diff --git a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/GenerateVariantClustersWalker.java b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/GenerateVariantClustersWalker.java
index 35dc5bc0d..0e7bdc21a 100755
--- a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/GenerateVariantClustersWalker.java
+++ b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/GenerateVariantClustersWalker.java
@@ -84,14 +84,12 @@ public class GenerateVariantClustersWalker extends RodWalker<ExpandingArrayList<
 //    private String PATH_TO_RESOURCES = "R/";
     @Argument(fullName="weightNovels", shortName="weightNovels", doc="The weight for novel variants during clustering", required=false)
     private double WEIGHT_NOVELS = 0.0;
-    @Argument(fullName="weightKnowns", shortName="weightKnowns", doc="The weight for MQ2+ known variants during clustering", required=false)
-    private double WEIGHT_KNOWNS = 0.0;
-    @Argument(fullName="weightHapMap", shortName="weightHapMap", doc="The weight for known HapMap variants during clustering", required=false)
+    @Argument(fullName="weightDBSNP", shortName="weightDBSNP", doc="The weight for dbSNP variants during clustering", required=false)
+    private double WEIGHT_DBSNP = 0.0;
+    @Argument(fullName="weightHapMap", shortName="weightHapMap", doc="The weight for HapMap variants during clustering", required=false)
     private double WEIGHT_HAPMAP = 1.0;
-    @Argument(fullName="weight1000Genomes", shortName="weight1000Genomes", doc="The weight for known 1000 Genomes Project variants during clustering", required=false)
-    private double WEIGHT_1000GENOMES = 1.0;
-    @Argument(fullName="weightMQ1", shortName="weightMQ1", doc="The weight for MQ1 dbSNP variants during clustering", required=false)
-    private double WEIGHT_MQ1 = 0.0;
+    @Argument(fullName="weight1KG", shortName="weight1KG", doc="The weight for 1000 Genomes Project variants during clustering", required=false)
+    private double WEIGHT_1KG = 1.0;
     @Argument(fullName="forceIndependent", shortName="forceIndependent", doc="Force off-diagonal entries in the covariance matrix to be zero.", required=false)
     private boolean FORCE_INDEPENDENT = false;
     @Argument(fullName="stdThreshold", shortName="std", doc="If a variant has annotations more than -std standard deviations away from mean then don't use it for clustering.", required=false)
@@ -113,7 +111,8 @@ public class GenerateVariantClustersWalker extends RodWalker<ExpandingArrayList<
     /////////////////////////////
     private ExpandingArrayList<String> annotationKeys;
     private Set<String> ignoreInputFilterSet = null;
-    private int maxAC = 0;
+    private Set<String> inputNames = new HashSet<String>();
+
 
     //---------------------------------------------------------------------------------------------------------------
     //
@@ -131,11 +130,21 @@ public class GenerateVariantClustersWalker extends RodWalker<ExpandingArrayList<
         }
 
         boolean foundDBSNP = false;
-        final List<ReferenceOrderedDataSource> dataSources = this.getToolkit().getRodDataSources();
-        for( final ReferenceOrderedDataSource source : dataSources ) {
-            final RMDTrack rod = source.getReferenceOrderedData();
-            if ( rod.getName().equals(DbSNPHelper.STANDARD_DBSNP_TRACK_NAME) ) {
+        for( ReferenceOrderedDataSource d : this.getToolkit().getRodDataSources() ) {
+            if( d.getName().startsWith("input") ) {
+                inputNames.add(d.getName());
+                logger.info("Found input variant track with name " + d.getName());
+            } else if ( d.getName().equals(DbSNPHelper.STANDARD_DBSNP_TRACK_NAME) ) {
+                logger.info("Found dbSNP track for use in training with weight = " + WEIGHT_DBSNP);
                 foundDBSNP = true;
+            } else if ( d.getName().equals("hapmap") ) {
+                logger.info("Found HapMap track for use in training with weight = " + WEIGHT_HAPMAP);
+                foundDBSNP = true;
+            } else if ( d.getName().equals("1kg") ) {
+                logger.info("Found 1KG track for use in training with weight = " + WEIGHT_1KG);
+                foundDBSNP = true;
+            } else {
+                logger.info("Not evaluating ROD binding " + d.getName());
             }
         }
 
@@ -160,8 +169,8 @@ public class GenerateVariantClustersWalker extends RodWalker<ExpandingArrayList<
 
         final double annotationValues[] = new double[annotationKeys.size()];
 
