@Test
public void testFixReverseComplementedGenotypes() {
final Allele refA = Allele.create("A", true);
final Allele altC = Allele.create("C", false);
final GenotypesContext originalGenotypes = GenotypesContext.create(3);
originalGenotypes.add(new GenotypeBuilder("homref").alleles(Arrays.asList(refA, refA)).make());
originalGenotypes.add(new GenotypeBuilder("het").alleles(Arrays.asList(refA, altC)).make());
originalGenotypes.add(new GenotypeBuilder("homvar").alleles(Arrays.asList(altC, altC)).make());
final Allele refT = Allele.create("T", true);
final Allele altG = Allele.create("G", false);
final GenotypesContext expectedGenotypes = GenotypesContext.create(3);
expectedGenotypes.add(new GenotypeBuilder("homref").alleles(Arrays.asList(refT, refT)).make());
expectedGenotypes.add(new GenotypeBuilder("het").alleles(Arrays.asList(refT, altG)).make());
expectedGenotypes.add(new GenotypeBuilder("homvar").alleles(Arrays.asList(altG, altG)).make());
final Map<Allele, Allele> reverseComplementAlleleMap = new HashMap<Allele, Allele>(2);
reverseComplementAlleleMap.put(refA, refT);
reverseComplementAlleleMap.put(altC, altG);
final GenotypesContext actualGenotypes =
LiftoverVcf.fixGenotypes(originalGenotypes, reverseComplementAlleleMap);
for (final String sample : Arrays.asList("homref", "het", "homvar")) {
final List<Allele> expected = expectedGenotypes.get(sample).getAlleles();
final List<Allele> actual = actualGenotypes.get(sample).getAlleles();
Assert.assertEquals(expected.get(0), actual.get(0));
Assert.assertEquals(expected.get(1), actual.get(1));
}
}
/**
* Test doesMaskCoverVariant() logic
*
* @param contig chromosome or contig name
* @param start variant context start
* @param stop variant context stop
* @param maskName mask or filter name
* @param maskExtension bases beyond the mask
* @param vcBeforeLoc if true, variant context is before the genome location; if false, the
* converse is true.
* @param expectedValue return the expected return value from doesMaskCoverVariant()
*/
@Test(dataProvider = "VariantMaskData")
public void TestDoesMaskCoverVariant(
final String contig,
final int start,
final int stop,
final String maskName,
final int maskExtension,
final boolean vcBeforeLoc,
final boolean expectedValue) {
// Build VariantContext
final byte[] allele1 = Utils.dupBytes((byte) 'A', 1);
final byte[] allele2 = Utils.dupBytes((byte) 'T', 2);
final List<Allele> alleles = new ArrayList<Allele>(2);
final Allele ref = Allele.create(allele1, true);
final Allele alt = Allele.create(allele2, false);
alleles.add(ref);
alleles.add(alt);
final VariantContext vc =
new VariantContextBuilder("test", contig, start, stop, alleles).filter(vcFilter).make();
boolean coversVariant =
VariantFiltration.doesMaskCoverVariant(vc, genomeLoc, maskName, maskExtension, vcBeforeLoc);
Assert.assertEquals(coversVariant, expectedValue);
}
private Collection<VariantContext> getVariantContexts(
RefMetaDataTracker tracker, ReferenceContext ref) {
List<Feature> features = tracker.getValues(variants, ref.getLocus());
List<VariantContext> VCs = new ArrayList<VariantContext>(features.size());
for (Feature record : features) {
if (VariantContextAdaptors.canBeConvertedToVariantContext(record)) {
// we need to special case the HapMap format because indels aren't handled correctly
if (record instanceof RawHapMapFeature) {
// is it an indel?
