309 lines
13 KiB
Java
Executable File
309 lines
13 KiB
Java
Executable File
/*
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* Copyright (c) 2009 The Broad Institute
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*
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* Permission is hereby granted, free of charge, to any person
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* obtaining a copy of this software and associated documentation
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* files (the "Software"), to deal in the Software without
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* restriction, including without limitation the rights to use,
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* copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following
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* conditions:
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*
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* The above copyright notice and this permission notice shall be
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* included in all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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* HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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* WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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* OTHER DEALINGS IN THE SOFTWARE.
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*/
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package org.broadinstitute.sting.gatk.traversals;
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import net.sf.picard.filter.FilteringIterator;
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import net.sf.picard.filter.SamRecordFilter;
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import net.sf.samtools.SAMRecord;
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import org.apache.log4j.Logger;
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import org.broadinstitute.sting.gatk.contexts.AlignmentContext;
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import org.broadinstitute.sting.gatk.datasources.providers.ReadView;
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import org.broadinstitute.sting.gatk.datasources.providers.ShardDataProvider;
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import org.broadinstitute.sting.gatk.datasources.shards.ReadShard;
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import org.broadinstitute.sting.gatk.datasources.shards.Shard;
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import org.broadinstitute.sting.gatk.iterators.PushbackIterator;
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import org.broadinstitute.sting.gatk.walkers.DuplicateWalker;
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import org.broadinstitute.sting.gatk.walkers.Walker;
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import org.broadinstitute.sting.utils.GenomeLoc;
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import org.broadinstitute.sting.utils.GenomeLocParser;
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import org.broadinstitute.sting.utils.Pair;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.Iterator;
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import java.util.List;
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/**
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* @author Mark DePristo
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* @version 0.1
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* <p/>
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* Class TraverseDuplicates
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* <p/>
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* This class handles traversing lists of duplicate reads in the new shardable style
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*/
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public class TraverseDuplicates extends TraversalEngine {
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/** our log, which we want to capture anything from this class */
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protected static Logger logger = Logger.getLogger(TraverseDuplicates.class);
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/** descriptor of the type */
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private static final String DUPS_STRING = "dups";
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private final boolean DEBUG = false;
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private List<SAMRecord> readsAtLoc(final SAMRecord read, PushbackIterator<SAMRecord> iter) {
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GenomeLoc site = GenomeLocParser.createGenomeLoc(read);
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ArrayList<SAMRecord> l = new ArrayList<SAMRecord>();
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l.add(read);
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for (SAMRecord read2 : iter) {
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GenomeLoc site2 = GenomeLocParser.createGenomeLoc(read2);
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// the next read starts too late
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if (site2.getStart() != site.getStart()) {
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//System.out.printf("site = %s, site2 = %s%n", site, site2);
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iter.pushback(read2);
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break;
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} else {
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//System.out.printf("Read is a duplicate: %s%n", read.format());
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l.add(read2);
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}
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}
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return l;
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}
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protected Pair<List<SAMRecord>, List<SAMRecord>> splitDuplicates(List<SAMRecord> reads) {
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List<SAMRecord> uniques = new ArrayList<SAMRecord>();
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List<SAMRecord> dups = new ArrayList<SAMRecord>();
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// find the first duplicate
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SAMRecord key = null;
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for (SAMRecord read : reads) {
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if (read.getDuplicateReadFlag()) {
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// this is our key
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key = read;
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if (DEBUG) logger.debug(String.format("Key %s is a duplicate", read.getReadName()));
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break;
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}
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}
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// At this point, there are two possibilities, we have found at least one dup or not
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// if it's a dup, add it to the dups list, otherwise add it to the uniques list
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if (key != null) {
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final GenomeLoc keyLoc = GenomeLocParser.createGenomeLoc(key);
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final GenomeLoc keyMateLoc = (!key.getReadPairedFlag()) ? null :
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GenomeLocParser.createGenomeLoc(key.getMateReferenceIndex(), key.getMateAlignmentStart(), key.getMateAlignmentStart());
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for (SAMRecord read : reads) {
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final GenomeLoc readLoc = GenomeLocParser.createGenomeLoc(read);
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final GenomeLoc readMateLoc = (!key.getReadPairedFlag()) ? null :
