misc clean up in VQSR

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@5014 348d0f76-0448-11de-a6fe-93d51630548a

java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/GenerateVariantClustersWalker.java

@@ -242,18 +242,8 @@ public class GenerateVariantClustersWalker extends RodWalker<ExpandingArrayList<
 
         dataManager.normalizeData(); // Each data point is now [ (x - mean) / standard deviation ]
 
-        // Create either the Gaussian Mixture Model or the Nearest Neighbors model and run it
+        // Create the Gaussian Mixture Model model and run it
-        switch (OPTIMIZATION_MODEL) {
+        theModel = new VariantGaussianMixtureModel( dataManager, MAX_GAUSSIANS, MAX_ITERATIONS, FORCE_INDEPENDENT, STD_THRESHOLD, SHRINKAGE, DIRICHLET_PARAMETER );
-            case GAUSSIAN_MIXTURE_MODEL:
-                theModel = new VariantGaussianMixtureModel( dataManager, MAX_GAUSSIANS, MAX_ITERATIONS, FORCE_INDEPENDENT,
-                                                            STD_THRESHOLD, SHRINKAGE, DIRICHLET_PARAMETER );
-                break;
-            //case K_NEAREST_NEIGHBORS:
-            //    theModel = new VariantNearestNeighborsModel( dataManager, TARGET_TITV, NUM_KNN );
-            //    break;
-            default:
-                throw new UserException.BadArgumentValue("OPTIMIZATION_MODEL", "Variant Optimization Model is unrecognized. Implemented options are GAUSSIAN_MIXTURE_MODEL and K_NEAREST_NEIGHBORS" );
-        }
 
         theModel.run( CLUSTER_FILE );
     }

java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/Tranche.java

@@ -170,7 +170,7 @@ public class Tranche implements Comparable<Tranche> {
                     header = vals;
                     if ( header.length == 5 )
                         // old style tranches file, throw an error
-                        throw new UserException.MalformedFile(f, "Unfortuanately, your tranches file is from a previous version of this tool and cannot be used with the latest code.  Please rerun VariantRecalibrator");
+                        throw new UserException.MalformedFile(f, "Unfortunately, your tranches file is from a previous version of this tool and cannot be used with the latest code.  Please rerun VariantRecalibrator");
                     if ( header.length != 8 && header.length != 11 )
                         throw new UserException.MalformedFile(f, "Expected 8 elements in header line " + line);
                 } else {

java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantOptimizationModel.java

@@ -34,8 +34,7 @@ package org.broadinstitute.sting.gatk.walkers.variantrecalibration;
 public abstract class VariantOptimizationModel implements VariantOptimizationInterface {
 
     public enum Model {
-        GAUSSIAN_MIXTURE_MODEL,
+        GAUSSIAN_MIXTURE_MODEL
-        K_NEAREST_NEIGHBORS
     }
 
     protected final double targetTITV;
@@ -53,8 +52,6 @@ public abstract class VariantOptimizationModel implements VariantOptimizationInt
         if( titv > targetTITV ) { titv -= 2.0f*(titv-targetTITV); }
         if( titv < 0.5 ) { titv = 0.5; }
         return ( (titv - 0.5) / (targetTITV - 0.5) );
-        //if( titv < 0.0 ) { titv = 0.0; }
-        //return ( titv / targetTITV );
     }
 
     public final double calcTruePositiveRateFromKnownTITV( final double knownTITV, final double _novelTITV, final double overallTITV, final double knownAlphaFactor ) {

java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrator.java

@@ -164,21 +164,11 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
             ignoreInputFilterSet = new TreeSet<String>(Arrays.asList(IGNORE_INPUT_FILTERS));
         }
 
-        switch (OPTIMIZATION_MODEL) {
+        theModel = new VariantGaussianMixtureModel( TARGET_TITV, CLUSTER_FILE, BACKOFF_FACTOR );
-            case GAUSSIAN_MIXTURE_MODEL:
+        if ( SINGLETON_FP_RATE != -1 ) {
-                theModel = new VariantGaussianMixtureModel( TARGET_TITV, CLUSTER_FILE, BACKOFF_FACTOR );
+            theModel.setSingletonFPRate(SINGLETON_FP_RATE);
-                if ( SINGLETON_FP_RATE != -1 ) {
-                    theModel.setSingletonFPRate(SINGLETON_FP_RATE);
-                }
-                break;
-            //case K_NEAREST_NEIGHBORS:
-            //    theModel = new VariantNearestNeighborsModel( dataManager, TARGET_TITV, NUM_KNN );
-            //    break;
-            default:
-                throw new UserException.BadArgumentValue("OPTIMIZATION_MODEL", "Variant Optimization Model is unrecognized. Implemented options are GAUSSIAN_MIXTURE_MODEL and K_NEAREST_NEIGHBORS" );
         }
 
-
         // deal with annotations
         if ( USE_ANNOTATIONS  != null ) {
             for ( String annotation : USE_ANNOTATIONS ) {
@@ -265,9 +255,6 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
         }
         nTruthSites += isAtTruthSite ? 1 : 0;
 
-        //final VariantContext vcTruth = ( vcsTruth.size() != 0 ? vcsTruth.iterator().next() : null );
-        //nTruthSites += vcTruth != null && vcTruth.isVariant() ? 1 : 0;
-
         for( final VariantContext vc : tracker.getVariantContexts(ref, inputNames, null, context.getLocation(), false, false) ) {
             if( vc != null && vc.isSNP() ) {
                 if( !vc.isFiltered() || IGNORE_ALL_INPUT_FILTERS || (ignoreInputFilterSet != null && ignoreInputFilterSet.containsAll(vc.getFilters())) ) {
@@ -345,7 +332,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
                         variantDatum.lod = round4(lod);
 
                         // deal with the truth calculation
-                        variantDatum.atTruthSite = isAtTruthSite; //vcTruth != null && vcTruth.isVariant();
+                        variantDatum.atTruthSite = isAtTruthSite; 
 
                         mapList.add( variantDatum );
                         final Map<String, Object> attrs = new HashMap<String, Object>(vc.getAttributes());