RawHapMapFeature hapmap = (RawHapMapFeature) record;
if (hapmap.getAlleles()[0].equals(RawHapMapFeature.NULL_ALLELE_STRING)
|| hapmap.getAlleles()[1].equals(RawHapMapFeature.NULL_ALLELE_STRING)) {
// get the dbsnp object corresponding to this record (needed to help us distinguish
// between insertions and deletions)
VariantContext dbsnpVC = getDbsnp(hapmap.getName());
if (dbsnpVC == null || dbsnpVC.isMixed()) continue;
Map<String, Allele> alleleMap = new HashMap<String, Allele>(2);
alleleMap.put(
RawHapMapFeature.DELETION,
Allele.create(ref.getBase(), dbsnpVC.isSimpleInsertion()));
alleleMap.put(
RawHapMapFeature.INSERTION,
Allele.create(
(char) ref.getBase() + ((RawHapMapFeature) record).getAlleles()[1],
!dbsnpVC.isSimpleInsertion()));
hapmap.setActualAlleles(alleleMap);
// also, use the correct positioning for insertions
hapmap.updatePosition(dbsnpVC.getStart());
if (hapmap.getStart() < ref.getWindow().getStart()) {
logger.warn(
"Hapmap record at "
+ ref.getLocus()
+ " represents an indel too large to be converted; skipping...");
continue;
}
}
}
// ok, we might actually be able to turn this record in a variant context
VariantContext vc =
VariantContextAdaptors.toVariantContext(variants.getName(), record, ref);
if (vc != null) // sometimes the track has odd stuff in it that can't be converted
VCs.add(vc);
}
}
return VCs;
}
private VariantContext makeVC() {
final GenotypesContext testGC = GenotypesContext.create(2);
final Allele refAllele = Allele.create("A", true);
final Allele altAllele = Allele.create("T");
return (new VariantContextBuilder())
.alleles(Arrays.asList(refAllele, altAllele))
.chr("1")
.start(15L)
.stop(15L)
.genotypes(testGC)
.make();
}
/**
* Loop over all of the reads in this likelihood map and realign them to its most likely haplotype
*
* @param haplotypes the collection of haplotypes
* @param paddedReferenceLoc the active region
*/
public void realignReadsToMostLikelyHaplotype(
final Collection<Haplotype> haplotypes, final GenomeLoc paddedReferenceLoc) {
// we need to remap the Alleles back to the Haplotypes; inefficient but unfortunately this is a
// requirement currently
final Map<Allele, Haplotype> alleleToHaplotypeMap = new HashMap<>(haplotypes.size());
Haplotype refHaplotype = null;
for (final Haplotype haplotype : haplotypes) {
alleleToHaplotypeMap.put(Allele.create(haplotype.getBases()), haplotype);
if (refHaplotype == null && haplotype.isReference()) refHaplotype = haplotype;
}
final Map<GATKSAMRecord, Map<Allele, Double>> newLikelihoodReadMap =
new LinkedHashMap<>(likelihoodReadMap.size());
for (final Map.Entry<GATKSAMRecord, Map<Allele, Double>> entry : likelihoodReadMap.entrySet()) {
final MostLikelyAllele bestAllele =
PerReadAlleleLikelihoodMap.getMostLikelyAllele(entry.getValue());
final GATKSAMRecord alignedToRef =
AlignmentUtils.createReadAlignedToRef(
entry.getKey(),
alleleToHaplotypeMap.get(bestAllele.getMostLikelyAllele()),
refHaplotype,
paddedReferenceLoc.getStart(),
bestAllele.isInformative());
newLikelihoodReadMap.put(alignedToRef, entry.getValue());
}
likelihoodReadMap.clear();
likelihoodReadMap.putAll(newLikelihoodReadMap);
}
static {
final StringBuilder sb = new StringBuilder(51);
testAlleles = new ArrayList<>(51);
sb.append('A');
for (int i = 0; i <= 50; i++) {
testAlleles.add(Allele.create(sb.toString().getBytes(), i == 0));
sb.append('A');
}
}
/**
* Generate testing alleles.
*
* <p>Basically all are random alleles given the maximum allele length.
*
* <p>So with a low max-allele-length and high allele-count you can force repeats.
*
* @param alleleCount number of alleles to generate.
* @param maxAlleleLength the maximum length of the allele in bases.
* @param skipIfRepeats throw an test-skip exception {@link SkipException} if the resulting
* allele-list has repeats, thus is size is less than {@code alleleCount}
* @throws RuntimeException if {@code alleleCount} is negative or {@code maxAlleleLength} is less
* than 1.
* @return never {@code null}.
*/
static AlleleList<Allele> alleleList(
final int alleleCount, final int maxAlleleLength, final boolean skipIfRepeats) {
final Allele[] alleles =
AlleleListUnitTester.generateRandomAlleles(alleleCount, maxAlleleLength);
if (alleleCount > 0) alleles[0] = Allele.create(alleles[0].getBases(), true);
final AlleleList<Allele> alleleList = new IndexedAlleleList<>(alleles);
if (skipIfRepeats && alleleList.alleleCount() != alleles.length)
throw new SkipException("repeated alleles, should be infrequent");
return alleleList;
}
/**
* Generate testing alleles.
*
* <p>Basically all are random alleles given the maximum allele length.
*
* <p>So with a low max-allele-length and high allele-count you can force repeats.
*
* @param alleleCount number of alleles to generate.
* @param maxAlleleLength the maximum length of the allele in bases.
* @throws RuntimeException if {@code alleleCount} is negative or {@code maxAlleleLength} is less
* than 1.
* @return never {@code null}.
