public Map<String, Object> annotate(
RefMetaDataTracker tracker,
AnnotatorCompatibleWalker walker,
ReferenceContext ref,
Map<String, AlignmentContext> stratifiedContexts,
VariantContext vc) {
if (stratifiedContexts.size() == 0) return null;
double mq0 = 0;
double mq10 = 0;
double total = 0;
for (Map.Entry<String, AlignmentContext> sample : stratifiedContexts.entrySet()) {
if (!sample.getValue().hasBasePileup()) continue;
for (PileupElement p : sample.getValue().getBasePileup()) {
if (p.getMappingQual() == 0) {
mq0 += 1;
}
if (p.getMappingQual() <= 10) {
mq10 += 1;
}
total += 1;
}
}
Map<String, Object> map = new HashMap<String, Object>();
map.put(
getKeyNames().get(0), String.format("%.04f,%.04f,%.00f", mq0 / total, mq10 / total, total));
return map;
}
private Haplotype getHaplotypeFromRead(
final PileupElement p, final int contextSize, final int locus) {
final GATKSAMRecord read = p.getRead();
int readOffsetFromPileup = p.getOffset();
final byte[] haplotypeBases = new byte[contextSize];
Arrays.fill(haplotypeBases, (byte) REGEXP_WILDCARD);
final double[] baseQualities = new double[contextSize];
Arrays.fill(baseQualities, 0.0);
byte[] readBases = read.getReadBases();
readBases =
AlignmentUtils.readToAlignmentByteArray(
read.getCigar(), readBases); // Adjust the read bases based on the Cigar string
byte[] readQuals = read.getBaseQualities();
readQuals =
AlignmentUtils.readToAlignmentByteArray(
read.getCigar(),
readQuals); // Shift the location of the qual scores based on the Cigar string
readOffsetFromPileup =
AlignmentUtils.calcAlignmentByteArrayOffset(
read.getCigar(), p, read.getAlignmentStart(), locus);
final int baseOffsetStart = readOffsetFromPileup - (contextSize - 1) / 2;
for (int i = 0; i < contextSize; i++) {
final int baseOffset = i + baseOffsetStart;
if (baseOffset < 0) {
continue;
}
if (baseOffset >= readBases.length) {
break;
}
if (readQuals[baseOffset] == PileupElement.DELETION_BASE) {
readQuals[baseOffset] = PileupElement.DELETION_QUAL;
}
if (!BaseUtils.isRegularBase(readBases[baseOffset])) {
readBases[baseOffset] = (byte) REGEXP_WILDCARD;
readQuals[baseOffset] = (byte) 0;
} // N's shouldn't be treated as distinct bases
readQuals[baseOffset] = (byte) Math.min((int) readQuals[baseOffset], p.getMappingQual());
if (((int) readQuals[baseOffset]) < 5) {
readQuals[baseOffset] = (byte) 0;
} // quals less than 5 are used as codes and don't have actual probabilistic meaning behind
// them
haplotypeBases[i] = readBases[baseOffset];
baseQualities[i] = (double) readQuals[baseOffset];
}
return new Haplotype(haplotypeBases, baseQualities);
}
private Map<String, Object> annotateSNP(AlignmentContext stratifiedContext, VariantContext vc) {
if (!stratifiedContext.hasBasePileup()) return null;
HashMap<Byte, Integer> alleleCounts = new HashMap<Byte, Integer>();
for (Allele allele : vc.getAlternateAlleles()) alleleCounts.put(allele.getBases()[0], 0);
ReadBackedPileup pileup = stratifiedContext.getBasePileup();
int totalDepth = pileup.size();
Map<String, Object> map = new HashMap<String, Object>();
map.put(getKeyNames().get(0), totalDepth); // put total depth in right away
if (totalDepth == 0) return map; // done, can not compute FA at 0 coverage!!
int mq0 = 0; // number of "ref" reads that are acually mq0
for (PileupElement p : pileup) {
if (p.getMappingQual() == 0) {
mq0++;
continue;
}
if (alleleCounts.containsKey(p.getBase())) // non-mq0 read and it's an alt
alleleCounts.put(p.getBase(), alleleCounts.get(p.getBase()) + 1);
}
if (mq0 == totalDepth) return map; // if all reads are mq0, there is nothing left to do
// we need to add counts in the correct order
String[] fracs = new String[alleleCounts.size()];
for (int i = 0; i < vc.getAlternateAlleles().size(); i++) {
fracs[i] =
String.format(
"%.3f",
((float) alleleCounts.get(vc.getAlternateAllele(i).getBases()[0]))
/ (totalDepth - mq0));
}
map.put(getKeyNames().get(1), fracs);
return map;
}
private double scoreReadAgainstHaplotype(
final PileupElement p, final int contextSize, final Haplotype haplotype, final int locus) {
double expected = 0.0;
double mismatches = 0.0;
// What's the expected mismatch rate under the model that this read is actually sampled from
// this haplotype? Let's assume the consensus base c is a random choice one of A, C, G, or T,
// and that
// the observed base is actually from a c with an error rate e. Since e is the rate at which
// we'd
// see a miscalled c, the expected mismatch rate is really e. So the expected number of
// mismatches
// is just sum_i e_i for i from 1..n for n sites
//
// Now, what's the probabilistic sum of mismatches? Suppose that the base b is equal to c.
// Well, it could
// actually be a miscall in a matching direction, which would happen at a e / 3 rate. If b !=
// c, then
// the chance that it is actually a mismatch is 1 - e, since any of the other 3 options would be
// a mismatch.
// so the probability-weighted mismatch rate is sum_i ( matched ? e_i / 3 : 1 - e_i ) for i = 1
// ... n
final byte[] haplotypeBases = haplotype.getBases();
final GATKSAMRecord read = p.getRead();
byte[] readBases = read.getReadBases();
readBases =
AlignmentUtils.readToAlignmentByteArray(
p.getRead().getCigar(), readBases); // Adjust the read bases based on the Cigar string
byte[] readQuals = read.getBaseQualities();
readQuals =
AlignmentUtils.readToAlignmentByteArray(
p.getRead().getCigar(),
readQuals); // Shift the location of the qual scores based on the Cigar string
int readOffsetFromPileup = p.getOffset();
readOffsetFromPileup =
AlignmentUtils.calcAlignmentByteArrayOffset(
p.getRead().getCigar(), p, read.getAlignmentStart(), locus);
final int baseOffsetStart = readOffsetFromPileup - (contextSize - 1) / 2;
for (int i = 0; i < contextSize; i++) {
final int baseOffset = i + baseOffsetStart;
if (baseOffset < 0) {
continue;
}
if (baseOffset >= readBases.length) {
break;
}
final byte haplotypeBase = haplotypeBases[i];
final byte readBase = readBases[baseOffset];
final boolean matched =
(readBase == haplotypeBase || haplotypeBase == (byte) REGEXP_WILDCARD);
byte qual = readQuals[baseOffset];
if (qual == PileupElement.DELETION_BASE) {
qual = PileupElement.DELETION_QUAL;
} // calcAlignmentByteArrayOffset fills the readQuals array with DELETION_BASE at deletions
qual = (byte) Math.min((int) qual, p.getMappingQual());
if (((int) qual)
>= 5) { // quals less than 5 are used as codes and don't have actual probabilistic meaning
// behind them
final double e = QualityUtils.qualToErrorProb(qual);
expected += e;
mismatches += matched ? e : 1.0 - e / 3.0;
}
// a more sophisticated calculation would include the reference quality, but it's nice to
// actually penalize
// the mismatching of poorly determined regions of the consensus
}
return mismatches - expected;
}