-        for( final VariantContext vc : tracker.getAllVariantContexts(ref, null, context.getLocation(), false, false) ) {
-            if( vc != null && !vc.getName().equals(DbSNPHelper.STANDARD_DBSNP_TRACK_NAME) && vc.isSNP() ) {
+        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())) ) {
                     int iii = 0;
                     for( final String key : annotationKeys ) {
@@ -171,23 +180,24 @@ public class GenerateVariantClustersWalker extends RodWalker<ExpandingArrayList<
                     final VariantDatum variantDatum = new VariantDatum();
                     variantDatum.annotations = annotationValues;
                     variantDatum.isTransition = VariantContextUtils.getSNPSubstitutionType(vc).compareTo(BaseUtils.BaseSubstitutionType.TRANSITION) == 0;
-                    variantDatum.alleleCount = vc.getChromosomeCount(vc.getAlternateAllele(0)); // BUGBUG: assumes file has genotypes
-                    if( variantDatum.alleleCount > maxAC ) {
-                        maxAC = variantDatum.alleleCount;
-                    }
 
                     variantDatum.isKnown = false;
                     variantDatum.weight = WEIGHT_NOVELS;
                     variantDatum.qual = vc.getPhredScaledQual();
 
                     final DbSNPFeature dbsnp = DbSNPHelper.getFirstRealSNP(tracker.getReferenceMetaData(DbSNPHelper.STANDARD_DBSNP_TRACK_NAME));
-                    if( dbsnp != null ) {
-                        variantDatum.isKnown = true;
-                        variantDatum.weight = WEIGHT_KNOWNS;
+                    final VariantContext vcHapMap = tracker.getVariantContext(ref, "hapmap", null, context.getLocation(), false);
+                    final VariantContext vc1KG = tracker.getVariantContext(ref, "1kg", null, context.getLocation(), false);
 
-                        if( DbSNPHelper.isHapmap( dbsnp ) ) { variantDatum.weight = WEIGHT_HAPMAP; }
-                        else if( DbSNPHelper.is1000genomes( dbsnp ) ) { variantDatum.weight = WEIGHT_1000GENOMES; }
-                        else if( DbSNPHelper.isMQ1( dbsnp ) ) { variantDatum.weight = WEIGHT_MQ1; }
+                    if( vcHapMap != null ) {
+                        variantDatum.isKnown = true;
+                        variantDatum.weight = WEIGHT_HAPMAP;
+                    } else if( vc1KG != null ) {
+                        variantDatum.isKnown = true;
+                        variantDatum.weight = WEIGHT_1KG;
+                    } else if( dbsnp != null ) {
+                        variantDatum.isKnown = true;
+                        variantDatum.weight = WEIGHT_DBSNP;
                     }
 
                     if( variantDatum.weight > 0.0 && variantDatum.qual > QUAL_THRESHOLD ) {
@@ -220,7 +230,7 @@ public class GenerateVariantClustersWalker extends RodWalker<ExpandingArrayList<
         final VariantDataManager dataManager = new VariantDataManager( reduceSum, annotationKeys );
         reduceSum.clear(); // Don't need this ever again, clean up some memory
 
-        logger.info( "There are " + dataManager.numVariants + " variants and " + dataManager.numAnnotations + " annotations." );
+        logger.info( "There are " + dataManager.numVariants + " variants with >0 clustering weight and " + dataManager.numAnnotations + " annotations." );
         logger.info( "The annotations are: " + annotationKeys );
 
         dataManager.normalizeData(); // Each data point is now [ (x - mean) / standard deviation ]
diff --git a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantDatum.java b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantDatum.java
index 117a50deb..b12aec37b 100755
--- a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantDatum.java
+++ b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantDatum.java
@@ -37,5 +37,4 @@ public class VariantDatum {
     public boolean isKnown;
     public double qual;
     public double weight;
-    public int alleleCount;
 }
diff --git a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantGaussianMixtureModel.java b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantGaussianMixtureModel.java
index dc30df25c..7558b35db 100755
--- a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantGaussianMixtureModel.java
+++ b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantGaussianMixtureModel.java
@@ -167,11 +167,6 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
     
     public final void run( final PrintStream clusterFile ) {
 
-//        int numValid = 0;
-//        int numOutlier = 0;
-//        int numBadQual = 0;
-//        int numZeroWeight = 0;
-
         // Only cluster with a good set of knowns. Filter based on being too many std's away from the mean annotation value
         // Filtering based on known status and qual threshold happens in GenerateVariantClusters
         for( int iii = 0; iii < dataManager.data.length; iii++ ) {
@@ -184,21 +179,12 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
             }
         }
 
-//        logger.info("Clustering with " + data.length + " valid variants.");
-//        logger.info("  " + numZeroWeight + " variants were removed from clustering due to having zero clustering weight.");
-//        logger.info("  " + numOutlier + " variants were removed due to having annotations that were more than " + stdThreshold + " standard deviations away from the mean annotation value.");
-//        logger.info("  " + numBadQual + " variants were removed because raw QUAL value was less than threshold (" + qualThreshold + ").");
-
         generateEmpricalStats( dataManager.data );
 
         logger.info("Initializing using k-means...");
         initializeUsingKMeans( dataManager.data );
         logger.info("... done!");
         createClusters( dataManager.data, 0, maxGaussians, clusterFile );
-
-        // Simply cluster with all the variants. The knowns have been given more weight than the novels
-        //logger.info("Clustering with " + dataManager.data.length + " variants.");
-        //createClusters( dataManager.data, 0, numGaussians, clusterFileName );
     }
 
