use of htsjdk.samtools.filter.SamRecordFilter in project gatk by broadinstitute.
the class CountingPairedFilter method doWork.
@Override
protected Object doWork() {
IOUtil.assertFileIsReadable(INPUT);
IOUtil.assertFileIsWritable(OUTPUT);
IOUtil.assertFileIsReadable(REFERENCE_SEQUENCE);
// Setup all the inputs
final ProgressLogger progress = new ProgressLogger(logger, 10000000, "Processed", "loci");
final ReferenceSequenceFileWalker refWalker = new ReferenceSequenceFileWalker(REFERENCE_SEQUENCE);
final SamReader in = SamReaderFactory.makeDefault().referenceSequence(REFERENCE_SEQUENCE).validationStringency(VALIDATION_STRINGENCY).open(INPUT);
// Load up the reference sequence and double check sequence dictionaries
if (!in.getFileHeader().getSequenceDictionary().isEmpty()) {
SequenceUtil.assertSequenceDictionariesEqual(in.getFileHeader().getSequenceDictionary(), refWalker.getSequenceDictionary());
}
final SamLocusIterator iterator = new SamLocusIterator(in);
final List<SamRecordFilter> filters = new ArrayList<>();
final CountingFilter dupeFilter = new CountingDuplicateFilter();
final CountingFilter mapqFilter = new CountingMapQFilter(MINIMUM_MAPPING_QUALITY);
final CountingPairedFilter pairFilter = new CountingPairedFilter();
filters.add(mapqFilter);
filters.add(dupeFilter);
filters.add(pairFilter);
// Not a counting filter because we never want to count reads twice
filters.add(new SecondaryAlignmentFilter());
iterator.setSamFilters(filters);
iterator.setEmitUncoveredLoci(true);
// Handled separately because we want to count bases
iterator.setMappingQualityScoreCutoff(0);
// Handled separately because we want to count bases
iterator.setQualityScoreCutoff(0);
iterator.setIncludeNonPfReads(false);
final int max = COVERAGE_CAP;
final long[] HistogramArray = new long[max + 1];
final long[] baseQHistogramArray = new long[Byte.MAX_VALUE];
final boolean usingStopAfter = STOP_AFTER > 0;
final long stopAfter = STOP_AFTER - 1;
long counter = 0;
long basesExcludedByBaseq = 0;
long basesExcludedByOverlap = 0;
long basesExcludedByCapping = 0;
// Loop through all the loci
while (iterator.hasNext()) {
final SamLocusIterator.LocusInfo info = iterator.next();
// Check that the reference is not N
final ReferenceSequence ref = refWalker.get(info.getSequenceIndex());
final byte base = ref.getBases()[info.getPosition() - 1];
if (base == 'N')
continue;
// Figure out the coverage while not counting overlapping reads twice, and excluding various things
final Set<String> readNames = new HashSet<>(info.getRecordAndOffsets().size());
int pileupSize = 0;
for (final SamLocusIterator.RecordAndOffset recs : info.getRecordAndOffsets()) {
if (recs.getBaseQuality() < MINIMUM_BASE_QUALITY) {
++basesExcludedByBaseq;
continue;
}
if (!readNames.add(recs.getRecord().getReadName())) {
++basesExcludedByOverlap;
continue;
}
pileupSize++;
if (pileupSize <= max) {
baseQHistogramArray[recs.getRecord().getBaseQualities()[recs.getOffset()]]++;
}
}
final int depth = Math.min(readNames.size(), max);
if (depth < readNames.size())
basesExcludedByCapping += readNames.size() - max;
HistogramArray[depth]++;
// Record progress and perhaps stop
progress.record(info.getSequenceName(), info.getPosition());
if (usingStopAfter && ++counter > stopAfter)
break;
}
// Construct and write the outputs
final Histogram<Integer> histo = new Histogram<>("coverage", "count");
for (int i = 0; i < HistogramArray.length; ++i) {
histo.increment(i, HistogramArray[i]);
}
// Construct and write the outputs
final Histogram<Integer> baseQHisto = new Histogram<>("value", "baseq_count");
for (int i = 0; i < baseQHistogramArray.length; ++i) {
baseQHisto.increment(i, baseQHistogramArray[i]);
}
final WgsMetrics metrics = generateWgsMetrics();
metrics.GENOME_TERRITORY = (long) histo.getSumOfValues();
metrics.MEAN_COVERAGE = histo.getMean();
metrics.SD_COVERAGE = histo.getStandardDeviation();
metrics.MEDIAN_COVERAGE = histo.getMedian();
metrics.MAD_COVERAGE = histo.getMedianAbsoluteDeviation();
final long basesExcludedByDupes = dupeFilter.getFilteredBases();
final long basesExcludedByMapq = mapqFilter.getFilteredBases();
final long basesExcludedByPairing = pairFilter.getFilteredBases();
final double total = histo.getSum();
final double totalWithExcludes = total + basesExcludedByDupes + basesExcludedByMapq + basesExcludedByPairing + basesExcludedByBaseq + basesExcludedByOverlap + basesExcludedByCapping;
metrics.PCT_EXC_DUPE = basesExcludedByDupes / totalWithExcludes;
metrics.PCT_EXC_MAPQ = basesExcludedByMapq / totalWithExcludes;
metrics.PCT_EXC_UNPAIRED = basesExcludedByPairing / totalWithExcludes;
metrics.PCT_EXC_BASEQ = basesExcludedByBaseq / totalWithExcludes;
