/**
* Checks if vc has a variant call for (at least one of) the samples.
*
* @param vc the variant rod VariantContext. Here, the variant is the dataset you're looking for
* discordances to (e.g. HapMap)
* @param compVCs the comparison VariantContext (discordance
* @return
*/
private boolean isDiscordant(VariantContext vc, Collection<VariantContext> compVCs) {
if (vc == null) return false;
// if we're not looking at specific samples then the absence of a compVC means discordance
if (NO_SAMPLES_SPECIFIED) return (compVCs == null || compVCs.isEmpty());
// check if we find it in the variant rod
Map<String, Genotype> genotypes = vc.getGenotypes(samples);
for (Genotype g : genotypes.values()) {
if (sampleHasVariant(g)) {
// There is a variant called (or filtered with not exclude filtered option set) that is not
// HomRef for at least one of the samples.
if (compVCs == null) return true;
// Look for this sample in the all vcs of the comp ROD track.
boolean foundVariant = false;
for (VariantContext compVC : compVCs) {
if (sampleHasVariant(compVC.getGenotype(g.getSampleName()))) {
foundVariant = true;
break;
}
}
// if (at least one sample) was not found in all VCs of the comp ROD, we have discordance
if (!foundVariant) return true;
}
}
return false; // we only get here if all samples have a variant in the comp rod.
}
protected final void printCallInfo(
final VariantContext vc,
final double[] log10AlleleFrequencyPriors,
final long runtimeNano,
final AFCalcResult result) {
printCallElement(vc, "type", "ignore", vc.getType());
int allelei = 0;
for (final Allele a : vc.getAlleles())
printCallElement(vc, "allele", allelei++, a.getDisplayString());
for (final Genotype g : vc.getGenotypes())
printCallElement(vc, "PL", g.getSampleName(), g.getLikelihoodsString());
for (int priorI = 0; priorI < log10AlleleFrequencyPriors.length; priorI++)
printCallElement(vc, "priorI", priorI, log10AlleleFrequencyPriors[priorI]);
printCallElement(vc, "runtime.nano", "ignore", runtimeNano);
printCallElement(vc, "log10PosteriorOfAFEq0", "ignore", result.getLog10PosteriorOfAFEq0());
printCallElement(vc, "log10PosteriorOfAFGt0", "ignore", result.getLog10PosteriorOfAFGT0());
for (final Allele allele : result.getAllelesUsedInGenotyping()) {
if (allele.isNonReference()) {
printCallElement(vc, "MLE", allele, result.getAlleleCountAtMLE(allele));
printCallElement(
vc, "pNonRefByAllele", allele, result.getLog10PosteriorOfAFGt0ForAllele(allele));
}
}
callReport.flush();
}
public PhaseAndQuality(Genotype gt) {
this.isPhased = gt.isPhased();
if (this.isPhased) {
this.PQ = gt.getAttributeAsDouble(ReadBackedPhasingWalker.PQ_KEY, -1);
if (this.PQ == -1) this.PQ = null;
}
}
static boolean allGenotypesAreUnfilteredAndCalled(VariantContext vc) {
for (final Genotype gt : vc.getGenotypes()) {
if (gt.isNoCall() || gt.isFiltered()) return false;
}
return true;
}
public Map<String, Object> annotate(
RefMetaDataTracker tracker,
AnnotatorCompatible walker,
ReferenceContext ref,
Map<String, AlignmentContext> stratifiedContexts,
VariantContext vc) {
if (stratifiedContexts.size()
== 0) // size 0 means that call was made by someone else and we have no data here
return null;
if (!vc.isSNP() && !vc.isIndel() && !vc.isMixed()) return null;
final AlignmentContext context =
AlignmentContextUtils.joinContexts(stratifiedContexts.values());
final int contextWingSize = Math.min((ref.getWindow().size() - 1) / 2, MIN_CONTEXT_WING_SIZE);
final int contextSize = contextWingSize * 2 + 1;
final int locus =
ref.getLocus().getStart() + (ref.getLocus().getStop() - ref.getLocus().getStart()) / 2;
final ReadBackedPileup pileup = context.getBasePileup();
