Computes empirical confusion matrices, optionally with up to five bases of preceding context
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2621 348d0f76-0448-11de-a6fe-93d51630548a
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kiran
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package org.broadinstitute.sting.playground.gatk.walkers.diagnostics;
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import org.broadinstitute.sting.gatk.walkers.LocusWalker;
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import org.broadinstitute.sting.gatk.walkers.Reference;
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import org.broadinstitute.sting.gatk.walkers.Window;
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import org.broadinstitute.sting.gatk.refdata.RefMetaDataTracker;
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import org.broadinstitute.sting.gatk.contexts.ReferenceContext;
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import org.broadinstitute.sting.gatk.contexts.AlignmentContext;
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import org.broadinstitute.sting.utils.cmdLine.Argument;
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import org.broadinstitute.sting.utils.BaseUtils;
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import net.sf.samtools.SAMRecord;
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import java.util.HashMap;
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import java.util.Arrays;
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import java.util.Hashtable;
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/**
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* Computes empirical base confusion matrix, and optionally computes
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* these matrices with up to five bases of preceding context
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*/
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@Reference(window=@Window(start=-5,stop=5))
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public class ComputeConfusionMatrix extends LocusWalker<Integer, Integer> {
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@Argument(fullName="minimumDepth", shortName="minDepth", doc="Require locus pileup to have specified minimum depth", required=false)
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public Integer MIN_DEPTH = 10;
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@Argument(fullName="maximumDepth", shortName="maxDepth", doc="Require locus pileup to have specified maximum depth", required=false)
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public Integer MAX_DEPTH = 100;
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@Argument(fullName="contextWindowSize", shortName="window", doc="Size of context window", required=false)
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public Integer WINDOW_SIZE = 0;
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private Hashtable<String, Integer> confusionCounts = new Hashtable<String, Integer>();
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public boolean filter(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context) {
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int pileupSize = context.size();
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int numAlts = 0;
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int[] baseCounts = context.getBasePileup().getBaseCounts();
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for (int baseIndex = 0; baseIndex < baseCounts.length; baseIndex++) {
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if (baseIndex != ref.getBaseIndex()) {
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numAlts += baseCounts[baseIndex];
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}
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}
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return (
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pileupSize >= MIN_DEPTH && // don't process regions without a reasonable pileup
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pileupSize < MAX_DEPTH && // don't process suspiciously overcovered regions
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ref.getBases().length % 2 == 1 && // don't process regions that don't have a full context window
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numAlts == 1 && // don't process regions that have more than one mismatching base
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ref.getBaseIndex() >= 0 // don't process a locus with an ambiguous reference base
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);
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}
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public Integer map(RefMetaDataTracker tracker, ReferenceContext ref, AlignmentContext context) {
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int windowLength = ref.getBases().length;
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int windowCenter = (windowLength - 1)/2;
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String fwRefBases = new String(ref.getBases());
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String fwRefBase = String.format("%c", ref.getBase());
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String fwWindowLeft = fwRefBases.substring(windowCenter - WINDOW_SIZE, windowCenter);
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//String rcRefBases = new String(BaseUtils.simpleReverseComplement(ref.getBases()));
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//String rcRefBase = String.format("%c", BaseUtils.simpleComplement(ref.getBase()));
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//String rcWindowRight = rcRefBases.substring(windowCenter + 1, windowCenter + 1 + WINDOW_SIZE);
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int[] baseCounts = context.getBasePileup().getBaseCounts();
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int altBaseIndex = -1;
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for (int baseIndex = 0; baseIndex < 4; baseIndex++) {
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if (baseCounts[baseIndex] == 1) {
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altBaseIndex = baseIndex;
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}
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}
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String fwAltBase = String.format("%c", BaseUtils.baseIndexToSimpleBase(altBaseIndex));
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//String rcAltBase = BaseUtils.simpleComplement(fwAltBase);
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for (int readIndex = 0; readIndex < context.getReads().size(); readIndex++) {
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SAMRecord read = context.getReads().get(readIndex);
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int offset = context.getOffsets().get(readIndex);
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char base = read.getReadString().charAt(offset);
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int baseIndex = BaseUtils.simpleBaseToBaseIndex(base);
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if (baseIndex == altBaseIndex) {
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if (read.getReadNegativeStrandFlag()) {
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//incrementConfusionCounts(rcWindowRight, rcRefBase, rcAltBase);
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} else {
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incrementConfusionCounts(fwWindowLeft, fwAltBase, fwRefBase);
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}
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}
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}
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return null;
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}
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private void incrementConfusionCounts(String context, String altBase, String refBase) {
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String key = String.format("%s:%s:%s", context, altBase, refBase);
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Integer counts = confusionCounts.get(key);
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if (counts == null) { counts = 0; }
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confusionCounts.put(key, counts + 1);
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}
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public Integer reduceInit() {
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return null;
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}
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public Integer reduce(Integer value, Integer sum) {
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return null;
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}
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public void onTraversalDone(Integer result) {
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String[] keys = confusionCounts.keySet().toArray(new String[0]);
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Arrays.sort(keys);
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HashMap<String, Integer> contextualNorms = new HashMap<String, Integer>();
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for (String key : keys) {
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String[] fields = key.split(":");
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String contextualKey = String.format("%s:%s", fields[0], fields[1]);
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Integer contextualCount = contextualNorms.get(contextualKey);
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if (contextualCount == null) { contextualCount = 0; }
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contextualNorms.put(contextualKey, contextualCount + confusionCounts.get(key));
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}
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out.printf("confusionMatrix\tcontext\talt\tref\tcontextualCounts\tcontextualPercentage\n");
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for (String key : keys) {
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String[] fields = key.split(":");
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String contextualKey = String.format("%s:%s", fields[0], fields[1]);
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out.printf(
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"confusionMatrix\t%s\t%s\t%s\t%d\t%d\t%f\n",
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fields[0],
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fields[1],
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fields[2],
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confusionCounts.get(key),
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contextualNorms.get(contextualKey),
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confusionCounts.get(key)/((float) contextualNorms.get(contextualKey))
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);
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}
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}
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}
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