*/
public static Allele[] generateRandomAlleles(final int alleleCount, final int maxAlleleLength) {
if (maxAlleleLength < 1)
throw new IllegalArgumentException("the max allele length cannot be less than 1");
final Allele[] result = new Allele[alleleCount];
for (int i = 0; i < alleleCount; i++) {
final int alleleLength = rnd.nextInt(maxAlleleLength) + 1;
result[i] = Allele.create(rndDNA.nextBases(alleleLength));
}
return result;
}
/** Debug method to dump contents of object into string for display */
public String toString() {
final StringBuilder sb = new StringBuilder();
sb.append("Alelles in map:");
for (final Allele a : alleles) {
sb.append(a.getDisplayString() + ",");
}
sb.append("\n");
for (final Map.Entry<GATKSAMRecord, Map<Allele, Double>> el :
getLikelihoodReadMap().entrySet()) {
for (final Map.Entry<Allele, Double> eli : el.getValue().entrySet()) {
sb.append(
"Read "
+ el.getKey().getReadName()
+ ". Allele:"
+ eli.getKey().getDisplayString()
+ " has likelihood="
+ Double.toString(eli.getValue())
+ "\n");
}
}
return sb.toString();
}
/**
* Outputs all intervals that are behind the current reference locus
*
* @param refLocus the current reference locus
* @param refBase the reference allele
*/
private void outputFinishedIntervals(final GenomeLoc refLocus, final byte refBase) {
// output any intervals that were finished
final List<GenomeLoc> toRemove = new LinkedList<>();
for (GenomeLoc key : intervalMap.keySet()) {
if (key.isBefore(refLocus)) {
final IntervalStratification intervalStats = intervalMap.get(key);
outputStatsToVCF(intervalStats, Allele.create(refBase, true));
if (hasMissingLoci(intervalStats)) {
outputMissingInterval(intervalStats);
}
toRemove.add(key);
}
}
for (GenomeLoc key : toRemove) {
intervalMap.remove(key);
}
}
@Test
public void testPerReadAlleleLikelihoodMap() {
final PerReadAlleleLikelihoodMap map = new PerReadAlleleLikelihoodMap();
final Allele alleleA = Allele.create("A");
final double lik = -1.0; // ignored
final int[] MQs = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, QualityUtils.MAPPING_QUALITY_UNAVAILABLE};
final List<Integer> MQsList = Arrays.asList(ArrayUtils.toObject(MQs));
// MQ 255 are excluded from the calculations, we test it here.
final List<Integer> MQsListOK = new ArrayList<>(MQsList);
// NOTE: if we just call remove(i), Java thinks i is an index.
// A workaround for this overloading bogosity to to call removeAll and pass a collection
// (casting i to (Object) would work too but it's more error prone)
MQsListOK.removeAll(Collections.singleton(QualityUtils.MAPPING_QUALITY_UNAVAILABLE));
final int n1A = MQs.length;
for (int i = 0; i < n1A; i++) {
final GATKRead read = ArtificialReadUtils.createArtificialRead(TextCigarCodec.decode("10M"));
read.setMappingQuality(MQs[i]);
map.add(read, alleleA, lik);
}
final Map<String, PerReadAlleleLikelihoodMap> perReadAlleleLikelihoodMap =
Collections.singletonMap("sample1", map);
final VariantContext vc = makeVC();
final ReferenceContext referenceContext = null;
final Map<String, Object> annotate =
new RMSMappingQuality().annotate(referenceContext, vc, perReadAlleleLikelihoodMap);
Assert.assertEquals(annotate.size(), 1, "size");
Assert.assertEquals(
annotate.keySet(), Collections.singleton(VCFConstants.RMS_MAPPING_QUALITY_KEY), "annots");
final double rms = MathUtils.rms(MQsListOK); // only those are MQ0
Assert.assertEquals(
annotate.get(VCFConstants.RMS_MAPPING_QUALITY_KEY), String.format("%.2f", rms));
}
@Override
protected Object doWork() {
IOUtil.assertFileIsReadable(INPUT);
IOUtil.assertFileIsReadable(REFERENCE_SEQUENCE);
IOUtil.assertFileIsReadable(CHAIN);
IOUtil.assertFileIsWritable(OUTPUT);
IOUtil.assertFileIsWritable(REJECT);
////////////////////////////////////////////////////////////////////////
// Setup the inputs
////////////////////////////////////////////////////////////////////////
final LiftOver liftOver = new LiftOver(CHAIN);
final VCFFileReader in = new VCFFileReader(INPUT, false);
logger.info("Loading up the target reference genome.");
final ReferenceSequenceFileWalker walker = new ReferenceSequenceFileWalker(REFERENCE_SEQUENCE);
final Map<String, byte[]> refSeqs = new HashMap<>();
for (final SAMSequenceRecord rec : walker.getSequenceDictionary().getSequences()) {
refSeqs.put(rec.getSequenceName(), walker.get(rec.getSequenceIndex()).getBases());
}
CloserUtil.close(walker);
////////////////////////////////////////////////////////////////////////
// Setup the outputs
////////////////////////////////////////////////////////////////////////
final VCFHeader inHeader = in.getFileHeader();
final VCFHeader outHeader = new VCFHeader(inHeader);
outHeader.setSequenceDictionary(walker.getSequenceDictionary());
final VariantContextWriter out =
new VariantContextWriterBuilder()
.setOption(Options.INDEX_ON_THE_FLY)
.setOutputFile(OUTPUT)
.setReferenceDictionary(walker.getSequenceDictionary())
.build();
out.writeHeader(outHeader);
final VariantContextWriter rejects =
new VariantContextWriterBuilder()
.setOutputFile(REJECT)
.unsetOption(Options.INDEX_ON_THE_FLY)
.build();
final VCFHeader rejectHeader = new VCFHeader(in.getFileHeader());
for (final VCFFilterHeaderLine line : FILTERS) rejectHeader.addMetaDataLine(line);
rejects.writeHeader(rejectHeader);
////////////////////////////////////////////////////////////////////////
// Read the input VCF, lift the records over and write to the sorting
// collection.
