Exemple #1
0
  /**
   * 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;
  }
  @Test(dataProvider = "RepeatDetectorTest")
  public void testRepeatDetectorTest(RepeatDetectorTest cfg) {

    // test alleles are equal
    Assert.assertEquals(
        VariantContextUtils.isTandemRepeat(cfg.vc, cfg.ref.getBytes()), cfg.isTrueRepeat);
  }
  @Test(dataProvider = "mergeAlleles")
  public void testMergeAlleles(MergeAllelesTest cfg) {
    final List<VariantContext> inputs = new ArrayList<VariantContext>();

    int i = 0;
    for (final List<Allele> alleles : cfg.inputs) {
      final String name = "vcf" + ++i;
      inputs.add(makeVC(name, alleles));
    }

    final List<String> priority = vcs2priority(inputs);

    final VariantContext merged =
        VariantContextUtils.simpleMerge(
            genomeLocParser,
            inputs,
            priority,
            VariantContextUtils.FilteredRecordMergeType.KEEP_IF_ANY_UNFILTERED,
            VariantContextUtils.GenotypeMergeType.PRIORITIZE,
            false,
            false,
            "set",
            false,
            false);

    Assert.assertEquals(merged.getAlleles(), cfg.expected);
  }
  @Test(dataProvider = "mergeFiltered")
  public void testMergeFiltered(MergeFilteredTest cfg) {
    final List<String> priority = vcs2priority(cfg.inputs);
    final VariantContext merged =
        VariantContextUtils.simpleMerge(
            genomeLocParser,
            cfg.inputs,
            priority,
            cfg.type,
            VariantContextUtils.GenotypeMergeType.PRIORITIZE,
            true,
            false,
            "set",
            false,
            false);

    // test alleles are equal
    Assert.assertEquals(merged.getAlleles(), cfg.expected.getAlleles());

    // test set field
    Assert.assertEquals(merged.getAttribute("set"), cfg.setExpected);

    // test filter field
    Assert.assertEquals(merged.getFilters(), cfg.expected.getFilters());
  }
  @Test
  public void testAnnotationSet() {
    for (final boolean annotate : Arrays.asList(true, false)) {
      for (final String set : Arrays.asList("set", "combine", "x")) {
        final List<String> priority = Arrays.asList("1", "2");
        VariantContext vc1 = makeVC("1", Arrays.asList(Aref, T), VariantContext.PASSES_FILTERS);
        VariantContext vc2 = makeVC("2", Arrays.asList(Aref, T), VariantContext.PASSES_FILTERS);

        final VariantContext merged =
            VariantContextUtils.simpleMerge(
                genomeLocParser,
                Arrays.asList(vc1, vc2),
                priority,
                VariantContextUtils.FilteredRecordMergeType.KEEP_IF_ANY_UNFILTERED,
                VariantContextUtils.GenotypeMergeType.PRIORITIZE,
                annotate,
                false,
                set,
                false,
                false);

        if (annotate)
          Assert.assertEquals(merged.getAttribute(set), VariantContextUtils.MERGE_INTERSECTION);
        else Assert.assertFalse(merged.hasAttribute(set));
      }
    }
  }
Exemple #6
0
  static boolean mergeIntoMNPvalidationCheck(
      GenomeLocParser genomeLocParser, VariantContext vc1, VariantContext vc2) {
    GenomeLoc loc1 = VariantContextUtils.getLocation(genomeLocParser, vc1);
    GenomeLoc loc2 = VariantContextUtils.getLocation(genomeLocParser, vc2);

    if (!loc1.onSameContig(loc2))
      throw new ReviewedStingException("Can only merge vc1, vc2 if on the same chromosome");

    if (!loc1.isBefore(loc2))
      throw new ReviewedStingException("Can only merge if vc1 is BEFORE vc2");

    if (vc1.isFiltered() || vc2.isFiltered()) return false;

    if (!vc1.getSampleNames()
        .equals(vc2.getSampleNames())) // vc1, vc2 refer to different sample sets
    return false;

    if (!allGenotypesAreUnfilteredAndCalled(vc1) || !allGenotypesAreUnfilteredAndCalled(vc2))
      return false;

    return true;
  }
  @Test(expectedExceptions = UserException.class)
  public void testMergeGenotypesRequireUnique() {
    final VariantContext vc1 = makeVC("1", Arrays.asList(Aref, T), makeG("s1", Aref, T, -1));
    final VariantContext vc2 = makeVC("2", Arrays.asList(Aref, T), makeG("s1", Aref, T, -2));