// Compute all haplotypes consistent with the current read pileup
final List<Haplotype> haplotypes = computeHaplotypes(pileup, contextSize, locus, vc);
final MathUtils.RunningAverage scoreRA = new MathUtils.RunningAverage();
if (haplotypes != null) {
for (final Genotype genotype : vc.getGenotypes()) {
final AlignmentContext thisContext = stratifiedContexts.get(genotype.getSampleName());
if (thisContext != null) {
final ReadBackedPileup thisPileup = thisContext.getBasePileup();
if (vc.isSNP())
scoreRA.add(
scoreReadsAgainstHaplotypes(
haplotypes,
thisPileup,
contextSize,
locus)); // Taking the simple average of all sample's score since the score can
// be negative and the RMS doesn't make sense
else if (vc.isIndel() || vc.isMixed()) {
Double d = scoreIndelsAgainstHaplotypes(thisPileup);
if (d == null) return null;
scoreRA.add(
d); // Taking the simple average of all sample's score since the score can be
// negative and the RMS doesn't make sense
}
}
}
}
// annotate the score in the info field
final Map<String, Object> map = new HashMap<String, Object>();
map.put(getKeyNames().get(0), String.format("%.4f", scoreRA.mean()));
return map;
}
static boolean alleleSegregationIsKnown(Genotype gt1, Genotype gt2) {
if (gt1.getPloidy() != gt2.getPloidy()) return false;
/* If gt2 is phased or hom, then could even be MERGED with gt1 [This is standard].
HOWEVER, EVEN if this is not the case, but gt1.isHom(),
it is trivially known that each of gt2's alleles segregate with the single allele type present in gt1.
*/
return (gt2.isPhased() || gt2.isHom() || gt1.isHom());
}
static boolean allSamplesAreMergeable(VariantContext vc1, VariantContext vc2) {
// Check that each sample's genotype in vc2 is uniquely appendable onto its genotype in vc1:
for (final Genotype gt1 : vc1.getGenotypes()) {
Genotype gt2 = vc2.getGenotype(gt1.getSampleName());
if (!alleleSegregationIsKnown(gt1, gt2)) // can merge if: phased, or if either is a hom
return false;
}
return true;
}
private Map<String, Object> calculateIC(final VariantContext vc) {
final GenotypesContext genotypes =
(founderIds == null || founderIds.isEmpty())
? vc.getGenotypes()
: vc.getGenotypes(founderIds);
if (genotypes == null || genotypes.size() < MIN_SAMPLES) return null;
int idxAA = 0, idxAB = 1, idxBB = 2;
if (!vc.isBiallelic()) {
// for non-bliallelic case, do test with most common alt allele.
// Get then corresponding indeces in GL vectors to retrieve GL of AA,AB and BB.
int[] idxVector = vc.getGLIndecesOfAlternateAllele(vc.getAltAlleleWithHighestAlleleCount());
idxAA = idxVector[0];
idxAB = idxVector[1];
idxBB = idxVector[2];
}
double refCount = 0.0;
double hetCount = 0.0;
double homCount = 0.0;
int N = 0; // number of samples that have likelihoods
for (final Genotype g : genotypes) {
if (g.isNoCall() || !g.hasLikelihoods()) continue;
if (g.getPloidy() != 2) // only work for diploid samples
continue;
N++;
final double[] normalizedLikelihoods =
MathUtils.normalizeFromLog10(g.getLikelihoods().getAsVector());
refCount += normalizedLikelihoods[idxAA];
hetCount += normalizedLikelihoods[idxAB];
homCount += normalizedLikelihoods[idxBB];
}
if (N < MIN_SAMPLES) {
return null;
}
final double p =
(2.0 * refCount + hetCount)
/ (2.0 * (refCount + hetCount + homCount)); // expected reference allele frequency
final double q = 1.0 - p; // expected alternative allele frequency
final double F = 1.0 - (hetCount / (2.0 * p * q * (double) N)); // inbreeding coefficient
Map<String, Object> map = new HashMap<String, Object>();
map.put(getKeyNames().get(0), String.format("%.4f", F));
return map;
}
/**
* Helper method to subset a VC record, modifying some metadata stored in the INFO field (i.e. AN,
* AC, AF).
