
} else if (variable.equals("log10PosteriorOfAFEq0")) {
posteriors[0] = Double.valueOf(value);
} else if (variable.equals("log10PosteriorOfAFGt0")) {
posteriors[1] = Double.valueOf(value);
} else if (variable.equals("MLE")) {
mle.add(Integer.valueOf(value));
} else if (variable.equals("pNonRefByAllele")) {
final Allele a = Allele.create(key);
log10pNonRefByAllele.put(a, Double.valueOf(value));
} else if (variable.equals("runtime.nano")) {
runtimeNano = Long.valueOf(value);
} else {
// nothing to do
}
}
}
}
/**
* Main entry function to calculate genotypes of a given VC with corresponding GL's
*
* @param tracker Tracker
* @param refContext Reference context
* @param rawContext Raw context
* @param stratifiedContexts Stratified alignment contexts
* @param vc Input VC
* @param model GL calculation model
* @param inheritAttributesFromInputVC Output VC will contain attributes inherited from input vc
* @return VC with assigned genotypes
*/
public VariantCallContext calculateGenotypes(
final RefMetaDataTracker tracker,
final ReferenceContext refContext,
final AlignmentContext rawContext,
Map<String, AlignmentContext> stratifiedContexts,
final VariantContext vc,
final GenotypeLikelihoodsCalculationModel.Model model,
final boolean inheritAttributesFromInputVC,
final Map<String, org.broadinstitute.sting.utils.genotyper.PerReadAlleleLikelihoodMap>
perReadAlleleLikelihoodMap) {
boolean limitedContext =
tracker == null || refContext == null || rawContext == null || stratifiedContexts == null;
// initialize the data for this thread if that hasn't been done yet
if (afcm.get() == null) {
afcm.set(AFCalcFactory.createAFCalc(UAC, N, logger));
}
// estimate our confidence in a reference call and return
if (vc.getNSamples() == 0) {
if (limitedContext) return null;
return (UAC.OutputMode != OUTPUT_MODE.EMIT_ALL_SITES
? estimateReferenceConfidence(vc, stratifiedContexts, getTheta(model), false, 1.0)
: generateEmptyContext(tracker, refContext, stratifiedContexts, rawContext));
}
AFCalcResult AFresult = afcm.get().getLog10PNonRef(vc, getAlleleFrequencyPriors(model));
// is the most likely frequency conformation AC=0 for all alternate alleles?
boolean bestGuessIsRef = true;
// determine which alternate alleles have AF>0
final List<Allele> myAlleles = new ArrayList<Allele>(vc.getAlleles().size());
final List<Integer> alleleCountsofMLE = new ArrayList<Integer>(vc.getAlleles().size());
myAlleles.add(vc.getReference());
for (int i = 0; i < AFresult.getAllelesUsedInGenotyping().size(); i++) {
final Allele alternateAllele = AFresult.getAllelesUsedInGenotyping().get(i);
if (alternateAllele.isReference()) continue;
// we are non-ref if the probability of being non-ref > the emit confidence.
// the emit confidence is phred-scaled, say 30 => 10^-3.
// the posterior AF > 0 is log10: -5 => 10^-5
// we are non-ref if 10^-5 < 10^-3 => -5 < -3
final boolean isNonRef =
AFresult.isPolymorphic(alternateAllele, UAC.STANDARD_CONFIDENCE_FOR_EMITTING / -10.0);
// if the most likely AC is not 0, then this is a good alternate allele to use
if (isNonRef) {
myAlleles.add(alternateAllele);
alleleCountsofMLE.add(AFresult.getAlleleCountAtMLE(alternateAllele));
bestGuessIsRef = false;
}
// if in GENOTYPE_GIVEN_ALLELES mode, we still want to allow the use of a poor allele
else if (UAC.GenotypingMode
== GenotypeLikelihoodsCalculationModel.GENOTYPING_MODE.GENOTYPE_GIVEN_ALLELES) {
myAlleles.add(alternateAllele);
alleleCountsofMLE.add(AFresult.getAlleleCountAtMLE(alternateAllele));
}
}
final double PoFGT0 = Math.pow(10, AFresult.getLog10PosteriorOfAFGT0());
// note the math.abs is necessary because -10 * 0.0 => -0.0 which isn't nice
final double phredScaledConfidence =
Math.abs(
!bestGuessIsRef
|| UAC.GenotypingMode
== GenotypeLikelihoodsCalculationModel.GENOTYPING_MODE
.GENOTYPE_GIVEN_ALLELES
? -10 * AFresult.getLog10PosteriorOfAFEq0()
: -10 * AFresult.getLog10PosteriorOfAFGT0());
// return a null call if we don't pass the confidence cutoff or the most likely allele frequency
// is zero
if (UAC.OutputMode != OUTPUT_MODE.EMIT_ALL_SITES
&& !passesEmitThreshold(phredScaledConfidence, bestGuessIsRef)) {
// technically, at this point our confidence in a reference call isn't accurately estimated
// because it didn't take into account samples with no data, so let's get a better estimate
return limitedContext
? null
: estimateReferenceConfidence(vc, stratifiedContexts, getTheta(model), true, PoFGT0);
}
// start constructing the resulting VC
final GenomeLoc loc = genomeLocParser.createGenomeLoc(vc);
final VariantContextBuilder builder =
new VariantContextBuilder(
"UG_call", loc.getContig(), loc.getStart(), loc.getStop(), myAlleles);
builder.log10PError(phredScaledConfidence / -10.0);
if (!passesCallThreshold(phredScaledConfidence)) builder.filters(filter);
// create the genotypes
final GenotypesContext genotypes = afcm.get().subsetAlleles(vc, myAlleles, true, ploidy);