    final VariantContext merged =
        VariantContextUtils.simpleMerge(
            genomeLocParser,
            Arrays.asList(vc1, vc2),
            null,
            VariantContextUtils.FilteredRecordMergeType.KEEP_IF_ANY_UNFILTERED,
            VariantContextUtils.GenotypeMergeType.REQUIRE_UNIQUE,
            false,
            false,
            "set",
            false,
            false);
  }
Exemple #8
0
  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());
      }
    }
  }
  @Test(dataProvider = "mergeGenotypes")
  public void testMergeGenotypes(MergeGenotypesTest cfg) {
    final VariantContext merged =
        VariantContextUtils.simpleMerge(
            genomeLocParser,
            cfg.inputs,
            cfg.priority,
            VariantContextUtils.FilteredRecordMergeType.KEEP_IF_ANY_UNFILTERED,
            VariantContextUtils.GenotypeMergeType.PRIORITIZE,
            true,
            false,
            "set",
            false,
            false);

    // test alleles are equal
    Assert.assertEquals(merged.getAlleles(), cfg.expected.getAlleles());

    // test genotypes
    assertGenotypesAreMostlyEqual(merged.getGenotypes(), cfg.expected.getGenotypes());
  }
  @Test
  public void testMergeGenotypesUniquify() {
    final VariantContext vc1 = makeVC("1", Arrays.asList(Aref, T), makeG("s1", Aref, T, -1));
    final VariantContext vc2 = makeVC("2", Arrays.asList(Aref, T), makeG("s1", Aref, T, -2));

    final VariantContext merged =
        VariantContextUtils.simpleMerge(
            genomeLocParser,
            Arrays.asList(vc1, vc2),
            null,
            VariantContextUtils.FilteredRecordMergeType.KEEP_IF_ANY_UNFILTERED,
            VariantContextUtils.GenotypeMergeType.UNIQUIFY,
            false,
            false,
            "set",
            false,
            false);

    // test genotypes
    Assert.assertEquals(
        merged.getSampleNames(), new HashSet<String>(Arrays.asList("s1.1", "s1.2")));
  }
  /**
   * Method for creating JexlVCMatchExp from input walker arguments names and exps. These two arrays
   * contain the name associated with each JEXL expression. initializeMatchExps will parse each
   * expression and return a list of JexlVCMatchExp, in order, that correspond to the names and
   * exps. These are suitable input to match() below.
   *
   * @param names names
   * @param exps expressions
   * @return list of matches
   */
  public static List<JexlVCMatchExp> initializeMatchExps(String[] names, String[] exps) {
    if (names == null || exps == null)
      throw new ReviewedStingException(
          "BUG: neither names nor exps can be null: names "
              + Arrays.toString(names)
              + " exps="
              + Arrays.toString(exps));

    if (names.length != exps.length)
      throw new UserException(
          "Inconsistent number of provided filter names and expressions: names="
              + Arrays.toString(names)
              + " exps="
              + Arrays.toString(exps));

    Map<String, String> map = new HashMap<String, String>();
    for (int i = 0; i < names.length; i++) {
      map.put(names[i], exps[i]);
    }

    return VariantContextUtils.initializeMatchExps(map);
  }
  @Test(dataProvider = "simplemergersiddata")
  public void testRSIDMerge(SimpleMergeRSIDTest cfg) {
    VariantContext snpVC1 = makeVC("snpvc1", Arrays.asList(Aref, T));
    final List<VariantContext> inputs = new ArrayList<VariantContext>();

    for (final String id : cfg.inputs) {
      inputs.add(new VariantContextBuilder(snpVC1).id(id).make());
    }

    final VariantContext merged =
        VariantContextUtils.simpleMerge(
            genomeLocParser,
            inputs,
            null,
            VariantContextUtils.FilteredRecordMergeType.KEEP_IF_ANY_UNFILTERED,
            VariantContextUtils.GenotypeMergeType.UNSORTED,
            false,
            false,
            "set",
            false,
            false);
    Assert.assertEquals(merged.getID(), cfg.expected);
  }
 @Test(dataProvider = "ReverseClippingPositionTestProvider")
 public void testReverseClippingPositionTestProvider(ReverseClippingPositionTestProvider cfg) {
   int result =
       VariantContextUtils.computeReverseClipping(cfg.alleles, cfg.ref.getBytes(), 0, false);
   Assert.assertEquals(result, cfg.expectedClip);
 }
  /** Initialize the stratifications, evaluations, evaluation contexts, and reporting object */
  public void initialize() {
    // Just list the modules, and exit quickly.
    if (LIST) {
      variantEvalUtils.listModulesAndExit();
    }

