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Get rid of useless test/'optimization' that was carried over from UGv1. New codde is (minimally) faster with same results. 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@4478 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
ebanks 2010-10-11 04:04:07 +00:00
parent f28523e7de
commit fd8351cd49
3 changed files with 1 additions and 22 deletions
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11
java/src/org/broadinstitute/sting/playground/gatk/walkers/genotyper/AlleleFrequencyCalculationModel.java
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@ -61,8 +61,6 @@ public abstract class AlleleFrequencyCalculationModel implements Cloneable {
protected Logger logger; protected Logger logger;
protected PrintStream verboseWriter; protected PrintStream verboseWriter;
private int minAlleleFrequencyToTest;
protected AlleleFrequencyCalculationModel(int N, Logger logger, PrintStream verboseWriter) { protected AlleleFrequencyCalculationModel(int N, Logger logger, PrintStream verboseWriter) {
this.N = N; this.N = N;
this.logger = logger; this.logger = logger;
@ -109,15 +107,6 @@ public abstract class AlleleFrequencyCalculationModel implements Cloneable {
return generateCalls(contexts, GLs, AFofMaxLikelihood); return generateCalls(contexts, GLs, AFofMaxLikelihood);
} }
// TODO: get rid of this optimization, it is wrong!
protected int getMinAlleleFrequencyToTest() {
return minAlleleFrequencyToTest;
}
protected void setMinAlleleFrequencyToTest(int minAF) {
minAlleleFrequencyToTest = minAF;
}
protected Map<String, Genotype> generateCalls(Map<String, StratifiedAlignmentContext> contexts, protected Map<String, Genotype> generateCalls(Map<String, StratifiedAlignmentContext> contexts,
Map<String, BiallelicGenotypeLikelihoods> GLs, Map<String, BiallelicGenotypeLikelihoods> GLs,
int frequency) { int frequency) {

5
java/src/org/broadinstitute/sting/playground/gatk/walkers/genotyper/GridSearchAFEstimation.java
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@ -56,9 +56,6 @@ public class GridSearchAFEstimation extends AlleleFrequencyCalculationModel {
log10AlleleFrequencyPosteriors[0] = AFMatrix.getLikelihoodsOfFrequency() + log10AlleleFrequencyPriors[0]; log10AlleleFrequencyPosteriors[0] = AFMatrix.getLikelihoodsOfFrequency() + log10AlleleFrequencyPriors[0];
double maxLikelihoodSeen = log10AlleleFrequencyPosteriors[0]; double maxLikelihoodSeen = log10AlleleFrequencyPosteriors[0];
// TODO: get rid of this optimization, it is wrong!
int minAlleleFrequencyToTest = getMinAlleleFrequencyToTest();
int maxAlleleFrequencyToTest = AFMatrix.getSamples().size() * 2; int maxAlleleFrequencyToTest = AFMatrix.getSamples().size() * 2;
// for each minor allele frequency, calculate log10PofDgivenAFi // for each minor allele frequency, calculate log10PofDgivenAFi
@ -71,7 +68,7 @@ public class GridSearchAFEstimation extends AlleleFrequencyCalculationModel {
// an optimization to speed up the calculation: if we are beyond the local maximum such // an optimization to speed up the calculation: if we are beyond the local maximum such
// that subsequent likelihoods won't factor into the confidence score, just quit // that subsequent likelihoods won't factor into the confidence score, just quit
if ( i >= minAlleleFrequencyToTest && maxLikelihoodSeen - log10AlleleFrequencyPosteriors[i] > LOG10_OPTIMIZATION_EPSILON ) if ( maxLikelihoodSeen - log10AlleleFrequencyPosteriors[i] > LOG10_OPTIMIZATION_EPSILON )
return; return;
if ( log10AlleleFrequencyPosteriors[i] > maxLikelihoodSeen ) if ( log10AlleleFrequencyPosteriors[i] > maxLikelihoodSeen )

7
java/src/org/broadinstitute/sting/playground/gatk/walkers/genotyper/UnifiedGenotyperEngine.java
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@ -142,10 +142,6 @@ public class UnifiedGenotyperEngine {
if ( GLs.size() == 0 ) if ( GLs.size() == 0 )
return estimateReferenceConfidence(stratifiedContexts, genotypePriors.getHeterozygosity(), false); return estimateReferenceConfidence(stratifiedContexts, genotypePriors.getHeterozygosity(), false);
// reset the optimization value and determine the p(AF>0)
// TODO: get rid of this optimization, it is wrong!
afcm.get().setMinAlleleFrequencyToTest(0);
// 'zero' out the AFs (so that we don't have to worry if not all samples have reads at this position) // 'zero' out the AFs (so that we don't have to worry if not all samples have reads at this position)
clearAFarray(log10AlleleFrequencyPosteriors.get()); clearAFarray(log10AlleleFrequencyPosteriors.get());
afcm.get().getLog10PNonRef(tracker, refContext, GLs, log10AlleleFrequencyPriors, log10AlleleFrequencyPosteriors.get()); afcm.get().getLog10PNonRef(tracker, refContext, GLs, log10AlleleFrequencyPriors, log10AlleleFrequencyPosteriors.get());
@ -221,9 +217,6 @@ public class UnifiedGenotyperEngine {
double lod = overallLog10PofF - overallLog10PofNull; double lod = overallLog10PofF - overallLog10PofNull;
//System.out.println("overallLog10PofNull=" + overallLog10PofNull + ", overallLog10PofF=" + overallLog10PofF); //System.out.println("overallLog10PofNull=" + overallLog10PofNull + ", overallLog10PofF=" + overallLog10PofF);
// set the optimization value for the subsequent strand calculations
afcm.get().setMinAlleleFrequencyToTest(bestAFguess);
// the forward lod // the forward lod
GLs.clear(); GLs.clear();
glcm.get().getLikelihoods(tracker, refContext, stratifiedContexts, StratifiedAlignmentContext.StratifiedContextType.FORWARD, genotypePriors, GLs); glcm.get().getLikelihoods(tracker, refContext, stratifiedContexts, StratifiedAlignmentContext.StratifiedContextType.FORWARD, genotypePriors, GLs);