////////////////////////////////////////////////////////////////////////
long failedLiftover = 0, failedAlleleCheck = 0, total = 0;
logger.info("Lifting variants over and sorting.");
final SortingCollection<VariantContext> sorter =
SortingCollection.newInstance(
VariantContext.class,
new VCFRecordCodec(outHeader),
outHeader.getVCFRecordComparator(),
MAX_RECORDS_IN_RAM,
TMP_DIR);
ProgressLogger progress = new ProgressLogger(logger, 1000000, "read");
for (final VariantContext ctx : in) {
++total;
final Interval source =
new Interval(
ctx.getContig(),
ctx.getStart(),
ctx.getEnd(),
false,
ctx.getContig() + ":" + ctx.getStart() + "-" + ctx.getEnd());
final Interval target = liftOver.liftOver(source, 1.0);
if (target == null) {
rejects.add(new VariantContextBuilder(ctx).filter(FILTER_CANNOT_LIFTOVER).make());
failedLiftover++;
} else {
// Fix the alleles if we went from positive to negative strand
final List<Allele> alleles = new ArrayList<>();
for (final Allele oldAllele : ctx.getAlleles()) {
if (target.isPositiveStrand() || oldAllele.isSymbolic()) {
alleles.add(oldAllele);
} else {
alleles.add(
Allele.create(
SequenceUtil.reverseComplement(oldAllele.getBaseString()),
oldAllele.isReference()));
}
}
// Build the new variant context
final VariantContextBuilder builder =
new VariantContextBuilder(
ctx.getSource(), target.getContig(), target.getStart(), target.getEnd(), alleles);
builder.id(ctx.getID());
builder.attributes(ctx.getAttributes());
builder.genotypes(ctx.getGenotypes());
builder.filters(ctx.getFilters());
builder.log10PError(ctx.getLog10PError());
// Check that the reference allele still agrees with the reference sequence
boolean mismatchesReference = false;
for (final Allele allele : builder.getAlleles()) {
if (allele.isReference()) {
final byte[] ref = refSeqs.get(target.getContig());
final String refString =
StringUtil.bytesToString(ref, target.getStart() - 1, target.length());
if (!refString.equalsIgnoreCase(allele.getBaseString())) {
mismatchesReference = true;
}
break;
}
}
if (mismatchesReference) {
rejects.add(new VariantContextBuilder(ctx).filter(FILTER_MISMATCHING_REF_ALLELE).make());
failedAlleleCheck++;
} else {
sorter.add(builder.make());
}
}
progress.record(ctx.getContig(), ctx.getStart());
}
final NumberFormat pfmt = new DecimalFormat("0.0000%");
final String pct = pfmt.format((failedLiftover + failedAlleleCheck) / (double) total);
logger.info("Processed ", total, " variants.");
logger.info(Long.toString(failedLiftover), " variants failed to liftover.");
logger.info(
Long.toString(failedAlleleCheck),
" variants lifted over but had mismatching reference alleles after lift over.");
logger.info(pct, " of variants were not successfully lifted over and written to the output.");
rejects.close();
in.close();
////////////////////////////////////////////////////////////////////////
// Write the sorted outputs to the final output file
////////////////////////////////////////////////////////////////////////
sorter.doneAdding();
progress = new ProgressLogger(logger, 1000000, "written");
logger.info("Writing out sorted records to final VCF.");
for (final VariantContext ctx : sorter) {
out.add(ctx);
progress.record(ctx.getContig(), ctx.getStart());
}
out.close();
sorter.cleanup();
return null;
}
/**
* Analyze coverage distribution and validate read mates per interval and per sample
*
* <p>This tool is useful for diagnosing regions with bad coverage, mapping, or read mate pairs. It
* analyzes each sample independently and aggregates results over intervals of interest.
* Low-coverage regions can be identified by using e.g. FindCoveredIntervals with the -uncovered
* argument.
*
* <h3>Input</h3>
*
* <ul>
* <li>A reference file
* <li>one or more input BAMs
* <li>One or more intervals
* </ul>
*
* <h3>Output</h3>
*
* <p>A modified VCF detailing each interval by sample and information for each interval according
* to the thresholds used. Interval information includes GC Content, average interval depth,
* callable status among others. If you use the --missing option, you can get as a second output a
* intervals file with the loci that have missing data. This file can then be used as input to
* QualifyMissingIntervals for full qualification and interpretation of why the data is missing.