metrics.PCT_EXC_OVERLAP = basesExcludedByOverlap / totalWithExcludes;
metrics.PCT_EXC_CAPPED = basesExcludedByCapping / totalWithExcludes;
metrics.PCT_EXC_TOTAL = (totalWithExcludes - total) / totalWithExcludes;
metrics.PCT_5X = MathUtils.sum(HistogramArray, 5, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_10X = MathUtils.sum(HistogramArray, 10, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_15X = MathUtils.sum(HistogramArray, 15, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_20X = MathUtils.sum(HistogramArray, 20, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_25X = MathUtils.sum(HistogramArray, 25, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_30X = MathUtils.sum(HistogramArray, 30, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_40X = MathUtils.sum(HistogramArray, 40, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_50X = MathUtils.sum(HistogramArray, 50, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_60X = MathUtils.sum(HistogramArray, 60, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_70X = MathUtils.sum(HistogramArray, 70, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_80X = MathUtils.sum(HistogramArray, 80, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_90X = MathUtils.sum(HistogramArray, 90, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
metrics.PCT_100X = MathUtils.sum(HistogramArray, 100, HistogramArray.length) / (double) metrics.GENOME_TERRITORY;
final MetricsFile<WgsMetrics, Integer> out = getMetricsFile();
out.addMetric(metrics);
out.addHistogram(histo);
if (INCLUDE_BQ_HISTOGRAM) {
out.addHistogram(baseQHisto);
}
out.write(OUTPUT);
return null;
}
use of htsjdk.samtools.filter.SamRecordFilter in project gatk-protected by broadinstitute.
the class AllelicCountCollector method collect.
/**
* Returns an {@link AllelicCountCollection} based on the pileup at sites (specified by an interval list)
* in a sorted BAM file. Reads and bases below the specified mapping quality and base quality, respectively,
* are filtered out of the pileup. The alt count is defined as the total count minus the ref count, and the
* alt nucleotide is defined as the non-ref base with the highest count, with ties broken by the order of the
* bases in {@link AllelicCountCollector#BASES}.
* @param bamFile sorted BAM file
* @param siteIntervals interval list of sites
* @param minMappingQuality minimum mapping quality required for reads to be included in pileup
* @param minBaseQuality minimum base quality required for bases to be included in pileup
* @return AllelicCountCollection of ref/alt counts at sites in BAM file
*/
public AllelicCountCollection collect(final File bamFile, final IntervalList siteIntervals, final int minMappingQuality, final int minBaseQuality) {
try (final SamReader reader = readerFactory.open(bamFile)) {
ParamUtils.isPositiveOrZero(minMappingQuality, "Minimum mapping quality must be nonnegative.");
ParamUtils.isPositiveOrZero(minBaseQuality, "Minimum base quality must be nonnegative.");
if (reader.getFileHeader().getSortOrder() != SAMFileHeader.SortOrder.coordinate) {
throw new UserException.BadInput("BAM file " + bamFile.toString() + " must be coordinate sorted.");
}
final int numberOfSites = siteIntervals.size();
final boolean useIndex = numberOfSites < MAX_INTERVALS_FOR_INDEX;
final SamLocusIterator locusIterator = new SamLocusIterator(reader, siteIntervals, useIndex);
//set read and locus filters [note: read counts match IGV, but off by a few from pysam.mpileup]
final List<SamRecordFilter> samFilters = Arrays.asList(new NotPrimaryAlignmentFilter(), new DuplicateReadFilter());
locusIterator.setSamFilters(samFilters);
locusIterator.setEmitUncoveredLoci(true);
locusIterator.setIncludeNonPfReads(false);
locusIterator.setMappingQualityScoreCutoff(minMappingQuality);
locusIterator.setQualityScoreCutoff(minBaseQuality);
logger.info("Examining " + numberOfSites + " sites in total...");
int locusCount = 0;
final AllelicCountCollection counts = new AllelicCountCollection();
for (final SamLocusIterator.LocusInfo locus : locusIterator) {
if (locusCount % NUMBER_OF_SITES_PER_LOGGED_STATUS_UPDATE == 0) {
logger.info("Examined " + locusCount + " sites.");
}
locusCount++;
final Nucleotide refBase = Nucleotide.valueOf(referenceWalker.get(locus.getSequenceIndex()).getBases()[locus.getPosition() - 1]);
if (!BASES.contains(refBase)) {
logger.warn(String.format("The reference position at %d has an unknown base call (value: %s). Skipping...", locus.getPosition(), refBase.toString()));
continue;
}
final Nucleotide.Counter baseCounts = getPileupBaseCounts(locus);
//only include total ACGT counts in binomial test (exclude N, etc.)