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GenomeLocParser.createGenomeLoc(read.getMateReferenceIndex(), read.getMateAlignmentStart(), read.getMateAlignmentStart());
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if (DEBUG)
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logger.debug(String.format("Examining reads at %s vs. %s at %s / %s vs. %s / %s%n", key.getReadName(), read.getReadName(), keyLoc, keyMateLoc, readLoc, readMateLoc));
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// read and key start at the same place, and either the this read and the key
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// share a mate location or the read is flagged as a duplicate
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if (readLoc.compareTo(keyLoc) == 0 ||
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read.getDuplicateReadFlag()) {
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if ((readMateLoc != null && keyMateLoc != null && readMateLoc.compareTo(keyMateLoc) == 0) ||
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(readMateLoc == null && keyMateLoc == null)) {
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// we are at the same position as the dup and have the same mat pos, it's a dup
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if (DEBUG) logger.debug(String.format(" => Adding read to dups list: %s%n", read));
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dups.add(read);
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} else {
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uniques.add(read);
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}
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} else {
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uniques.add(read);
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}
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}
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} else {
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uniques = reads;
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}
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return new Pair<List<SAMRecord>, List<SAMRecord>>(uniques, dups);
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}
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/**
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* Traverse by reads, given the data and the walker
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*
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* @param sum of type T, the return from the walker
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* @param <M> the generic type
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* @param <T> the return type of the reduce function
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* @param dupWalker our duplicates walker
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* @param readIter our iterator
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*
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* @return the reduce type, T, the final product of all the reduce calls
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*/
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private <M, T> T actuallyTraverse(DuplicateWalker<M, T> dupWalker,
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Iterator<SAMRecord> readIter,
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T sum) {
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/**
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* while we still have more reads:
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* ok, here's the idea. We get all the reads that start at the same position in the genome
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* We then split the list of reads into sublists of reads:
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* -> those with the same mate pair position, for paired reads
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* -> those flagged as unpaired and duplicated but having the same start and end and
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*/
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PushbackIterator<SAMRecord> iter = new PushbackIterator<SAMRecord>(readIter);
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for (SAMRecord read : iter) {
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// get the genome loc from the read
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GenomeLoc site = GenomeLocParser.createGenomeLoc(read);
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List<SAMRecord> reads = readsAtLoc(read, iter);
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Pair<List<SAMRecord>, List<SAMRecord>> split = splitDuplicates(reads);
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List<SAMRecord> uniqueReads = split.getFirst();
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List<SAMRecord> duplicateReads = split.getSecond();
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logger.debug(String.format("*** TraverseDuplicates.traverse at %s with %d reads has %d unique and %d duplicate reads",
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site, reads.size(), uniqueReads.size(), duplicateReads.size()));
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if (reads.size() != uniqueReads.size() + duplicateReads.size())
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throw new RuntimeException(String.format("Bug occurred spliting reads [N=%d] at loc %s into unique [N=%d] and duplicates [N=%d], sizes don't match",
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reads.size(), site.toString(), uniqueReads.size(), duplicateReads.size()));
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// Jump forward in the reference to this locus location
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AlignmentContext locus = new AlignmentContext(site, duplicateReads, Arrays.asList(0));
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// update the number of duplicate sets we've seen
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TraversalStatistics.nRecords++;
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// we still have to fix the locus context provider to take care of this problem with > 1 length contexts
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// AlignmentContext locus = locusProvider.getLocusContext(site);
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byte[] refBases = new byte[0];
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if (dupWalker.mapUniqueReadsTooP()) {
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// Send each unique read to the map function
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for (SAMRecord unique : uniqueReads) {
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List<SAMRecord> l = Arrays.asList(unique);
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sum = mapOne(dupWalker, uniqueReads, l, site, refBases, locus, sum);
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}
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}
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if (duplicateReads.size() > 0)
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sum = mapOne(dupWalker, uniqueReads, duplicateReads, site, refBases, locus, sum);
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printProgress(DUPS_STRING, site);
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if (this.maximumIterations > 0 && TraversalStatistics.nRecords > this.maximumIterations) {
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logger.warn(String.format(("Maximum number of duplicate sets encountered, terminating traversal " + TraversalStatistics.nRecords)));
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break;
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}
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}
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return sum;
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}
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/**
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* Class to filter out un-handle-able reads from the stream. We currently are skipping
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* unmapped reads, non-primary reads, unaligned reads, and duplicate reads.
