Now outputs stats. Doesn't do the downsampling thing because I think I'll have enough counts.
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@1184 348d0f76-0448-11de-a6fe-93d51630548a
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jmaguire
parent
5d7393d7cb
commit
1fa71aa31d
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@ -13,6 +13,7 @@ import org.broadinstitute.sting.playground.utils.*;
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import org.broadinstitute.sting.utils.*;
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import org.broadinstitute.sting.utils.ReadBackedPileup;
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import org.broadinstitute.sting.utils.cmdLine.Argument;
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import org.broadinstitute.sting.playground.indels.Matrix;
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import java.util.*;
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import java.util.zip.*;
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@ -24,54 +25,122 @@ import java.io.*;
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public class MultiSampleCallerAccuracyTest extends MultiSampleCaller
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{
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@Argument(required=false, shortName="lod_threshold", doc="") public double LOD_THRESHOLD = 1e-6;
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@Argument(required=true, shortName="stats_output", doc="") public String STATS_OUTPUT;
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Matrix<Integer> n_variants;
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Matrix<Integer> n_found;
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PrintStream stats_output;
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public void initialize()
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{
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this.DISCOVERY_OUTPUT = "/dev/null";
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this.INDIVIDUAL_OUTPUT = "/dev/null";
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super.initialize();
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n_variants = new Matrix<Integer>(sample_names.size()*2, sample_names.size()*2);
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n_found = new Matrix<Integer>(sample_names.size()*2, sample_names.size()*2);
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for (int i = 0; i < sample_names.size()*2; i++)
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{
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for (int j = 0; j < sample_names.size()*2; j++)
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{
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n_variants.set(i,j,0);
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n_found.set(i,j,0);
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}
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}
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try
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{
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stats_output = new PrintStream(STATS_OUTPUT);
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}
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catch (Exception e)
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{
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throw new RuntimeException(e);
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}
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}
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public MultiSampleCallResult map(RefMetaDataTracker tracker, char ref, LocusContext context)
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{
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HapMapGenotypeROD hapmap = (HapMapGenotypeROD)tracker.lookup("hapmap", null);
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MultiSampleCallResult call_result = super.map(tracker, ref, context);
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EM_Result em_result = call_result.em_result;
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// Collect all the variants and the normals.
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ArrayList<String> variant_samples = new ArrayList<String>();
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ArrayList<String> reference_samples = new ArrayList<String>();
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// Compute individual accuracy.
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double n_calls = 0;
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double n_correct = 0;
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for (int i = 0; i < em_result.sample_names.length; i++)
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int n_ref_chromosomes = 0;
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int n_alt_chromosomes = 0;
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String reference_genotype = String.format("%c%c", ref, ref);
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for (int i = 0; i < sample_names.size(); i++)
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{
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String sample_name = em_result.sample_names[i];
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String hyp_genotype = em_result.genotype_likelihoods[i].BestGenotype();
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String ref_genotype = hapmap.get(sample_name);
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double lod = em_result.genotype_likelihoods[i].LodVsNextBest();
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String true_genotype = hapmap.get(sample_names.get(i));
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if (true_genotype == null) { continue; }
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if ((lod > LOD_THRESHOLD) && (ref_genotype != null))
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{
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n_calls += 1;
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if (hyp_genotype.equals(ref_genotype))
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{
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n_correct += 1;
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}
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}
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if (true_genotype.equals(reference_genotype)) { reference_samples.add(sample_names.get(i)); }
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else { variant_samples.add(sample_names.get(i)); }
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if (true_genotype.equals(reference_genotype)) { n_ref_chromosomes += 1; }
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else if (true_genotype.contains(String.format("%c",ref))) { n_ref_chromosomes += 1; n_alt_chromosomes += 1; }
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else { n_alt_chromosomes += 2; }
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}
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out.printf("%s %.0f %.0f %.2f%%\n",
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context.getLocation(),
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n_calls,
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n_correct,
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100.0*n_correct / n_calls);
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// Put together a context.
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ArrayList<String> working_samples = new ArrayList<String>();
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working_samples.addAll(variant_samples);
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working_samples.addAll(reference_samples);
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LocusContext working_context = filterLocusContextBySamples(context, working_samples);
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return call_result;
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// Call.
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MultiSampleCallResult call_result = super.map(tracker, ref, working_context);
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EM_Result em_result = call_result.em_result;
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// Compute Statistics.
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if (n_variants == null) { System.out.printf("n_variants is null\n"); }
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if (n_found == null) { System.out.printf("n_found is null\n"); }
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n_variants.set(n_ref_chromosomes, n_alt_chromosomes, n_variants.get(n_ref_chromosomes, n_alt_chromosomes)+1);
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if ((call_result.lod > LOD_THRESHOLD) && (n_alt_chromosomes >= 1))
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{
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n_found.set(n_ref_chromosomes, n_alt_chromosomes, n_found.get(n_ref_chromosomes, n_alt_chromosomes)+1);
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}
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return null;
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}
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private void PrintStats()
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{
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stats_output.printf("n_reference_chromosomes n_variant_chromosomes n_sites n_found fraction_found\n");
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for (int i = 0; i < sample_names.size()*2; i++)
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{
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for (int j = 0; j < sample_names.size()*2; j++)
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{
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int N = (int)n_variants.get(i,j);
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int found = (int)n_found.get(i,j);
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if (N == 0) { continue; }
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if (found == 0) { continue; }
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double fraction_found = 100.0 * (double)found / (double)N;
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n_variants.set(i,j,0);
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n_found.set(i,j,0);
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stats_output.printf("%d %d %d %d %f\n",
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i,
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j,
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N,
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found,
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fraction_found);
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}
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}
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}
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public void onTraversalDone(String sum)
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{
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PrintStats();
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stats_output.flush();
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stats_output.close();
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out.println("MultiSampleCallerAccuracyTest done.");
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return;
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}
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@ -89,4 +158,46 @@ public class MultiSampleCallerAccuracyTest extends MultiSampleCaller
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// END Walker Interface Functions
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/////////
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/////////
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// BEGIN Utility Functions
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// Filter a locus context by sample IDs
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// (pulls out only reads from the specified samples, and returns them in one context).
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private LocusContext filterLocusContextBySamples(LocusContext context, List<String> sample_names)
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{
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HashSet<String> index = new HashSet<String>();
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for (int i = 0; i < sample_names.size(); i++)
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{
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index.add(sample_names.get(i));
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}
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ArrayList<SAMRecord> reads = new ArrayList();
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ArrayList<Integer> offsets = new ArrayList();
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for (int i = 0; i < context.getReads().size(); i++)
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{
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SAMRecord read = context.getReads().get(i);
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Integer offset = context.getOffsets().get(i);
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String RG = (String)(read.getAttribute("RG"));
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assert(header != null);
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assert(header.getReadGroup(RG) != null);
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String sample = header.getReadGroup(RG).getSample();
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if (SAMPLE_NAME_REGEX != null) { sample = sample.replaceAll(SAMPLE_NAME_REGEX, "$1"); }
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if (index.contains(sample))
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{
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reads.add(read);
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offsets.add(offset);
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}
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}
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return new LocusContext(context.getLocation(), reads, offsets);
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}
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// END Utility Functions
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/////////
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}
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