final int totalBaseCount = BASES.stream().mapToInt(b -> (int) baseCounts.get(b)).sum();
final int refReadCount = (int) baseCounts.get(refBase);
//we take alt = total - ref instead of the actual alt count
final int altReadCount = totalBaseCount - refReadCount;
final Nucleotide altBase = inferAltFromPileupBaseCounts(baseCounts, refBase);
counts.add(new AllelicCount(new SimpleInterval(locus.getSequenceName(), locus.getPosition(), locus.getPosition()), refReadCount, altReadCount, refBase, altBase));
}
logger.info(locusCount + " sites out of " + numberOfSites + " total sites were examined.");
return counts;
} catch (final IOException | SAMFormatException e) {
throw new UserException("Unable to collect allelic counts from " + bamFile);
}
}
use of htsjdk.samtools.filter.SamRecordFilter in project gatk by broadinstitute.
the class BayesianHetPulldownCalculator method getSamLocusIteratorWithDefaultFilters.
/**
* Returns a {@link SamLocusIterator} object for a given {@link SamReader} and {@link IntervalList} with filters
* on minimum base quality and minimum mapping quality
*
* @param samReader a SamReader object
* @return a SamLocusIterator object
*/
private SamLocusIterator getSamLocusIteratorWithDefaultFilters(final SamReader samReader) {
final SamLocusIterator locusIterator = new SamLocusIterator(samReader, snpIntervals, false);
/* set read and locus filters */
final List<SamRecordFilter> samFilters = Arrays.asList(new NotPrimaryAlignmentFilter(), new DuplicateReadFilter());
locusIterator.setSamFilters(samFilters);
locusIterator.setEmitUncoveredLoci(false);
locusIterator.setIncludeNonPfReads(false);
locusIterator.setMappingQualityScoreCutoff(minMappingQuality);
locusIterator.setQualityScoreCutoff(minBaseQuality);
return locusIterator;
}
use of htsjdk.samtools.filter.SamRecordFilter in project gatk by broadinstitute.
the class HetPulldownCalculator method getHetPulldown.
/**
* For a normal or tumor sample, returns a data structure giving (intervals, reference counts, alternate counts),
* where intervals give positions of likely heterozygous SNP sites.
*
* <p>
* For a normal sample:
* <ul>
* The IntervalList snpIntervals gives common SNP sites in 1-based format.
* </ul>
* <ul>
* The p-value threshold must be specified for a two-sided binomial test,
* which is used to determine SNP sites from snpIntervals that are
* compatible with a heterozygous SNP, given the sample. Only these sites are output.
* </ul>
* </p>
* <p>
* For a tumor sample:
* <ul>
* The IntervalList snpIntervals gives heterozygous SNP sites likely to be present in the normal sample.
* This should be from {@link HetPulldownCalculator#getNormal} in 1-based format.
* Only these sites are output.
