From 97fdd92e7b078ee327a80f5a239e09fcd42355ac Mon Sep 17 00:00:00 2001
From: rpoplin <rpoplin@348d0f76-0448-11de-a6fe-93d51630548a>
Date: Mon, 3 May 2010 13:30:20 +0000
Subject: [PATCH] Clean up the code to have a unified approach to calculating
 p(true) for both with and without ti/tv models

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@3289 348d0f76-0448-11de-a6fe-93d51630548a
---
 .../variantoptimizer/ApplyVariantClustersWalker.java | 10 ++--------
 .../VariantGaussianMixtureModel.java                 | 12 +++++++-----
 2 files changed, 9 insertions(+), 13 deletions(-)

diff --git a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/ApplyVariantClustersWalker.java b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/ApplyVariantClustersWalker.java
index 67e11bbe8..37e05ff9a 100755
--- a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/ApplyVariantClustersWalker.java
+++ b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/ApplyVariantClustersWalker.java
@@ -161,14 +161,8 @@ public class ApplyVariantClustersWalker extends RodWalker<ExpandingArrayList<Var
                     variantDatum.isKnown = !vc.getAttribute("ID").equals(".");
 
                     final double pTrue = theModel.evaluateVariant( vc.getAttributes(), vc.getPhredScaledQual() );
-                    double recalQual = QualityUtils.phredScaleErrorRate( Math.max(1.0 - pTrue, 0.000000001) );
-                    if( !theModel.isUsingTiTvModel ) {
-                        recalQual *= 30.0;
-                    } else {
-                        recalQual *= 3.0;
-                    }
-                    // BUGBUG: decide how to scale the quality score
-
+                    double recalQual = 400.0 * QualityUtils.phredScaleErrorRate( Math.max(1.0 - pTrue, 0.000000001) );
+                    
                     if( variantDatum.isKnown && KNOWN_VAR_QUAL_PRIOR > 0.1 ) { // only use the known prior if the value is specified (meaning not equal to zero)
                         variantDatum.qual = 0.5 * recalQual + 0.5 * KNOWN_VAR_QUAL_PRIOR;
                     } else {
diff --git a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantGaussianMixtureModel.java b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantGaussianMixtureModel.java
index 2b11b62d1..0a1d301ec 100755
--- a/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantGaussianMixtureModel.java
+++ b/java/src/org/broadinstitute/sting/playground/gatk/walkers/variantoptimizer/VariantGaussianMixtureModel.java
@@ -721,6 +721,7 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
             final double denom = Math.pow(2.0 * 3.14159, ((double)numAnnotations) / 2.0) * Math.pow(determinant[kkk], 0.5);
             pVarInCluster[kkk] =  (1.0 / ((double) numGaussians)) * (Math.exp( -0.5 * sum )) / denom;
 
+            /*
             if( isUsingTiTvModel ) {
                 //pVarInCluster[kkk] =  Math.exp( -0.5 * sum );
                 if( pVarInCluster[kkk] < MIN_PROB) { // Very small numbers are a very big problem
@@ -733,13 +734,14 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
                 //pVarInCluster[kkk] =  Math.exp( -0.5 * sum );
                 // BUGBUG: should pCluster be the distribution from the GMM or a uniform distribution here?
             }
+            */
         }
 
-        if( isUsingTiTvModel ) {
-            for( int kkk = 0; kkk < numGaussians; kkk++ ) {
-                pVarInCluster[kkk] /= sumProb;
-            }
-        }
+        //if( isUsingTiTvModel ) {
+        //    for( int kkk = 0; kkk < numGaussians; kkk++ ) {
+        //        pVarInCluster[kkk] /= sumProb;
+        //    }
+        //}
     }