1. Merged CoverageHistogram into DepthOfCoverageWalker
2. Fixed bug in histogram calculation for small intervals 3. Better output in DoCWalker 4. Comments added to code git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2245 348d0f76-0448-11de-a6fe-93d51630548a
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@ -60,20 +60,37 @@ public class DepthOfCoverageWalker extends LocusWalker<DepthOfCoverageWalker.DoC
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@Argument(fullName="bySample", shortName="bySample", doc="List read depths for each sample")
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protected boolean bySample = false;
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@Argument(fullName="printHistogram", shortName="histogram", doc="Print a histogram of the coverage")
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protected boolean printHistogram = false;
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// keep track of the read group and sample names
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private TreeSet<String> readGroupNames = new TreeSet<String>();
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private TreeSet<String> sampleNames = new TreeSet<String>();
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// keep track of the histogram data
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private ExpandingArrayList<Integer> coverageHist = null;
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private int maxDepth = 0;
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private int totalLoci = 0;
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// we want to see reads with deletions
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public boolean includeReadsWithDeletionAtLoci() { return true; }
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public void initialize() {
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// initialize histogram array
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if ( printHistogram ) {
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coverageHist = new ExpandingArrayList<Integer>();
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}
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// initialize read group names from BAM header
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if ( byReadGroup ) {
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List<SAMReadGroupRecord> readGroups = this.getToolkit().getSAMFileHeader().getReadGroups();
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for ( SAMReadGroupRecord record : readGroups )
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readGroupNames.add(record.getReadGroupId());
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}
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// initialize sample names from BAM header
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if ( bySample ) {
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List<SAMReadGroupRecord> readGroups = this.getToolkit().getSAMFileHeader().getReadGroups();
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for ( SAMReadGroupRecord record : readGroups ) {
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@ -83,6 +100,8 @@ public class DepthOfCoverageWalker extends LocusWalker<DepthOfCoverageWalker.DoC
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}
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}
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// build and print the per-locus header
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out.println("\nPER_LOCUS_COVERAGE_SECTION");
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StringBuilder header = new StringBuilder("location\ttotal_coverage\tcoverage_without_deletions");
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if ( excludeMAPQBelowThis > 0 ) {
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header.append("\tcoverage_atleast_MQ");
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@ -105,6 +124,8 @@ public class DepthOfCoverageWalker extends LocusWalker<DepthOfCoverageWalker.DoC
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public DoCInfo map(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context) {
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// fill in and print all of the per-locus coverage data, then return it to reduce
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ReadBackedPileup pileup = context.getPileup();
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DoCInfo info = new DoCInfo();
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@ -141,6 +162,10 @@ public class DepthOfCoverageWalker extends LocusWalker<DepthOfCoverageWalker.DoC
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if ( excludeMAPQBelowThis > 0 )
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info.numBadMQReads = nBadMAPQReads;
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// if we need to print the histogram, fill in the data
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if ( printHistogram )
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incCov(info.totalCoverage);
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printDoCInfo(context.getLocation(), info, false);
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return info;
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@ -153,6 +178,9 @@ public class DepthOfCoverageWalker extends LocusWalker<DepthOfCoverageWalker.DoC
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public DoCInfo reduceInit() { return new DoCInfo(); }
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public DoCInfo reduce(DoCInfo value, DoCInfo sum) {
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// combine all of the per-locus data for a given interval
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sum.totalCoverage += value.totalCoverage;
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sum.numDeletions += value.numDeletions;
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sum.numBadMQReads += value.numBadMQReads;
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@ -178,7 +206,10 @@ public class DepthOfCoverageWalker extends LocusWalker<DepthOfCoverageWalker.DoC
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@Override
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public void onTraversalDone(List<Pair<GenomeLoc, DoCInfo>> results) {
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StringBuilder header = new StringBuilder("\nlocation\ttotal_coverage\taverage_coverage\tcoverage_without_deletions\taverage_coverage_without_deletions");
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// build and print the per-interval header
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out.println("\n\nPER_INTERVAL_COVERAGE_SECTION");
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StringBuilder header = new StringBuilder("location\ttotal_coverage\taverage_coverage\tcoverage_without_deletions\taverage_coverage_without_deletions");
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if ( excludeMAPQBelowThis > 0 ) {
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header.append("\tcoverage_atleast_MQ");
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header.append(excludeMAPQBelowThis);
