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Merge pull request #373 from broadinstitute/rp_vqsr_numbad_docs 

Cleaning up help text for the -numBad argument.
This commit is contained in:
Eric Banks 2013-08-12 10:56:46 -07:00
parent 163d796ae7 59f56bef30
commit 4aeb37e1e7
3 changed files with 4 additions and 4 deletions
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4
protected/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantDataManager.java
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@ -264,7 +264,7 @@ public class VariantDataManager {
Collections.sort( data, new VariantDatum.VariantDatumLODComparator() );
final int numToAdd = minimumNumber - trainingData.size();
if( numToAdd > data.size() ) {
throw new UserException.BadInput( "Error during negative model training. Minimum number of variants to use in training is larger than the whole call set. One can attempt to lower the --minNumBadVariants arugment but this is unsafe." );
throw new UserException.BadInput( "Error during negative model training. Minimum number of variants to use in training is larger than the whole call set. One can attempt to lower the --numBadVariants arugment but this is unsafe." );
}
int index = 0, numAdded = 0;
while( numAdded < numToAdd && index < data.size() ) {
@ -275,7 +275,7 @@ public class VariantDataManager {
numAdded++;
}
}
logger.info( "Additionally training with worst " + numToAdd + "% of passing data --> " + (trainingData.size() - numBadSitesAdded) + " variants with LOD <= " + String.format("%.4f", data.get(index).lod) + "." );
logger.info( "Additionally training with worst " + numToAdd + " scoring variants --> " + (trainingData.size() - numBadSitesAdded) + " variants with LOD <= " + String.format("%.4f", data.get(index).lod) + "." );
return trainingData;
}

2
protected/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrator.java
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@ -335,7 +335,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
engine.evaluateData( dataManager.getData(), badModel, true );
if( badModel.failedToConverge || goodModel.failedToConverge ) {
throw new UserException("NaN LOD value assigned. Clustering with this few variants and these annotations is unsafe. Please consider raising the number of variants used to train the negative model (via --minNumBad, for example) or lowering the maximum number of Gaussians to use in the model (via --maxGaussians 4, for example)");
throw new UserException("NaN LOD value assigned. Clustering with this few variants and these annotations is unsafe. Please consider " + (badModel.failedToConverge ? "raising the number of variants used to train the negative model (via --numBad 3000, for example)." : "lowering the maximum number of Gaussians allowed for use in the model (via --maxGaussians 4, for example).") );
}
engine.calculateWorstPerformingAnnotation( dataManager.getData(), goodModel, badModel );

2
protected/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibratorArgumentCollection.java
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@ -94,6 +94,6 @@ public class VariantRecalibratorArgumentCollection {
public double DIRICHLET_PARAMETER = 0.001;
@Argument(fullName="priorCounts", shortName="priorCounts", doc="The number of prior counts to use in the variational Bayes algorithm.", required=false)
public double PRIOR_COUNTS = 20.0;
@Argument(fullName="numBadVariants", shortName="numBad", doc="The number of worst scoring variants to use when building the Gaussian mixture model of bad variants. Will override -percentBad argument if necessary.", required=false)
@Argument(fullName="numBadVariants", shortName="numBad", doc="The number of worst scoring variants to use when building the Gaussian mixture model of bad variants.", required=false)
public int NUM_BAD_VARIANTS = 1000;
}