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Bugfix for FisherStrand 

-- FisherStrand pValues can sum to slightly greater than 1.0, so they need to be capped to convert to a Phred-scaled quality score
This commit is contained in:
Mark DePristo 2013-02-11 11:16:19 -08:00
parent 9a29d6d4be
commit 3231031c1a
1 changed files with 11 additions and 10 deletions
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21
protected/java/src/org/broadinstitute/sting/gatk/walkers/annotator/FisherStrand.java
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@ -142,7 +142,7 @@ public class FisherStrand extends InfoFieldAnnotation implements StandardAnnotat
public List<VCFInfoHeaderLine> getDescriptions() {
return Arrays.asList(
new VCFInfoHeaderLine(FS, 1, VCFHeaderLineType.Float, "Phred-scaled p-value using Fisher's exact test to detect strand bias"));
new VCFInfoHeaderLine(FS, 1, VCFHeaderLineType.Float, "Phred-scaled p-value using Fisher's exact test to detect strand bias"));
}
private Double pValueForContingencyTable(int[][] originalTable) {
@ -176,7 +176,8 @@ public class FisherStrand extends InfoFieldAnnotation implements StandardAnnotat
//System.out.printf("P-cutoff: %f\n", pCutoff);
//System.out.printf("P-value: %f\n\n", pValue);
return pValue;
// min is necessary as numerical precision can result in pValue being slightly greater than 1.0
return Math.min(pValue, 1.0);
}
private static int [][] copyContingencyTable(int [][] t) {
@ -222,14 +223,14 @@ public class FisherStrand extends InfoFieldAnnotation implements StandardAnnotat
// calculate in log space so we don't die with high numbers
double pCutoff = Arithmetic.logFactorial(rowSums[0])
+ Arithmetic.logFactorial(rowSums[1])
+ Arithmetic.logFactorial(colSums[0])
+ Arithmetic.logFactorial(colSums[1])
- Arithmetic.logFactorial(table[0][0])
- Arithmetic.logFactorial(table[0][1])
- Arithmetic.logFactorial(table[1][0])
- Arithmetic.logFactorial(table[1][1])
- Arithmetic.logFactorial(N);
+ Arithmetic.logFactorial(rowSums[1])
+ Arithmetic.logFactorial(colSums[0])
+ Arithmetic.logFactorial(colSums[1])
- Arithmetic.logFactorial(table[0][0])
- Arithmetic.logFactorial(table[0][1])
- Arithmetic.logFactorial(table[1][0])
- Arithmetic.logFactorial(table[1][1])
- Arithmetic.logFactorial(N);
return Math.exp(pCutoff);
}