*
* @param vc the VariantContext record to subset
* @param samples the samples to extract
* @return the subsetted VariantContext
*/
private VariantContext subsetRecord(VariantContext vc, Set<String> samples) {
if (samples == null || samples.isEmpty()) return vc;
ArrayList<Genotype> genotypes = new ArrayList<Genotype>();
for (Map.Entry<String, Genotype> genotypePair : vc.getGenotypes().entrySet()) {
if (samples.contains(genotypePair.getKey())) genotypes.add(genotypePair.getValue());
}
VariantContext sub = vc.subContextFromGenotypes(genotypes, vc.getAlleles());
// if we have fewer alternate alleles in the selected VC than in the original VC, we need to
// strip out the GL/PLs (because they are no longer accurate)
if (vc.getAlleles().size() != sub.getAlleles().size())
sub = VariantContext.modifyGenotypes(sub, VariantContextUtils.stripPLs(vc.getGenotypes()));
HashMap<String, Object> attributes = new HashMap<String, Object>(sub.getAttributes());
int depth = 0;
for (String sample : sub.getSampleNames()) {
Genotype g = sub.getGenotype(sample);
if (g.isNotFiltered() && g.isCalled()) {
String dp = (String) g.getAttribute("DP");
if (dp != null
&& !dp.equals(VCFConstants.MISSING_DEPTH_v3)
&& !dp.equals(VCFConstants.MISSING_VALUE_v4)) {
depth += Integer.valueOf(dp);
}
}
}
if (KEEP_ORIGINAL_CHR_COUNTS) {
if (attributes.containsKey(VCFConstants.ALLELE_COUNT_KEY))
attributes.put("AC_Orig", attributes.get(VCFConstants.ALLELE_COUNT_KEY));
if (attributes.containsKey(VCFConstants.ALLELE_FREQUENCY_KEY))
attributes.put("AF_Orig", attributes.get(VCFConstants.ALLELE_FREQUENCY_KEY));
if (attributes.containsKey(VCFConstants.ALLELE_NUMBER_KEY))
attributes.put("AN_Orig", attributes.get(VCFConstants.ALLELE_NUMBER_KEY));
}
VariantContextUtils.calculateChromosomeCounts(sub, attributes, false);
attributes.put("DP", depth);
sub = VariantContext.modifyAttributes(sub, attributes);
return sub;
}
private boolean haveSameGenotypes(Genotype g1, Genotype g2) {
if ((g1.isCalled() && g2.isFiltered())
|| (g2.isCalled() && g1.isFiltered())
|| (g1.isFiltered() && g2.isFiltered() && EXCLUDE_FILTERED)) return false;
List<Allele> a1s = g1.getAlleles();
List<Allele> a2s = g2.getAlleles();
return (a1s.containsAll(a2s) && a2s.containsAll(a1s));
}
static boolean someSampleHasDoubleNonReferenceAllele(VariantContext vc1, VariantContext vc2) {
for (final Genotype gt1 : vc1.getGenotypes()) {
Genotype gt2 = vc2.getGenotype(gt1.getSampleName());
List<Allele> site1Alleles = gt1.getAlleles();
List<Allele> site2Alleles = gt2.getAlleles();
Iterator<Allele> all2It = site2Alleles.iterator();
for (Allele all1 : site1Alleles) {
Allele all2 = all2It.next(); // this is OK, since allSamplesAreMergeable()