builder.genotypes(genotypes);
// print out stats if we have a writer
if (verboseWriter != null && !limitedContext)
printVerboseData(refContext.getLocus().toString(), vc, PoFGT0, phredScaledConfidence, model);
// *** note that calculating strand bias involves overwriting data structures, so we do that
// last
final HashMap<String, Object> attributes = new HashMap<String, Object>();
// inherit attributed from input vc if requested
if (inheritAttributesFromInputVC) attributes.putAll(vc.getAttributes());
// if the site was downsampled, record that fact
if (!limitedContext && rawContext.hasPileupBeenDownsampled())
attributes.put(VCFConstants.DOWNSAMPLED_KEY, true);
if (UAC.ANNOTATE_NUMBER_OF_ALLELES_DISCOVERED)
attributes.put(NUMBER_OF_DISCOVERED_ALLELES_KEY, vc.getAlternateAlleles().size());
// add the MLE AC and AF annotations
if (alleleCountsofMLE.size() > 0) {
attributes.put(VCFConstants.MLE_ALLELE_COUNT_KEY, alleleCountsofMLE);
final int AN = builder.make().getCalledChrCount();
final ArrayList<Double> MLEfrequencies = new ArrayList<Double>(alleleCountsofMLE.size());
// the MLEAC is allowed to be larger than the AN (e.g. in the case of all PLs being 0, the GT
// is ./. but the exact model may arbitrarily choose an AC>1)
for (int AC : alleleCountsofMLE) MLEfrequencies.add(Math.min(1.0, (double) AC / (double) AN));
attributes.put(VCFConstants.MLE_ALLELE_FREQUENCY_KEY, MLEfrequencies);
}
if (UAC.COMPUTE_SLOD && !limitedContext && !bestGuessIsRef) {
// final boolean DEBUG_SLOD = false;
// the overall lod
// double overallLog10PofNull = AFresult.log10AlleleFrequencyPosteriors[0];
double overallLog10PofF = AFresult.getLog10LikelihoodOfAFGT0();
// if ( DEBUG_SLOD ) System.out.println("overallLog10PofF=" + overallLog10PofF);
List<Allele> allAllelesToUse = builder.make().getAlleles();
// the forward lod
VariantContext vcForward =
calculateLikelihoods(
tracker,
refContext,
stratifiedContexts,
AlignmentContextUtils.ReadOrientation.FORWARD,
allAllelesToUse,
false,
model,
perReadAlleleLikelihoodMap);
AFresult = afcm.get().getLog10PNonRef(vcForward, getAlleleFrequencyPriors(model));
// double[] normalizedLog10Posteriors =
// MathUtils.normalizeFromLog10(AFresult.log10AlleleFrequencyPosteriors, true);
double forwardLog10PofNull = AFresult.getLog10LikelihoodOfAFEq0();
double forwardLog10PofF = AFresult.getLog10LikelihoodOfAFGT0();
// if ( DEBUG_SLOD ) System.out.println("forwardLog10PofNull=" + forwardLog10PofNull + ",
// forwardLog10PofF=" + forwardLog10PofF);
// the reverse lod
VariantContext vcReverse =
calculateLikelihoods(
tracker,
refContext,
stratifiedContexts,
AlignmentContextUtils.ReadOrientation.REVERSE,
allAllelesToUse,
false,
model,
perReadAlleleLikelihoodMap);
AFresult = afcm.get().getLog10PNonRef(vcReverse, getAlleleFrequencyPriors(model));
// normalizedLog10Posteriors =
// MathUtils.normalizeFromLog10(AFresult.log10AlleleFrequencyPosteriors, true);
double reverseLog10PofNull = AFresult.getLog10LikelihoodOfAFEq0();
double reverseLog10PofF = AFresult.getLog10LikelihoodOfAFGT0();
// if ( DEBUG_SLOD ) System.out.println("reverseLog10PofNull=" + reverseLog10PofNull + ",
// reverseLog10PofF=" + reverseLog10PofF);
double forwardLod = forwardLog10PofF + reverseLog10PofNull - overallLog10PofF;
double reverseLod = reverseLog10PofF + forwardLog10PofNull - overallLog10PofF;
// if ( DEBUG_SLOD ) System.out.println("forward lod=" + forwardLod + ", reverse lod=" +
// reverseLod);
// strand score is max bias between forward and reverse strands
double strandScore = Math.max(forwardLod, reverseLod);
// rescale by a factor of 10
strandScore *= 10.0;
// logger.debug(String.format("SLOD=%f", strandScore));
if (!Double.isNaN(strandScore)) attributes.put("SB", strandScore);
}
// finish constructing the resulting VC
builder.attributes(attributes);
VariantContext vcCall = builder.make();
// if we are subsetting alleles (either because there were too many or because some were not
// polymorphic)
// then we may need to trim the alleles (because the original VariantContext may have had to pad
// at the end).
if (myAlleles.size() != vc.getAlleles().size()
&& !limitedContext) // limitedContext callers need to handle allele trimming on their own to
// keep their perReadAlleleLikelihoodMap alleles in sync
vcCall = VariantContextUtils.reverseTrimAlleles(vcCall);
if (annotationEngine != null
&& !limitedContext) { // limitedContext callers need to handle annotations on their own by
// calling their own annotationEngine
// Note: we want to use the *unfiltered* and *unBAQed* context for the annotations
final ReadBackedPileup pileup = rawContext.getBasePileup();
stratifiedContexts = AlignmentContextUtils.splitContextBySampleName(pileup);
vcCall =
annotationEngine.annotateContext(
tracker, refContext, stratifiedContexts, vcCall, perReadAlleleLikelihoodMap);
}
return new VariantCallContext(vcCall, confidentlyCalled(phredScaledConfidence, PoFGT0));
}