* </ul>
* </p>
* @param bamFile sorted BAM file for sample
* @param snpIntervals IntervalList of SNP sites
* @param sampleType flag indicating type of sample (SampleType.NORMAL or SampleType.TUMOR)
* (determines whether to perform binomial test)
* @param pvalThreshold p-value threshold for two-sided binomial test, used for normal sample
* @param minimumRawReads minimum number of total reads that must be present at a het site
* @return Pulldown of heterozygous SNP sites in 1-based format
*/
private Pulldown getHetPulldown(final File bamFile, final IntervalList snpIntervals, final SampleType sampleType, final double pvalThreshold, final int minimumRawReads) {
try (final SamReader bamReader = SamReaderFactory.makeDefault().validationStringency(validationStringency).referenceSequence(refFile).open(bamFile);
final ReferenceSequenceFileWalker refWalker = new ReferenceSequenceFileWalker(refFile)) {
if (bamReader.getFileHeader().getSortOrder() != SAMFileHeader.SortOrder.coordinate) {
throw new UserException.BadInput("BAM file " + bamFile.toString() + " must be coordinate sorted.");
}
final Pulldown hetPulldown = new Pulldown(bamReader.getFileHeader());
final int totalNumberOfSNPs = snpIntervals.size();
final SamLocusIterator locusIterator = new SamLocusIterator(bamReader, snpIntervals, totalNumberOfSNPs < MAX_INTERVALS_FOR_INDEX);
//set read and locus filters [note: read counts match IGV, but off by a few from pysam.mpileup]
final List<SamRecordFilter> samFilters = Arrays.asList(new NotPrimaryAlignmentFilter(), new DuplicateReadFilter());
locusIterator.setSamFilters(samFilters);
locusIterator.setEmitUncoveredLoci(false);
locusIterator.setIncludeNonPfReads(false);
locusIterator.setMappingQualityScoreCutoff(minMappingQuality);
locusIterator.setQualityScoreCutoff(minBaseQuality);
logger.info("Examining " + totalNumberOfSNPs + " sites in total...");
int locusCount = 0;
for (final SamLocusIterator.LocusInfo locus : locusIterator) {
if (locusCount % NUMBER_OF_SITES_PER_LOGGED_STATUS_UPDATE == 0) {
logger.info("Examined " + locusCount + " covered sites.");
}
locusCount++;
//include N, etc. reads here
final int totalReadCount = locus.getRecordAndOffsets().size();
if (totalReadCount < minimumRawReads) {
continue;
}
final Nucleotide.Counter baseCounts = getPileupBaseCounts(locus);
//only include total ACGT counts in binomial test (exclude N, etc.)
final int totalBaseCount = Arrays.stream(BASES).mapToInt(b -> (int) baseCounts.get(b)).sum();
if (sampleType == SampleType.NORMAL && !isPileupHetCompatible(baseCounts, totalBaseCount, pvalThreshold)) {
continue;
}
final Nucleotide refBase = Nucleotide.valueOf(refWalker.get(locus.getSequenceIndex()).getBases()[locus.getPosition() - 1]);
final int refReadCount = (int) baseCounts.get(refBase);
final int altReadCount = totalBaseCount - refReadCount;
hetPulldown.add(new AllelicCount(new SimpleInterval(locus.getSequenceName(), locus.getPosition(), locus.getPosition()), refReadCount, altReadCount));
}
logger.info(locusCount + " covered sites out of " + totalNumberOfSNPs + " total sites were examined.");
return hetPulldown;
} catch (final IOException | SAMFormatException e) {
throw new UserException(e.getMessage());
}
}
use of htsjdk.samtools.filter.SamRecordFilter in project ASCIIGenome by dariober.
the class TrackPileupTest method canFilterReadsSamtools.
@Test
public void canFilterReadsSamtools() throws InvalidGenomicCoordsException, IOException, ClassNotFoundException, InvalidRecordException, SQLException, InvalidColourException {
GenomicCoords gc = new GenomicCoords("chr7:5566778", 80, null, null);
TrackPileup tr = new TrackPileup("test_data/ds051.short.bam", gc);
tr.setNoFormat(true);
// Before filtering
assertTrue(tr.getTitle().contains("22.0"));
List<SamRecordFilter> samRecordFilter = new ArrayList<SamRecordFilter>();
samRecordFilter.add(new MappingQualityFilter(51));
tr.setSamRecordFilter(samRecordFilter);
assertEquals("", tr.printToScreen().trim());
samRecordFilter = new ArrayList<SamRecordFilter>();
samRecordFilter.add(new MappingQualityFilter(11));
tr.setSamRecordFilter(samRecordFilter);
assertTrue(tr.getTitle().contains("17.0"));
}
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