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@ -203,8 +234,77 @@ public class DepthOfCoverageWalker extends LocusWalker<DepthOfCoverageWalker.DoC
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}
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out.println(header.toString());
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// print all of the individual per-interval coverage data
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for ( Pair<GenomeLoc, DoCInfo> result : results )
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printDoCInfo(result.first, result.second, true);
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// if we need to print the histogram, do so now
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if ( printHistogram )
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printHisto();
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}
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private void incCov(int depth) {
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int c = coverageHist.expandingGet(depth, 0);
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coverageHist.set(depth, c + 1);
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if ( depth > maxDepth )
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maxDepth = depth;
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totalLoci++;
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}
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private int getCov(int depth) {
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return coverageHist.get(depth);
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}
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private void printHisto() {
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// sanity check
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if ( totalLoci == 0 )
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return;
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// Code for calculting std devs adapted from Michael Melgar's python script
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// Find the maximum extent of 'good' data
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// First, find the mode
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long maxValue = getCov(1); // ignore doc=0
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int mode = 1;
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for (int i = 2; i <= maxDepth; i++) {
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if ( getCov(i) > maxValue ) {
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maxValue = getCov(i);
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mode = i;
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}
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}
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// now, procede to find end of good Gaussian fit
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long dist = (long)Math.pow(10, 9);
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while ( Math.abs(getCov(mode) - getCov(1)) < dist && mode < maxDepth )
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dist = Math.abs(getCov(mode++) - getCov(1));
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int maxGoodDepth = Math.min(mode + 1, maxDepth);
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// calculate the mean of the good region
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long totalGoodSites = 0, totalGoodDepth = 0;
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for (int i = 1; i <= maxGoodDepth; i++) { // ignore doc=0
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totalGoodSites += getCov(i);
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totalGoodDepth += i * getCov(i);
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}
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double meanGoodDepth = (double)totalGoodDepth / (double)totalGoodSites;
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// calculate the variance and standard deviation of the good region
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double var = 0.0;
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for (int i = 1; i <= maxGoodDepth; i++) { // ignore doc=0
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var += getCov(i) * Math.pow(meanGoodDepth - (double)i, 2);
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}
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double stdev = Math.sqrt(var / (double)totalGoodSites);
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// print
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out.println("\n\nHISTOGRAM_SECTION");
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out.printf("# sites within Gaussian fit : mean:%f num_sites:%d std_dev:%f%n", meanGoodDepth, totalGoodSites, stdev);
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for (int i = 1; i <= 5; i++)
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out.printf("# Gaussian mean + %d Std Dev : %f%n", i, (meanGoodDepth + i*stdev));
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out.println("\ndepth count freq(percent)");
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for (int i = 0; i <= maxDepth; i++)
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out.printf("%d %d %f\n", i, getCov(i), (100.0*getCov(i)) / (double)totalLoci);
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}
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private void printDoCInfo(GenomeLoc loc, DoCInfo info, boolean printAverageCoverage) {
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@ -1,126 +0,0 @@
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package org.broadinstitute.sting.playground.gatk.walkers;
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import org.broadinstitute.sting.gatk.contexts.AlignmentContext;
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import org.broadinstitute.sting.gatk.contexts.ReferenceContext;
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import org.broadinstitute.sting.gatk.refdata.RefMetaDataTracker;
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import org.broadinstitute.sting.gatk.walkers.LocusWalker;
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import org.broadinstitute.sting.gatk.walkers.By;
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import org.broadinstitute.sting.gatk.walkers.DataSource;
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import org.broadinstitute.sting.utils.ExpandingArrayList;
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import java.util.*;
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// Plot a histogram of depth of coverage
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// j.maguire 6-11-2009
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@By(DataSource.REFERENCE)
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public class CoverageHistogram extends LocusWalker<Integer,Integer>
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{
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//@Argument(fullName="start", shortName="start", required=false, doc="start") public Integer START = 0;
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// Private state.
