예제 #1
0
  private void writeSampleLikelihoods(
      StringBuffer out, VariantContext vc, double[] log10Likelihoods) {
    if (VQSRCalibrator != null) {
      log10Likelihoods =
          VQSRCalibrator.includeErrorRateInLikelihoods(VQSLOD_KEY, vc, log10Likelihoods);
    }

    double[] normalizedLikelihoods = MathUtils.normalizeFromLog10(log10Likelihoods);
    // see if we need to randomly mask out genotype in this position.
    for (double likeVal : normalizedLikelihoods) {
      out.append(formatter.format(likeVal));
      //            out.append(String.format("%5.4f ",likeVal));
    }
  }
예제 #2
0
  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());
  }