if (all1.isNonReference() && all2.isNonReference()) // corresponding alleles are alternate
return true;
}
}
return false;
}
static PhaseAndQuality calcPhaseForMergedGenotypes(Genotype gt1, Genotype gt2) {
if (gt2.isPhased() || gt2.isHom()) return new PhaseAndQuality(gt1); // maintain the phase of gt1
if (!gt1.isHom())
throw new ReviewedStingException(
"alleleSegregationIsKnown(gt1, gt2) implies: gt2.genotypesArePhased() || gt2.isHom() || gt1.isHom()");
/* We're dealing with: gt1.isHom(), gt2.isHet(), !gt2.genotypesArePhased(); so, the merged (het) Genotype is not phased relative to the previous Genotype
For example, if we're merging the third Genotype with the second one:
0/1
1|1
0/1
Then, we want to output:
0/1
1/2
*/
return new PhaseAndQuality(gt2); // maintain the phase of gt2 [since !gt2.genotypesArePhased()]
}
private static List<String> calcVCFGenotypeKeys(VariantContext vc) {
Set<String> keys = new HashSet<String>();
boolean sawGoodGT = false;
boolean sawGoodQual = false;
boolean sawGenotypeFilter = false;
for (Genotype g : vc.getGenotypes().values()) {
keys.addAll(g.getAttributes().keySet());
if (g.isAvailable()) sawGoodGT = true;
if (g.hasNegLog10PError()) sawGoodQual = true;
if (g.isFiltered() && g.isCalled()) sawGenotypeFilter = true;
}
if (sawGoodQual) keys.add(VCFConstants.GENOTYPE_QUALITY_KEY);
if (sawGenotypeFilter) keys.add(VCFConstants.GENOTYPE_FILTER_KEY);
List<String> sortedList = ParsingUtils.sortList(new ArrayList<String>(keys));
// make sure the GT is first
if (sawGoodGT) {
List<String> newList = new ArrayList<String>(sortedList.size() + 1);
newList.add(VCFConstants.GENOTYPE_KEY);
newList.addAll(sortedList);
sortedList = newList;
}
return sortedList;
}
public Map<String, Object> annotate(
RefMetaDataTracker tracker,
AnnotatorCompatibleWalker walker,
ReferenceContext ref,
AlignmentContext stratifiedContext,
VariantContext vc,
Genotype g) {
if (g == null || !g.isCalled()) return null;
if (vc.isSNP()) return annotateSNP(stratifiedContext, vc);
if (vc.isIndel()) return annotateIndel(stratifiedContext, vc);
return null;
}
static boolean doubleAllelesSegregatePerfectlyAmongSamples(
VariantContext vc1, VariantContext vc2) {
// Check that Alleles at vc1 and at vc2 always segregate together in all samples (including
// reference):
Map<Allele, Allele> allele1ToAllele2 = new HashMap<Allele, Allele>();
Map<Allele, Allele> allele2ToAllele1 = new HashMap<Allele, Allele>();
// Note the segregation of the alleles for the reference genome:
allele1ToAllele2.put(vc1.getReference(), vc2.getReference());
allele2ToAllele1.put(vc2.getReference(), vc1.getReference());
// Note the segregation of the alleles for each sample (and check that it is consistent with the
// reference and all previous samples).