    // maintain the full list of comps
    comps.addAll(compsProvided);
    if (dbsnp.dbsnp.isBound()) {
      comps.add(dbsnp.dbsnp);
      knowns.add(dbsnp.dbsnp);
    }

    // Add a dummy comp track if none exists
    if (comps.size() == 0)
      comps.add(
          new RodBinding<VariantContext>(VariantContext.class, "none", "UNBOUND", "", new Tags()));

    // Set up set of additional knowns
    for (RodBinding<VariantContext> compRod : comps) {
      if (KNOWN_NAMES.contains(compRod.getName())) knowns.add(compRod);
    }

    // Now that we have all the rods categorized, determine the sample list from the eval rods.
    Map<String, VCFHeader> vcfRods = VCFUtils.getVCFHeadersFromRods(getToolkit(), evals);
    Set<String> vcfSamples =
        SampleUtils.getSampleList(vcfRods, VariantContextUtils.GenotypeMergeType.REQUIRE_UNIQUE);

    // Load the sample list
    sampleNamesForEvaluation.addAll(
        SampleUtils.getSamplesFromCommandLineInput(vcfSamples, SAMPLE_EXPRESSIONS));
    numSamples = NUM_SAMPLES > 0 ? NUM_SAMPLES : sampleNamesForEvaluation.size();

    if (Arrays.asList(STRATIFICATIONS_TO_USE).contains("Sample")) {
      sampleNamesForStratification.addAll(sampleNamesForEvaluation);
    }
    sampleNamesForStratification.add(ALL_SAMPLE_NAME);

    // Initialize select expressions
    for (VariantContextUtils.JexlVCMatchExp jexl :
        VariantContextUtils.initializeMatchExps(SELECT_NAMES, SELECT_EXPS)) {
      SortableJexlVCMatchExp sjexl = new SortableJexlVCMatchExp(jexl.name, jexl.exp);
      jexlExpressions.add(sjexl);
    }

    // Initialize the set of stratifications and evaluations to use
    stratificationObjects =
        variantEvalUtils.initializeStratificationObjects(
            this, NO_STANDARD_STRATIFICATIONS, STRATIFICATIONS_TO_USE);
    Set<Class<? extends VariantEvaluator>> evaluationObjects =
        variantEvalUtils.initializeEvaluationObjects(NO_STANDARD_MODULES, MODULES_TO_USE);
    for (VariantStratifier vs : getStratificationObjects()) {
      if (vs.getName().equals("Filter")) byFilterIsEnabled = true;
      else if (vs.getName().equals("Sample")) perSampleIsEnabled = true;
    }

    if (intervalsFile != null) {
      boolean fail = true;
      for (final VariantStratifier vs : stratificationObjects) {
        if (vs.getClass().equals(IntervalStratification.class)) fail = false;
      }
      if (fail)
        throw new UserException.BadArgumentValue(
            "ST", "stratIntervals argument provided but -ST IntervalStratification not provided");
    }

    // Initialize the evaluation contexts
    evaluationContexts =
        variantEvalUtils.initializeEvaluationContexts(
            stratificationObjects, evaluationObjects, null, null);

    // Initialize report table
    report = variantEvalUtils.initializeGATKReport(stratificationObjects, evaluationObjects);

    // Load ancestral alignments
    if (ancestralAlignmentsFile != null) {
      try {
        ancestralAlignments = new IndexedFastaSequenceFile(ancestralAlignmentsFile);
      } catch (FileNotFoundException e) {
        throw new ReviewedStingException(
            String.format(
                "The ancestral alignments file, '%s', could not be found",
                ancestralAlignmentsFile.getAbsolutePath()));
      }
    }

    // initialize CNVs
    if (knownCNVsFile != null) {
      knownCNVsByContig = createIntervalTreeByContig(knownCNVsFile);
    }
  }
Exemple #15
0
  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();
  }
Exemple #16
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  /**
   * Subset VC record if necessary and emit the modified record (provided it satisfies criteria for
   * printing)
   *
   * @param tracker the ROD tracker
   * @param ref reference information
   * @param context alignment info
   * @return 1 if the record was printed to the output file, 0 if otherwise
   */
  @Override
  public Integer map(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context) {
    if (tracker == null) return 0;