*
* <h3>Usage example</h3>
*
* <pre>
* java -jar GenomeAnalysisTK.jar
* -T DiagnoseTargets \
* -R reference.fasta \
* -I sample1.bam \
* -I sample2.bam \
* -I sample3.bam \
* -L intervals.interval_list \
* -o output.vcf
* </pre>
*
* @author Mauricio Carneiro, Roger Zurawicki
* @since 5/8/12
*/
@DocumentedGATKFeature(
groupName = HelpConstants.DOCS_CAT_QC,
extraDocs = {CommandLineGATK.class})
@By(value = DataSource.READS)
@PartitionBy(PartitionType.INTERVAL)
@Downsample(by = DownsampleType.NONE)
public class DiagnoseTargets extends LocusWalker<Long, Long> {
@Output(doc = "File to which interval statistics should be written")
private VariantContextWriter vcfWriter = null;
@ArgumentCollection private ThresHolder thresholds = new ThresHolder();
private Map<GenomeLoc, IntervalStratification> intervalMap =
null; // maps each interval => statistics
private PeekableIterator<GenomeLoc>
intervalListIterator; // an iterator to go over all the intervals provided as we traverse the
// genome
private Set<String> samples = null; // all the samples being processed
private static final Allele SYMBOLIC_ALLELE =
Allele.create("<DT>", false); // avoid creating the symbolic allele multiple times
private static final Allele UNCOVERED_ALLELE =
Allele.create(
"A", true); // avoid creating the 'fake' ref allele for uncovered intervals multiple times
private static final int INITIAL_HASH_SIZE =
50; // enough room for potential overlapping intervals plus recently finished intervals
@Override
public void initialize() {
super.initialize();
if (getToolkit().getIntervals() == null || getToolkit().getIntervals().isEmpty())
throw new UserException(
"This tool only works if you provide one or more intervals (use the -L argument). If you want to run whole genome, use -T DepthOfCoverage instead.");
intervalMap = new LinkedHashMap<>(INITIAL_HASH_SIZE);
intervalListIterator = new PeekableIterator<>(getToolkit().getIntervals().iterator());
// get all of the unique sample names for the VCF Header
samples = ReadUtils.getSAMFileSamples(getToolkit().getSAMFileHeader());
vcfWriter.writeHeader(new VCFHeader(getHeaderInfo(), samples));
// pre load all the statistics classes because it is costly to operate on the JVM and we only
// want to do it once.
loadAllPlugins(thresholds);
}
@Override
public Long map(
final RefMetaDataTracker tracker,
final ReferenceContext ref,
final AlignmentContext context) {
GenomeLoc refLocus = ref.getLocus();
// process and remove any intervals in the map that are don't overlap the current locus anymore
// and add all new intervals that may overlap this reference locus
addNewOverlappingIntervals(refLocus);
outputFinishedIntervals(refLocus, ref.getBase());
// at this point, all intervals in intervalMap overlap with this locus, so update all of them
for (IntervalStratification intervalStratification : intervalMap.values())
intervalStratification.addLocus(context, ref);
return 1L;
}
@Override
public Long reduceInit() {
return 0L;
}
/**
* Not sure what we are going to do here
*
* @param value result of the map.
* @param sum accumulator for the reduce.
* @return a long
*/
@Override
public Long reduce(Long value, Long sum) {
return sum + value;
}
/**
* Process all remaining intervals
*
* @param result number of loci processed by the walker
*/
@Override
public void onTraversalDone(final Long result) {
for (GenomeLoc interval : intervalMap.keySet())
outputStatsToVCF(intervalMap.get(interval), UNCOVERED_ALLELE);
GenomeLoc interval = intervalListIterator.peek();
while (interval != null) {
outputStatsToVCF(createIntervalStatistic(interval), UNCOVERED_ALLELE);
intervalListIterator.next();
interval = intervalListIterator.peek();
}
if (thresholds.missingTargets != null) {
thresholds.missingTargets.close();
}
}
/**
* Outputs all intervals that are behind the current reference locus
*
* @param refLocus the current reference locus
* @param refBase the reference allele
*/
private void outputFinishedIntervals(final GenomeLoc refLocus, final byte refBase) {
// output any intervals that were finished
final List<GenomeLoc> toRemove = new LinkedList<>();
for (GenomeLoc key : intervalMap.keySet()) {
if (key.isBefore(refLocus)) {
final IntervalStratification intervalStats = intervalMap.get(key);
outputStatsToVCF(intervalStats, Allele.create(refBase, true));
if (hasMissingLoci(intervalStats)) {
outputMissingInterval(intervalStats);
}
toRemove.add(key);
}
}
for (GenomeLoc key : toRemove) {
intervalMap.remove(key);
}
}
/**
* Adds all intervals that overlap the current reference locus to the intervalMap
*