for (final Genotype gt1 : vc1.getGenotypes()) {
Genotype gt2 = vc2.getGenotype(gt1.getSampleName());
List<Allele> site1Alleles = gt1.getAlleles();
List<Allele> site2Alleles = gt2.getAlleles();
Iterator<Allele> all2It = site2Alleles.iterator();
for (Allele all1 : site1Alleles) {
Allele all2 = all2It.next();
Allele all1To2 = allele1ToAllele2.get(all1);
if (all1To2 == null) allele1ToAllele2.put(all1, all2);
else if (!all1To2.equals(all2)) // all1 segregates with two different alleles at site 2
return false;
Allele all2To1 = allele2ToAllele1.get(all2);
if (all2To1 == null) allele2ToAllele1.put(all2, all1);
else if (!all2To1.equals(all1)) // all2 segregates with two different alleles at site 1
return false;
}
}
return true;
}
public void update2(
VariantContext eval,
VariantContext comp,
RefMetaDataTracker tracker,
ReferenceContext ref,
AlignmentContext context) {
if (eval == null || (getWalker().ignoreAC0Sites() && eval.isMonomorphicInSamples())) return;
final Type type = getType(eval);
if (type == null) return;
TypeSampleMap titvTable = null;
// update DP, if possible
if (eval.hasAttribute(VCFConstants.DEPTH_KEY)) depthPerSample.inc(type, ALL);
// update counts
allVariantCounts.inc(type, ALL);
// type specific calculations
if (type == Type.SNP && eval.isBiallelic()) {
titvTable =
VariantContextUtils.isTransition(eval) ? transitionsPerSample : transversionsPerSample;
titvTable.inc(type, ALL);
}
// novelty calculation
if (comp != null || (type == Type.CNV && overlapsKnownCNV(eval)))
knownVariantCounts.inc(type, ALL);
// per sample metrics
for (final Genotype g : eval.getGenotypes()) {
if (!g.isNoCall() && !g.isHomRef()) {
countsPerSample.inc(type, g.getSampleName());
// update transition / transversion ratio
if (titvTable != null) titvTable.inc(type, g.getSampleName());
if (g.hasDP()) depthPerSample.inc(type, g.getSampleName());
}
}
}
public String update1(
VariantContext vc1,
RefMetaDataTracker tracker,
ReferenceContext ref,
AlignmentContext context) {
nCalledLoci++;
// Note from Eric:
// This is really not correct. What we really want here is a polymorphic vs. monomorphic count
// (i.e. on the Genotypes).
// So in order to maintain consistency with the previous implementation (and the intention of
// the original author), I've
// added in a proxy check for monomorphic status here.
// Protect against case when vc only as no-calls too - can happen if we strafity by sample and
// sample as a single no-call.
if (vc1.isMonomorphicInSamples()) {
nRefLoci++;
} else {
switch (vc1.getType()) {
case NO_VARIATION:
// shouldn't get here
break;
case SNP:
nVariantLoci++;
nSNPs++;
if (vc1.getAttributeAsBoolean("ISSINGLETON", false)) nSingletons++;
break;
case MNP:
nVariantLoci++;
nMNPs++;
if (vc1.getAttributeAsBoolean("ISSINGLETON", false)) nSingletons++;
break;
case INDEL:
nVariantLoci++;
if (vc1.isSimpleInsertion()) nInsertions++;
else if (vc1.isSimpleDeletion()) nDeletions++;
else nComplex++;
break;
case MIXED:
nVariantLoci++;
nMixed++;
break;
case SYMBOLIC:
nSymbolic++;
break;
default:
throw new ReviewedStingException("Unexpected VariantContext type " + vc1.getType());
}
}
String refStr = vc1.getReference().getBaseString().toUpperCase();
String aaStr =
vc1.hasAttribute("ANCESTRALALLELE")
? vc1.getAttributeAsString("ANCESTRALALLELE", null).toUpperCase()
: null;
// if (aaStr.equals(".")) {
// aaStr = refStr;
// }
// ref aa alt class
// A C A der homozygote