    Collection<VariantContext> vcs =
        tracker.getValues(variantCollection.variants, context.getLocation());

    if (vcs == null || vcs.size() == 0) {
      return 0;
    }

    for (VariantContext vc : vcs) {
      if (MENDELIAN_VIOLATIONS) {
        boolean foundMV = false;
        for (MendelianViolation mv : mvSet) {
          if (mv.isViolation(vc)) {
            foundMV = true;
            // System.out.println(vc.toString());
            if (outMVFile != null)
              outMVFileStream.format(
                  "MV@%s:%d. REF=%s, ALT=%s, AC=%d, momID=%s, dadID=%s, childID=%s, momG=%s, momGL=%s, dadG=%s, dadGL=%s, "
                      + "childG=%s childGL=%s\n",
                  vc.getChr(),
                  vc.getStart(),
                  vc.getReference().getDisplayString(),
                  vc.getAlternateAllele(0).getDisplayString(),
                  vc.getChromosomeCount(vc.getAlternateAllele(0)),
                  mv.getSampleMom(),
                  mv.getSampleDad(),
                  mv.getSampleChild(),
                  vc.getGenotype(mv.getSampleMom()).toBriefString(),
                  vc.getGenotype(mv.getSampleMom()).getLikelihoods().getAsString(),
                  vc.getGenotype(mv.getSampleDad()).toBriefString(),
                  vc.getGenotype(mv.getSampleMom()).getLikelihoods().getAsString(),
                  vc.getGenotype(mv.getSampleChild()).toBriefString(),
                  vc.getGenotype(mv.getSampleChild()).getLikelihoods().getAsString());
          }
        }

        if (!foundMV) break;
      }
      if (DISCORDANCE_ONLY) {
        Collection<VariantContext> compVCs =
            tracker.getValues(discordanceTrack, context.getLocation());
        if (!isDiscordant(vc, compVCs)) return 0;
      }
      if (CONCORDANCE_ONLY) {
        Collection<VariantContext> compVCs =
            tracker.getValues(concordanceTrack, context.getLocation());
        if (!isConcordant(vc, compVCs)) return 0;
      }

      if (alleleRestriction.equals(NumberAlleleRestriction.BIALLELIC) && !vc.isBiallelic())
        continue;

      if (alleleRestriction.equals(NumberAlleleRestriction.MULTIALLELIC) && vc.isBiallelic())
        continue;

      if (!selectedTypes.contains(vc.getType())) continue;

      VariantContext sub = subsetRecord(vc, samples);
      if ((sub.isPolymorphic() || !EXCLUDE_NON_VARIANTS)
          && (!sub.isFiltered() || !EXCLUDE_FILTERED)) {
        for (VariantContextUtils.JexlVCMatchExp jexl : jexls) {
          if (!VariantContextUtils.match(sub, jexl)) {
            return 0;
          }
        }
        if (SELECT_RANDOM_NUMBER) {
          randomlyAddVariant(++variantNumber, sub, ref.getBase());
        } else if (!SELECT_RANDOM_FRACTION
            || (GenomeAnalysisEngine.getRandomGenerator().nextDouble() < fractionRandom)) {
          vcfWriter.add(sub);
        }
      }
    }

    return 1;
  }
Exemple #17
0
  /** Set up the VCF writer, the sample expressions and regexs, and the JEXL matcher */
  public void initialize() {
    // Get list of samples to include in the output
    List<String> rodNames = Arrays.asList(variantCollection.variants.getName());

    Map<String, VCFHeader> vcfRods = VCFUtils.getVCFHeadersFromRods(getToolkit(), rodNames);
    TreeSet<String> vcfSamples =
        new TreeSet<String>(
            SampleUtils.getSampleList(
                vcfRods, VariantContextUtils.GenotypeMergeType.REQUIRE_UNIQUE));

    Collection<String> samplesFromFile = SampleUtils.getSamplesFromFiles(sampleFiles);
    Collection<String> samplesFromExpressions =
        SampleUtils.matchSamplesExpressions(vcfSamples, sampleExpressions);

    // first, add any requested samples
    samples.addAll(samplesFromFile);
    samples.addAll(samplesFromExpressions);
    samples.addAll(sampleNames);

    // if none were requested, we want all of them
    if (samples.isEmpty()) {
      samples.addAll(vcfSamples);
      NO_SAMPLES_SPECIFIED = true;
    }