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*/
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public static class duplicateStreamFilterFunc implements SamRecordFilter {
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SAMRecord lastRead = null;
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public boolean filterOut(SAMRecord rec) {
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boolean result = false;
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if (rec.getReadUnmappedFlag()) {
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TraversalStatistics.nUnmappedReads++;
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result = true;
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} else if (rec.getNotPrimaryAlignmentFlag()) {
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TraversalStatistics.nNotPrimary++;
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result = true;
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} else if (rec.getAlignmentStart() == SAMRecord.NO_ALIGNMENT_START) {
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TraversalStatistics.nBadAlignments++;
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result = true;
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} else {
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result = false;
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}
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if (result) {
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TraversalStatistics.nSkippedReads++;
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//System.out.printf(" [filter] %s => %b %s", rec.getReadName(), result, why);
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} else {
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TraversalStatistics.nReads++;
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}
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return result;
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}
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}
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public <M, T> T mapOne(DuplicateWalker<M, T> dupWalker,
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List<SAMRecord> uniqueReads,
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List<SAMRecord> duplicateReads,
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GenomeLoc site,
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byte[] refBases,
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AlignmentContext locus,
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T sum) {
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final boolean keepMeP = dupWalker.filter(site, refBases, locus, uniqueReads, duplicateReads);
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if (keepMeP) {
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M x = dupWalker.map(site, refBases, locus, uniqueReads, duplicateReads);
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sum = dupWalker.reduce(x, sum);
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}
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return sum;
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}
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// --------------------------------------------------------------------------------------------------------------
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//
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// new style interface to the system
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//
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// --------------------------------------------------------------------------------------------------------------
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/**
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* Traverse by reads, given the data and the walker
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*
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* @param walker the walker to execute over
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* @param shard the shard of data to feed the walker
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* @param sum of type T, the return from the walker
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* @param <M> the generic type
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* @param <T> the return type of the reduce function
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*
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* @return the result type T, the product of all the reduce calls
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*/
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public <M, T> T traverse(Walker<M, T> walker,
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Shard shard,
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ShardDataProvider dataProvider,
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T sum) {
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logger.debug(String.format("TraverseDuplicates.traverse Genomic interval is %s", ((ReadShard) shard).getSize()));
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if (!(walker instanceof DuplicateWalker))
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throw new IllegalArgumentException("Walker isn't a duplicate walker!");
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DuplicateWalker<M, T> dupWalker = (DuplicateWalker<M, T>) walker;
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// while we still have more reads
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// ok, here's the idea. We get all the reads that start at the same position in the genome
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// We then split the list of reads into sublists of reads:
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// -> those with the same mate pair position, for paired reads
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// -> those flagged as unpaired and duplicated but having the same start and end and
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FilteringIterator filterIter = new FilteringIterator(new ReadView(dataProvider).iterator(), new duplicateStreamFilterFunc());
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PushbackIterator<SAMRecord> iter = new PushbackIterator<SAMRecord>(filterIter);
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return actuallyTraverse(dupWalker, iter, sum);
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}
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/**
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* Temporary override of printOnTraversalDone.
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* TODO: Add some sort of TE.getName() function once all TraversalEngines are ported.
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*
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* @param sum Result of the computation.
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* @param <T> Type of the result.
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*/
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public <T> void printOnTraversalDone(T sum) {
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printOnTraversalDone(DUPS_STRING, sum);
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}
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} |