// A C C anc homozygote
// A A A ref homozygote
// A A C
// A C A
// A C C
for (final Genotype g : vc1.getGenotypes()) {
final String altStr =
vc1.getAlternateAlleles().size() > 0
? vc1.getAlternateAllele(0).getBaseString().toUpperCase()
: null;
switch (g.getType()) {
case NO_CALL:
nNoCalls++;
break;
case HOM_REF:
nHomRef++;
if (aaStr != null && altStr != null && !refStr.equalsIgnoreCase(aaStr)) {
nHomDerived++;
}
break;
case HET:
nHets++;
break;
case HOM_VAR:
nHomVar++;
if (aaStr != null && altStr != null && !altStr.equalsIgnoreCase(aaStr)) {
nHomDerived++;
}
break;
case MIXED:
break;
default:
throw new ReviewedStingException("BUG: Unexpected genotype type: " + g);
}
}
return null; // we don't capture any interesting sites
}
public void writeBeagleOutput(
VariantContext preferredVC, VariantContext otherVC, boolean isValidationSite, double prior) {
GenomeLoc currentLoc =
VariantContextUtils.getLocation(getToolkit().getGenomeLocParser(), preferredVC);
StringBuffer beagleOut = new StringBuffer();
String marker = String.format("%s:%d ", currentLoc.getContig(), currentLoc.getStart());
beagleOut.append(marker);
if (markers != null)
markers.append(marker).append("\t").append(Integer.toString(markerCounter++)).append("\t");
for (Allele allele : preferredVC.getAlleles()) {
String bglPrintString;
if (allele.isNoCall() || allele.isNull()) bglPrintString = "-";
else bglPrintString = allele.getBaseString(); // get rid of * in case of reference allele
beagleOut.append(String.format("%s ", bglPrintString));
if (markers != null) markers.append(bglPrintString).append("\t");
}
if (markers != null) markers.append("\n");
GenotypesContext preferredGenotypes = preferredVC.getGenotypes();
GenotypesContext otherGenotypes = goodSite(otherVC) ? otherVC.getGenotypes() : null;
for (String sample : samples) {
boolean isMaleOnChrX = CHECK_IS_MALE_ON_CHR_X && getSample(sample).getGender() == Gender.MALE;
Genotype genotype;
boolean isValidation;
// use sample as key into genotypes structure
if (preferredGenotypes.containsSample(sample)) {
genotype = preferredGenotypes.get(sample);
isValidation = isValidationSite;
} else if (otherGenotypes != null && otherGenotypes.containsSample(sample)) {
genotype = otherGenotypes.get(sample);
isValidation = !isValidationSite;
} else {
// there is magically no genotype for this sample.
throw new StingException(
"Sample "
+ sample
+ " arose with no genotype in variant or validation VCF. This should never happen.");
}
/*
* Use likelihoods if: is validation, prior is negative; or: is not validation, has genotype key
*/
double[] log10Likelihoods = null;
if ((isValidation && prior < 0.0) || genotype.hasLikelihoods()) {
log10Likelihoods = genotype.getLikelihoods().getAsVector();
// see if we need to randomly mask out genotype in this position.
if (GenomeAnalysisEngine.getRandomGenerator().nextDouble() <= insertedNoCallRate) {
// we are masking out this genotype
log10Likelihoods =
isMaleOnChrX ? HAPLOID_FLAT_LOG10_LIKELIHOODS : DIPLOID_FLAT_LOG10_LIKELIHOODS;
}
if (isMaleOnChrX) {
log10Likelihoods[1] = -255; // todo -- warning this is dangerous for multi-allele case
}
}
/** otherwise, use the prior uniformly */
else if (!isValidation && genotype.isCalled() && !genotype.hasLikelihoods()) {
// hack to deal with input VCFs with no genotype likelihoods. Just assume the called
// genotype
// is confident. This is useful for Hapmap and 1KG release VCFs.