    // now, exclude any requested samples
    Collection<String> XLsamplesFromFile = SampleUtils.getSamplesFromFiles(XLsampleFiles);
    samples.removeAll(XLsamplesFromFile);
    samples.removeAll(XLsampleNames);

    if (samples.size() == 0 && !NO_SAMPLES_SPECIFIED)
      throw new UserException(
          "All samples requested to be included were also requested to be excluded.");

    for (String sample : samples) logger.info("Including sample '" + sample + "'");

    // if user specified types to include, add these, otherwise, add all possible variant context
    // types to list of vc types to include
    if (TYPES_TO_INCLUDE.isEmpty()) {

      for (VariantContext.Type t : VariantContext.Type.values()) selectedTypes.add(t);

    } else {
      for (VariantContext.Type t : TYPES_TO_INCLUDE) selectedTypes.add(t);
    }
    // Initialize VCF header
    Set<VCFHeaderLine> headerLines = VCFUtils.smartMergeHeaders(vcfRods.values(), logger);
    headerLines.add(new VCFHeaderLine("source", "SelectVariants"));

    if (KEEP_ORIGINAL_CHR_COUNTS) {
      headerLines.add(
          new VCFFormatHeaderLine("AC_Orig", 1, VCFHeaderLineType.Integer, "Original AC"));
      headerLines.add(
          new VCFFormatHeaderLine("AF_Orig", 1, VCFHeaderLineType.Float, "Original AF"));
      headerLines.add(
          new VCFFormatHeaderLine("AN_Orig", 1, VCFHeaderLineType.Integer, "Original AN"));
    }
    vcfWriter.writeHeader(new VCFHeader(headerLines, samples));

    for (int i = 0; i < SELECT_EXPRESSIONS.size(); i++) {
      // It's not necessary that the user supply select names for the JEXL expressions, since those
      // expressions will only be needed for omitting records.  Make up the select names here.
      selectNames.add(String.format("select-%d", i));
    }

    jexls = VariantContextUtils.initializeMatchExps(selectNames, SELECT_EXPRESSIONS);

    // Look at the parameters to decide which analysis to perform
    DISCORDANCE_ONLY = discordanceTrack.isBound();
    if (DISCORDANCE_ONLY)
      logger.info(
          "Selecting only variants discordant with the track: " + discordanceTrack.getName());

    CONCORDANCE_ONLY = concordanceTrack.isBound();
    if (CONCORDANCE_ONLY)
      logger.info(
          "Selecting only variants concordant with the track: " + concordanceTrack.getName());

    if (MENDELIAN_VIOLATIONS) {
      if (FAMILY_STRUCTURE_FILE != null) {
        try {
          for (final String line : new XReadLines(FAMILY_STRUCTURE_FILE)) {
            MendelianViolation mv =
                new MendelianViolation(line, MENDELIAN_VIOLATION_QUAL_THRESHOLD);
            if (samples.contains(mv.getSampleChild())
                && samples.contains(mv.getSampleDad())
                && samples.contains(mv.getSampleMom())) mvSet.add(mv);
          }
        } catch (FileNotFoundException e) {
          throw new UserException.CouldNotReadInputFile(FAMILY_STRUCTURE_FILE, e);
        }
        if (outMVFile != null)
          try {
            outMVFileStream = new PrintStream(outMVFile);
          } catch (FileNotFoundException e) {
            throw new UserException.CouldNotCreateOutputFile(
                outMVFile, "Can't open output file", e);
          }
      } else
        mvSet.add(new MendelianViolation(FAMILY_STRUCTURE, MENDELIAN_VIOLATION_QUAL_THRESHOLD));
    } else if (!FAMILY_STRUCTURE.isEmpty()) {
      mvSet.add(new MendelianViolation(FAMILY_STRUCTURE, MENDELIAN_VIOLATION_QUAL_THRESHOLD));
      MENDELIAN_VIOLATIONS = true;
    }

    SELECT_RANDOM_NUMBER = numRandom > 0;
    if (SELECT_RANDOM_NUMBER) {
      logger.info("Selecting " + numRandom + " variants at random from the variant track");
      variantArray = new RandomVariantStructure[numRandom];
    }

    SELECT_RANDOM_FRACTION = fractionRandom > 0;
    if (SELECT_RANDOM_FRACTION)
      logger.info(
          "Selecting approximately "
              + 100.0 * fractionRandom
              + "% of the variants at random from the variant track");
  }
  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());
  }
  /**
   * 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));
  }