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Minor updates to output of variant optimizer. 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@3031 348d0f76-0448-11de-a6fe-93d51630548a
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rpoplin 2010-03-18 12:46:47 +00:00
parent 0247548400
commit c78fc23ec5
2 changed files with 6 additions and 1 deletions
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1
R/plot_OptimizationCurve.R
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@ -10,6 +10,7 @@ targetTITV = as.numeric(args[2])
data = read.table(input,sep=",",head=T) data = read.table(input,sep=",",head=T)
maxVars = max(data$numKnown, data$numNovel) maxVars = max(data$numKnown, data$numNovel)
maxTITV = max(data$knownTITV[is.finite(data$knownTITV) & data$numKnown>2000], data$novelTITV[is.finite(data$novelTITV) & data$numNovel > 2000], targetTITV) maxTITV = max(data$knownTITV[is.finite(data$knownTITV) & data$numKnown>2000], data$novelTITV[is.finite(data$novelTITV) & data$numNovel > 2000], targetTITV)
maxTITV = min(maxTITV, targetTITV + 1)
minTITV = min(data$knownTITV[length(data$knownTITV)], data$novelTITV[length(data$novelTITV)], targetTITV) minTITV = min(data$knownTITV[length(data$knownTITV)], data$novelTITV[length(data$novelTITV)], targetTITV)
maxPCut = max(data$pCut[data$numKnown>0 | data$numNovel>0]) maxPCut = max(data$pCut[data$numKnown>0 | data$numNovel>0])

6
java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantGaussianMixtureModel.java
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@ -328,6 +328,10 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
final int numVariants = data.length; final int numVariants = data.length;
final boolean[] markedVariant = new boolean[numVariants]; final boolean[] markedVariant = new boolean[numVariants];
for( int iii = 0; iii < numVariants; iii++ ) {
markedVariant[iii] = false;
}
PrintStream outputFile = null; PrintStream outputFile = null;
try { try {
outputFile = new PrintStream( outputPrefix + ".dat" ); outputFile = new PrintStream( outputPrefix + ".dat" );
@ -368,7 +372,7 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
} }
} }
if( desiredNumVariants != 0 && !foundDesiredNumVariants && (numKnown + numNovel) >= desiredNumVariants ) { if( desiredNumVariants != 0 && !foundDesiredNumVariants && (numKnown + numNovel) >= desiredNumVariants ) {
System.out.println( "Keeping variants with p(true) >= " + String.format("%.1f",pCut) + " results in a filtered set with: " ); System.out.println( "Keeping variants with QUAL >= " + String.format("%.1f",pCut) + " results in a filtered set with: " );
System.out.println("\t" + numKnown + " known variants"); System.out.println("\t" + numKnown + " known variants");
System.out.println("\t" + numNovel + " novel variants, (dbSNP rate = " + String.format("%.2f",((double) numKnown * 100.0) / ((double) numKnown + numNovel) ) + "%)"); System.out.println("\t" + numNovel + " novel variants, (dbSNP rate = " + String.format("%.2f",((double) numKnown * 100.0) / ((double) numKnown + numNovel) ) + "%)");
System.out.println("\t" + String.format("%.4f known Ti/Tv ratio", ((double)numKnownTi) / ((double)numKnownTv))); System.out.println("\t" + String.format("%.4f known Ti/Tv ratio", ((double)numKnownTi) / ((double)numKnownTv)));