double AA = (1.0 - prior) / 2.0;
double AB = (1.0 - prior) / 2.0;
double BB = (1.0 - prior) / 2.0;
if (genotype.isHomRef()) {
AA = prior;
} else if (genotype.isHet()) {
AB = prior;
} else if (genotype.isHomVar()) {
BB = prior;
}
log10Likelihoods = MathUtils.toLog10(new double[] {AA, isMaleOnChrX ? 0.0 : AB, BB});
} else {
log10Likelihoods =
isMaleOnChrX ? HAPLOID_FLAT_LOG10_LIKELIHOODS : DIPLOID_FLAT_LOG10_LIKELIHOODS;
}
writeSampleLikelihoods(beagleOut, preferredVC, log10Likelihoods);
}
beagleWriter.println(beagleOut.toString());
}
static VariantContext reallyMergeIntoMNP(
VariantContext vc1, VariantContext vc2, ReferenceSequenceFile referenceFile) {
int startInter = vc1.getEnd() + 1;
int endInter = vc2.getStart() - 1;
byte[] intermediateBases = null;
if (startInter <= endInter) {
intermediateBases =
referenceFile.getSubsequenceAt(vc1.getChr(), startInter, endInter).getBases();
StringUtil.toUpperCase(intermediateBases);
}
MergedAllelesData mergeData =
new MergedAllelesData(
intermediateBases, vc1, vc2); // ensures that the reference allele is added
GenotypesContext mergedGenotypes = GenotypesContext.create();
for (final Genotype gt1 : vc1.getGenotypes()) {
Genotype gt2 = vc2.getGenotype(gt1.getSampleName());
List<Allele> site1Alleles = gt1.getAlleles();
List<Allele> site2Alleles = gt2.getAlleles();
List<Allele> mergedAllelesForSample = new LinkedList<Allele>();
/* NOTE: Since merged alleles are added to mergedAllelesForSample in the SAME order as in the input VC records,
we preserve phase information (if any) relative to whatever precedes vc1:
*/
Iterator<Allele> all2It = site2Alleles.iterator();
for (Allele all1 : site1Alleles) {
Allele all2 = all2It.next(); // this is OK, since allSamplesAreMergeable()
Allele mergedAllele = mergeData.ensureMergedAllele(all1, all2);
mergedAllelesForSample.add(mergedAllele);
}
double mergedGQ = Math.max(gt1.getLog10PError(), gt2.getLog10PError());
Set<String> mergedGtFilters =
new HashSet<
String>(); // Since gt1 and gt2 were unfiltered, the Genotype remains unfiltered
Map<String, Object> mergedGtAttribs = new HashMap<String, Object>();
PhaseAndQuality phaseQual = calcPhaseForMergedGenotypes(gt1, gt2);
if (phaseQual.PQ != null) mergedGtAttribs.put(ReadBackedPhasingWalker.PQ_KEY, phaseQual.PQ);
Genotype mergedGt =
new Genotype(
gt1.getSampleName(),
mergedAllelesForSample,
mergedGQ,
mergedGtFilters,
mergedGtAttribs,
phaseQual.isPhased);
mergedGenotypes.add(mergedGt);
}
String mergedName = mergeVariantContextNames(vc1.getSource(), vc2.getSource());
double mergedLog10PError = Math.min(vc1.getLog10PError(), vc2.getLog10PError());
Set<String> mergedFilters =
new HashSet<
String>(); // Since vc1 and vc2 were unfiltered, the merged record remains unfiltered
Map<String, Object> mergedAttribs = mergeVariantContextAttributes(vc1, vc2);
// ids
List<String> mergedIDs = new ArrayList<String>();
if (vc1.hasID()) mergedIDs.add(vc1.getID());
if (vc2.hasID()) mergedIDs.add(vc2.getID());
String mergedID =
mergedIDs.isEmpty()
? VCFConstants.EMPTY_ID_FIELD
: Utils.join(VCFConstants.ID_FIELD_SEPARATOR, mergedIDs);
VariantContextBuilder mergedBuilder =
new VariantContextBuilder(
mergedName,
vc1.getChr(),
vc1.getStart(),
vc2.getEnd(),
mergeData.getAllMergedAlleles())
.id(mergedID)
.genotypes(mergedGenotypes)
.log10PError(mergedLog10PError)
.filters(mergedFilters)
.attributes(mergedAttribs);
VariantContextUtils.calculateChromosomeCounts(mergedBuilder, true);
return mergedBuilder.make();
}
/**
* add the genotype data
*
* @param vc the variant context
* @param genotypeFormatKeys Genotype formatting string
* @param alleleMap alleles for this context
* @throws IOException for writer
*/
private void addGenotypeData(
VariantContext vc, Map<Allele, String> alleleMap, List<String> genotypeFormatKeys)
throws IOException {
for (String sample : mHeader.getGenotypeSamples()) {
mWriter.write(VCFConstants.FIELD_SEPARATOR);
Genotype g = vc.getGenotype(sample);
if (g == null) {
// TODO -- The VariantContext needs to know what the general ploidy is of the samples
// TODO -- We shouldn't be assuming diploid genotypes here!
