Esempio n. 1
0
  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);
  }
Esempio n. 2
0
  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;
  }