* @param refLocus the current reference locus
*/
private void addNewOverlappingIntervals(final GenomeLoc refLocus) {
GenomeLoc interval = intervalListIterator.peek();
while (interval != null && !interval.isPast(refLocus)) {
intervalMap.put(interval, createIntervalStatistic(interval));
intervalListIterator.next();
interval = intervalListIterator.peek();
}
}
/**
* Takes the interval, finds it in the stash, prints it to the VCF
*
* @param stats The statistics of the interval
* @param refAllele the reference allele
*/
private void outputStatsToVCF(final IntervalStratification stats, final Allele refAllele) {
GenomeLoc interval = stats.getInterval();
final List<Allele> alleles = new ArrayList<>();
final Map<String, Object> attributes = new HashMap<>();
final ArrayList<Genotype> genotypes = new ArrayList<>();
for (String sample : samples) {
final GenotypeBuilder gb = new GenotypeBuilder(sample);
SampleStratification sampleStat = stats.getSampleStatistics(sample);
gb.attribute(
GATKVCFConstants.AVG_INTERVAL_DP_BY_SAMPLE_KEY,
sampleStat.averageCoverage(interval.size()));
gb.attribute(GATKVCFConstants.LOW_COVERAGE_LOCI, sampleStat.getNLowCoveredLoci());
gb.attribute(GATKVCFConstants.ZERO_COVERAGE_LOCI, sampleStat.getNUncoveredLoci());
gb.filters(statusToStrings(stats.getSampleStatistics(sample).callableStatuses(), false));
genotypes.add(gb.make());
}
alleles.add(refAllele);
alleles.add(SYMBOLIC_ALLELE);
VariantContextBuilder vcb =
new VariantContextBuilder(
"DiagnoseTargets",
interval.getContig(),
interval.getStart(),
interval.getStop(),
alleles);
vcb = vcb.log10PError(VariantContext.NO_LOG10_PERROR);
vcb.filters(new LinkedHashSet<>(statusToStrings(stats.callableStatuses(), true)));
attributes.put(VCFConstants.END_KEY, interval.getStop());
attributes.put(GATKVCFConstants.AVG_INTERVAL_DP_KEY, stats.averageCoverage(interval.size()));
attributes.put(GATKVCFConstants.INTERVAL_GC_CONTENT_KEY, stats.gcContent());
vcb = vcb.attributes(attributes);
vcb = vcb.genotypes(genotypes);
vcfWriter.add(vcb.make());
}
private boolean hasMissingStatuses(AbstractStratification stats) {
return !stats.callableStatuses().isEmpty();
}
private boolean hasMissingLoci(final IntervalStratification stats) {
return thresholds.missingTargets != null && hasMissingStatuses(stats);
}
private void outputMissingInterval(final IntervalStratification stats) {
final GenomeLoc interval = stats.getInterval();
final boolean missing[] = new boolean[interval.size()];
Arrays.fill(missing, true);
for (AbstractStratification sample : stats.getElements()) {
if (hasMissingStatuses(sample)) {
int pos = 0;
for (AbstractStratification locus : sample.getElements()) {
if (locus.callableStatuses().isEmpty()) {
missing[pos] = false;
}
pos++;
}
}
}
int start = -1;
boolean insideMissing = false;
for (int i = 0; i < missing.length; i++) {
if (missing[i] && !insideMissing) {
start = interval.getStart() + i;
insideMissing = true;
} else if (!missing[i] && insideMissing) {
final int stop = interval.getStart() + i - 1;
outputMissingInterval(interval.getContig(), start, stop);
insideMissing = false;
}
}
if (insideMissing) {
outputMissingInterval(interval.getContig(), start, interval.getStop());
}
}
private void outputMissingInterval(final String contig, final int start, final int stop) {
final PrintStream out = thresholds.missingTargets;
out.println(String.format("%s:%d-%d", contig, start, stop));
}
/**
* Function that process a set of statuses into strings
*
* @param statuses the set of statuses to be converted
* @return a matching set of strings
*/
private List<String> statusToStrings(
Iterable<CallableStatus> statuses, final boolean isInfoField) {
List<String> output = new LinkedList<>();
for (CallableStatus status : statuses)
if (isInfoField || status != CallableStatus.PASS) output.add(status.name());
return output;
}
private IntervalStratification createIntervalStatistic(GenomeLoc interval) {
return new IntervalStratification(samples, interval, thresholds);
}
protected static void loadAllPlugins(final ThresHolder thresholds) {
for (Class<?> stat : new PluginManager<LocusMetric>(LocusMetric.class).getPlugins()) {
try {
final LocusMetric stats = (LocusMetric) stat.newInstance();
stats.initialize(thresholds);
thresholds.locusMetricList.add(stats);
} catch (Exception e) {
throw new DynamicClassResolutionException(stat, e);
}
}
for (Class<?> stat : new PluginManager<SampleMetric>(SampleMetric.class).getPlugins()) {
try {
final SampleMetric stats = (SampleMetric) stat.newInstance();
stats.initialize(thresholds);