mWriter.write(VCFConstants.EMPTY_GENOTYPE);
continue;
}
List<String> attrs = new ArrayList<String>(genotypeFormatKeys.size());
for (String key : genotypeFormatKeys) {
if (key.equals(VCFConstants.GENOTYPE_KEY)) {
if (!g.isAvailable()) {
throw new ReviewedStingException(
"GTs cannot be missing for some samples if they are available for others in the record");
}
writeAllele(g.getAllele(0), alleleMap);
for (int i = 1; i < g.getPloidy(); i++) {
mWriter.write(g.isPhased() ? VCFConstants.PHASED : VCFConstants.UNPHASED);
writeAllele(g.getAllele(i), alleleMap);
}
continue;
}
Object val = g.hasAttribute(key) ? g.getAttribute(key) : VCFConstants.MISSING_VALUE_v4;
// some exceptions
if (key.equals(VCFConstants.GENOTYPE_QUALITY_KEY)) {
if (Math.abs(g.getNegLog10PError() - Genotype.NO_NEG_LOG_10PERROR) < 1e-6)
val = VCFConstants.MISSING_VALUE_v4;
else {
val = getQualValue(Math.min(g.getPhredScaledQual(), VCFConstants.MAX_GENOTYPE_QUAL));
}
} else if (key.equals(VCFConstants.GENOTYPE_FILTER_KEY)) {
val =
g.isFiltered()
? ParsingUtils.join(";", ParsingUtils.sortList(g.getFilters()))
: (g.filtersWereApplied()
? VCFConstants.PASSES_FILTERS_v4
: VCFConstants.UNFILTERED);
}
VCFFormatHeaderLine metaData = mHeader.getFormatHeaderLine(key);
if (metaData != null) {
int numInFormatField = metaData.getCount(vc.getAlternateAlleles().size());
if (numInFormatField > 1 && val.equals(VCFConstants.MISSING_VALUE_v4)) {
// If we have a missing field but multiple values are expected, we need to construct a
// new string with all fields.
// For example, if Number=2, the string has to be ".,."
StringBuilder sb = new StringBuilder(VCFConstants.MISSING_VALUE_v4);
for (int i = 1; i < numInFormatField; i++) {
sb.append(",");
sb.append(VCFConstants.MISSING_VALUE_v4);
}
val = sb.toString();
}
}
// assume that if key is absent, then the given string encoding suffices
String outputValue = formatVCFField(val);
if (outputValue != null) attrs.add(outputValue);
}
// strip off trailing missing values
for (int i = attrs.size() - 1; i >= 0; i--) {
if (isMissingValue(attrs.get(i))) attrs.remove(i);
else break;
}
for (int i = 0; i < attrs.size(); i++) {
if (i > 0 || genotypeFormatKeys.contains(VCFConstants.GENOTYPE_KEY))
mWriter.write(VCFConstants.GENOTYPE_FIELD_SEPARATOR);
mWriter.write(attrs.get(i));
}
}
}
private boolean sampleHasVariant(Genotype g) {
return (g != null && !g.isHomRef() && (g.isCalled() || (g.isFiltered() && !EXCLUDE_FILTERED)));
}