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//long[] coverage_hist;
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ExpandingArrayList<Integer> coverage_hist = new ExpandingArrayList<Integer>();
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int max_depth = 0;
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long sum_coverage = 0;
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long num_sites = 0;
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/////////
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// Walker Interface Functions
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public void initialize()
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{
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//coverage_hist = new long[1000000];
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//Arrays.fill(coverage_hist, 0);
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}
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private void incCov(int depth) {
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int c = coverage_hist.expandingGet(depth, 0);
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coverage_hist.set(depth, c + 1);
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}
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private int getCov(int depth) {
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return coverage_hist.get(depth);
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}
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public Integer map(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context)
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{
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if (ref.getBase() == 'N') { return null; }
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int depth = context.getReads().size();
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incCov(depth);
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if (depth > max_depth) { max_depth = depth; }
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sum_coverage += depth;
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num_sites += 1;
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return 0;
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}
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public void onTraversalDone(Integer sum)
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{
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double mean_coverage = (double)sum_coverage / (double)num_sites;
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double mean_good_coverage = (double)sum_coverage / ((double)(num_sites - getCov(0)));
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out.printf("# all_sites : mean:%f num_sites:%d%n", mean_coverage, num_sites);
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out.printf("# sites with at least 1 read : mean:%f num_sites:%d%n", mean_good_coverage, num_sites - getCov(0));
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// Code for calculting std devs adapted from Michael Melgar's python script
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// Find the maximum extent of 'good' data
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// First, find the mode
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long maxValue = getCov(1); // ignore doc=0
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int mode = 1;
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for (int i = 2; i <= max_depth; i++) {
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if (getCov(i) > maxValue) {
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maxValue = getCov(i);
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mode = i;
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}
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}
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// now, procede to find end of good Gaussian fit
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long dist = (long)Math.pow(10, 9);
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while ( Math.abs(getCov(mode) - getCov(1)) < dist )
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dist = Math.abs(getCov(mode++) - getCov(1));
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int maxGoodDepth = mode + 1;
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// calculate the mean of the good region
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long totalGoodSites = 0, totalGoodDepth = 0;
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for (int i = 1; i <= maxGoodDepth; i++) { // ignore doc=0
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totalGoodSites += getCov(i);
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totalGoodDepth += i * getCov(i);
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}
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double meanGoodDepth = (double)totalGoodDepth / (double)totalGoodSites;
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// calculate the variance and standard deviation of the good region
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double var = 0.0;
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for (int i = 1; i <= maxGoodDepth; i++) { // ignore doc=0
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var += getCov(i) * Math.pow(meanGoodDepth - (double)i, 2);
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}
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double stdev = Math.sqrt(var / (double)totalGoodSites);
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out.printf("# sites within Gaussian fit : mean:%f num_sites:%d std_dev:%f%n", meanGoodDepth, totalGoodSites, stdev);
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for (int i = 1; i <= 5; i++)
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out.printf("# Gaussian mean + %d Std Dev : %f%n", i, (meanGoodDepth + i*stdev));
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out.println("\ndepth count freq(percent)");
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for (int i = 0; i <= max_depth; i++)
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{
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out.printf("%d %d %f\n", i, getCov(i), (100.0*getCov(i)) / (double)num_sites);
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}
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}
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public Integer reduceInit()
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{
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return 0;
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}
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public Integer reduce(Integer record, Integer sum)
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{
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return 0;
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}
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// END Walker Interface Functions
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/////////
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}
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@ -13,13 +13,14 @@ public class DepthOfCoverageIntegrationTest extends WalkerTest {
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private static String root = "-L 1:10,164,500-10,164,520 -R /broad/1KG/reference/human_b36_both.fasta -T DepthOfCoverage -I /humgen/gsa-scr1/GATK_Data/Validation_Data/NA12878.1kg.p2.chr1_10mb_11_mb.SLX.bam";
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static HashMap<String, String> expectations = new HashMap<String, String>();
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static {
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expectations.put("-minMAPQ 1", "59c6071105a598e19f460640c35768c6");
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expectations.put("-minMAPQ 100", "e997fb5d61eaec21518722b0de90af20");
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expectations.put("-minDepth 8", "3e50afef0e751119cd27c324bdfae544");
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expectations.put("-minDepth 10", "d4c336d9e748347e1082bbc92d2489a3");
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expectations.put("-bySample", "160ffa185dbfa8b0d2dc57f60f5b1e48");
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expectations.put("-byRG", "dd3b4d040df7325dad4760ac6fa5252d");
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expectations.put("-minMAPQ 1 -bySample -byRG", "bd2a07ef548b86e82ac6cce534225612");
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expectations.put("-minMAPQ 1", "8b73fad5cce4620907d5da2a985219d5");
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expectations.put("-minMAPQ 100", "1a959892d8ad0523dac2fb097eacb3c2");
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expectations.put("-minDepth 8", "6e8c6b6d78962d110c87ad905fa5b664");
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expectations.put("-minDepth 10", "14399e1237866540af3f1aee149030d0");
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expectations.put("-bySample", "93358437153b4d65bdff747e33de1d63");
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expectations.put("-byRG", "777e8427eb4bdad300b23800cb7b0592");
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expectations.put("-histogram", "96f15e1d9d598d48191e20ee84715d46");
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expectations.put("-minMAPQ 1 -bySample -byRG -minDepth 8 -histogram", "783b0bc83c54d883efa8383a379ff17b");
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}
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@Test
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@ -41,7 +42,7 @@ public class DepthOfCoverageIntegrationTest extends WalkerTest {
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WalkerTestSpec spec = new WalkerTestSpec(
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"-T DepthOfCoverage -R /broad/1KG/reference/human_b36_both.fasta -I /humgen/gsa-scr1/GATK_Data/Validation_Data/NA12873.454.SRP000031.2009_06.chr1.10_20mb.bam -L 1:10,001,890-10,001,895 -o %s",
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1, // just one output file
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Arrays.asList("51203ba5ab928449cd01363af0b91510"));
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Arrays.asList("a332d1539b29dff615b198818a3d4dd1"));
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executeTest("testDepthOfCoverage454", spec);
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}
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}
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