thresholds.sampleMetricList.add(stats);
} catch (Exception e) {
throw new DynamicClassResolutionException(stat, e);
}
}
for (Class<?> stat : new PluginManager<IntervalMetric>(IntervalMetric.class).getPlugins()) {
try {
final IntervalMetric stats = (IntervalMetric) stat.newInstance();
stats.initialize(thresholds);
thresholds.intervalMetricList.add(stats);
} catch (Exception e) {
throw new DynamicClassResolutionException(stat, e);
}
}
}
/**
* Gets the header lines for the VCF writer
*
* @return A set of VCF header lines
*/
private static Set<VCFHeaderLine> getHeaderInfo() {
Set<VCFHeaderLine> headerLines = new HashSet<>();
// INFO fields for overall data
headerLines.add(VCFStandardHeaderLines.getInfoLine(VCFConstants.END_KEY));
headerLines.add(GATKVCFHeaderLines.getInfoLine(GATKVCFConstants.AVG_INTERVAL_DP_KEY));
headerLines.add(GATKVCFHeaderLines.getInfoLine(GATKVCFConstants.INTERVAL_GC_CONTENT_KEY));
headerLines.add(
new VCFInfoHeaderLine(
"Diagnose Targets", 0, VCFHeaderLineType.Flag, "DiagnoseTargets mode"));
// FORMAT fields for each genotype
headerLines.add(VCFStandardHeaderLines.getFormatLine(VCFConstants.GENOTYPE_FILTER_KEY));
headerLines.add(
GATKVCFHeaderLines.getFormatLine(GATKVCFConstants.AVG_INTERVAL_DP_BY_SAMPLE_KEY));
headerLines.add(GATKVCFHeaderLines.getFormatLine(GATKVCFConstants.LOW_COVERAGE_LOCI));
headerLines.add(GATKVCFHeaderLines.getFormatLine(GATKVCFConstants.ZERO_COVERAGE_LOCI));
// FILTER fields
for (CallableStatus stat : CallableStatus.values())
headerLines.add(new VCFFilterHeaderLine(stat.name(), stat.description));
return headerLines;
}
}
/** * Helper class for those unit-test classes that test on implementations of SampleList. * * @author Valentin Ruano-Rubio <[email protected]> */ public class AlleleListUnitTester { private static final Random rnd = Utils.getRandomGenerator(); private static final RandomDNA rndDNA = new RandomDNA(rnd); /** * Test that the contents of an allele-list are the ones expected. * * <p> * * <p>This method perform various consistency check involving all the {@link * org.broadinstitute.gatk.utils.genotyper.AlleleList} interface methods. Therefore calling this * method is equivalent to a thorough check of the {@link * org.broadinstitute.gatk.utils.genotyper.AlleleList} aspect of the {@code actual} argument. * * @param actual the sample-list to assess. * @param expected the expected sample-list. * @throws IllegalArgumentException if {@code expected} is {@code null} or contains {@code null}s * which is an indication of an bug in the testing code. * @throws RuntimeException if there is some testing assertion exception which is an indication of * an actual bug the code that is been tested. */ public static <A extends Allele> void assertAlleleList( final AlleleList<A> actual, final List<A> expected) { if (expected == null) throw new IllegalArgumentException("the expected list cannot be null"); final Set<A> expectedAlleleSet = new HashSet<>(expected.size()); Assert.assertNotNull(actual); Assert.assertEquals(actual.alleleCount(), expected.size()); for (int i = 0; i < expected.size(); i++) { final A expectedAllele = expected.get(i); if (expectedAllele == null) throw new IllegalArgumentException("the expected sample cannot be null"); if (expectedAllele.equals(NEVER_USE_ALLELE)) throw new IllegalArgumentException("you cannot use the forbidden sample name"); if (expectedAlleleSet.contains(expected.get(i))) throw new IllegalArgumentException( "repeated allele in the expected list, this is a test bug"); final A actualAllele = actual.alleleAt(i); Assert.assertNotNull(actualAllele, "allele cannot be null"); Assert.assertFalse( expectedAlleleSet.contains(actualAllele), "repeated allele: " + actualAllele); Assert.assertEquals(actualAllele, expectedAllele, "wrong allele order; index = " + i); Assert.assertEquals(actual.alleleIndex(actualAllele), i, "allele index mismatch"); expectedAlleleSet.add(actualAllele); } Assert.assertEquals(actual.alleleIndex((A) NEVER_USE_ALLELE), -1); } /** Save to assume that this allele will never be used. */ private static final Allele NEVER_USE_ALLELE = Allele.create( new String("ACTGACTGACTGACTGACTGACTGACTGACTGGTCAGTCAGTCAGTCAGTCAGTCA").getBytes(), false); /** * Generate testing alleles. * * <p>Basically all are random alleles given the maximum allele length. * * <p>So with a low max-allele-length and high allele-count you can force repeats. * * @param alleleCount number of alleles to generate. * @param maxAlleleLength the maximum length of the allele in bases. * @throws RuntimeException if {@code alleleCount} is negative or {@code maxAlleleLength} is less * than 1. * @return never {@code null}. */ public static Allele[] generateRandomAlleles(final int alleleCount, final int maxAlleleLength) { if (maxAlleleLength < 1) throw new IllegalArgumentException("the max allele length cannot be less than 1"); final Allele[] result = new Allele[alleleCount]; for (int i = 0; i < alleleCount; i++) { final int alleleLength = rnd.nextInt(maxAlleleLength) + 1; result[i] = Allele.create(rndDNA.nextBases(alleleLength)); } return result; } /** * Generate testing alleles. * * <p>Basically all are random alleles given the maximum allele length. * * <p>So with a low max-allele-length and high allele-count you can force repeats. * * @param alleleCount number of alleles to generate. * @param maxAlleleLength the maximum length of the allele in bases. * @param skipIfRepeats throw an test-skip exception {@link SkipException} if the resulting * allele-list has repeats, thus is size is less than {@code alleleCount} * @throws RuntimeException if {@code alleleCount} is negative or {@code maxAlleleLength} is less * than 1. * @return never {@code null}. */ static AlleleList<Allele> alleleList( final int alleleCount, final int maxAlleleLength, final boolean skipIfRepeats) { final Allele[] alleles = AlleleListUnitTester.generateRandomAlleles(alleleCount, maxAlleleLength); if (alleleCount > 0) alleles[0] = Allele.create(alleles[0].getBases(), true); final AlleleList<Allele> alleleList = new IndexedAlleleList<>(alleles); if (skipIfRepeats && alleleList.alleleCount() != alleles.length) throw new SkipException("repeated alleles, should be infrequent"); return alleleList; } }
@Override
protected void doWork(VcfIterator r, VariantContextWriter w) throws IOException {
long nChanged = 0L;
final String TAG = "INDELFIXED";
VCFHeader header = r.getHeader();
VCFHeader h2 = new VCFHeader(header.getMetaDataInInputOrder(), header.getSampleNamesInOrder());
h2.addMetaDataLine(
new VCFInfoHeaderLine(TAG, 1, VCFHeaderLineType.String, "Fix Indels for @SolenaLS."));
w.writeHeader(h2);
final Pattern dna = Pattern.compile("[ATGCatgc]+");
while (r.hasNext()) {
VariantContext ctx = r.next();
VariantContextBuilder b = new VariantContextBuilder(ctx);
List<Allele> alleles = ctx.getAlternateAlleles();
if (alleles.size() != 1
|| !dna.matcher(ctx.getReference().getBaseString()).matches()
|| !dna.matcher(alleles.get(0).getBaseString()).matches()) {
w.add(ctx);
continue;
}
StringBuffer ref = new StringBuffer(ctx.getReference().getBaseString().toUpperCase());
StringBuffer alt = new StringBuffer(alleles.get(0).getBaseString().toUpperCase());
int start = ctx.getStart();
int end = ctx.getEnd();
boolean changed = false;
/** ** we trim on the right side *** */
// REF=TGCTGCGGGGGCCGCTGCGGGGG ALT=TGCTGCGGGGG
while (alt.length() > 1
&& alt.length() < ref.length()
&& ref.charAt(ref.length() - 1) == alt.charAt(alt.length() - 1)) {
changed = true;
ref.setLength(ref.length() - 1);
alt.deleteCharAt(alt.length() - 1);
end--;
}
// REF=TGCTGCGGGGG ALT= TGCTGCGGGGGCCGCTGCGGGGG
while (ref.length() > 1
&& alt.length() > ref.length()
&& ref.charAt(ref.length() - 1) == alt.charAt(alt.length() - 1)) {
changed = true;
ref.setLength(ref.length() - 1);
alt.deleteCharAt(alt.length() - 1);
end--;
}
/** ** we trim on the left side *** */
// REF=TGCTGCGGGGGCCGCTGCGGGGG ALT=TGCTGCGGGGG
while (alt.length() > 1 && alt.length() < ref.length() && ref.charAt(0) == alt.charAt(0)) {
changed = true;
ref.deleteCharAt(0);
alt.deleteCharAt(0);
start++;
}
// REF=TGCTGCGGGGG ALT= TGCTGCGGGGGCCGCTGCGGGGG
while (ref.length() > 1 && alt.length() > ref.length() && ref.charAt(0) == alt.charAt(0)) {
changed = true;
ref.deleteCharAt(0);
alt.deleteCharAt(0);
start++;
}
if (!changed) {
w.add(ctx);
continue;
}
/*
LOG.info(line);
LOG.info("ctx.getStart() "+ctx.getStart());
LOG.info("ctx.getEnd() "+ ctx.getEnd());
LOG.info("start " + start);
LOG.info("end "+end);
LOG.info("ref " + ref.toString());
LOG.info("alt "+alt.toString());
*/
Allele newRef = Allele.create(ref.toString(), true);
Allele newAlt = Allele.create(alt.toString(), false);
Allele newalleles[] = new Allele[] {newRef, newAlt};
b.attribute(
TAG,
ctx.getReference().getBaseString()
+ "|"
+ alleles.get(0).getBaseString()
+ "|"
+ ctx.getStart());
b.start(start);
b.stop(end);
b.alleles(Arrays.asList(newalleles));
nChanged++;
VariantContext ctx2 = b.make();
try {
w.add(ctx2);
} catch (TribbleException err) {
error(err, "Cannot convert new context:" + ctx2 + " old context:" + ctx);
w.add(ctx);
}
}
info("indels changed:" + nChanged);
}