     private void generateEmpricalStats( final VariantDatum[] data ) {
diff --git a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrator.java b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrator.java
index 6bfd3b984..2573bb6e1 100755
--- a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrator.java
+++ b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrator.java
@@ -90,17 +90,19 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
     private boolean IGNORE_ALL_INPUT_FILTERS = false;
     @Argument(fullName="ignore_filter", shortName="ignoreFilter", doc="If specified the optimizer will use variants even if the specified filter name is marked in the input VCF file", required=false)
     private String[] IGNORE_INPUT_FILTERS = null;
-    @Argument(fullName="hapmap_prior", shortName="hapmapPrior", doc="A prior on the quality of known variants, a phred scaled probability of being true.", required=false)
-    private double HAPMAP_QUAL_PRIOR = 15.0;
-    @Argument(fullName="known_prior", shortName="knownPrior", doc="A prior on the quality of known variants, a phred scaled probability of being true.", required=false)
-    private double KNOWN_QUAL_PRIOR = 10.0;
-    @Argument(fullName="novel_prior", shortName="novelPrior", doc="A prior on the quality of novel variants, a phred scaled probability of being true.", required=false)
-    private double NOVEL_QUAL_PRIOR = 2.0;
+    @Argument(fullName="priorNovels", shortName="priorNovels", doc="A prior on the quality of novel variants, a phred scaled probability of being true.", required=false)
+    private double PRIOR_NOVELS = 2.0;
+    @Argument(fullName="priorDBSNP", shortName="priorDBSNP", doc="A prior on the quality of dbSNP variants, a phred scaled probability of being true.", required=false)
+    private double PRIOR_DBSNP = 10.0;
+    @Argument(fullName="priorHapMap", shortName="priorHapMap", doc="A prior on the quality of HapMap variants, a phred scaled probability of being true.", required=false)
+    private double PRIOR_HAPMAP = 15.0;
+    @Argument(fullName="prior1KG", shortName="prior1KG", doc="A prior on the quality of 1000 Genomes Project variants, a phred scaled probability of being true.", required=false)
+    private double PRIOR_1KG = 12.0;
     @Argument(fullName="FDRtranche", shortName="tranche", doc="The levels of novel false discovery rate (FDR, implied by ti/tv) at which to slice the data. (in percent, that is 1.0 for 1 percent)", required=false)
     private Double[] FDR_TRANCHES = null;
-    @Argument(fullName = "path_to_Rscript", shortName = "Rscript", doc = "The path to your implementation of Rscript. For Broad users this is maybe /broad/tools/apps/R-2.6.0/bin/Rscript", required = false)
+    @Argument(fullName = "path_to_Rscript", shortName = "Rscript", doc = "The path to your implementation of Rscript. For Broad users this is maybe /broad/tools/apps/R-2.6.0/bin/Rscript", required=false)
     private String PATH_TO_RSCRIPT = "Rscript";
-    @Argument(fullName = "path_to_resources", shortName = "resources", doc = "Path to resources folder holding the Sting R scripts.", required = false)
+    @Argument(fullName = "path_to_resources", shortName = "resources", doc = "Path to resources folder holding the Sting R scripts.", required=false)
     private String PATH_TO_RESOURCES = "R/";
     @Argument(fullName="quality_step", shortName="qStep", doc="Resolution in QUAL units for optimization and tranche calculations", required=false)
     private double QUAL_STEP = 0.1;
@@ -115,6 +117,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
     private VariantOptimizationModel.Model OPTIMIZATION_MODEL = VariantOptimizationModel.Model.GAUSSIAN_MIXTURE_MODEL;
     private VariantGaussianMixtureModel theModel = null;
     private Set<String> ignoreInputFilterSet = null;
+    private Set<String> inputNames = new HashSet<String>();
 
     //---------------------------------------------------------------------------------------------------------------
     //
@@ -146,7 +149,6 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
         // setup the header fields
         final Set<VCFHeaderLine> hInfo = new HashSet<VCFHeaderLine>();
         final TreeSet<String> samples = new TreeSet<String>();
-        final List<ReferenceOrderedDataSource> dataSources = this.getToolkit().getRodDataSources();
         hInfo.addAll(VCFUtils.getHeaderFields(getToolkit()));
         hInfo.add(new VCFInfoHeaderLine("OQ", 1, VCFHeaderLineType.Float, "The original variant quality score"));
         hInfo.add(new VCFHeaderLine("source", "VariantOptimizer"));
@@ -156,10 +158,21 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
         vcfWriter.writeHeader(vcfHeader);
 
         boolean foundDBSNP = false;
-        for( final ReferenceOrderedDataSource source : dataSources ) {
-            final RMDTrack rod = source.getReferenceOrderedData();
-            if( rod.getName().equals(DbSNPHelper.STANDARD_DBSNP_TRACK_NAME) ) {
+        for( ReferenceOrderedDataSource d : this.getToolkit().getRodDataSources() ) {
+            if( d.getName().startsWith("input") ) {
+                inputNames.add(d.getName());
+                logger.info("Found input variant track with name " + d.getName());
+            } else if ( d.getName().equals(DbSNPHelper.STANDARD_DBSNP_TRACK_NAME) ) {
+                logger.info("Found dbSNP track with prior probability = Q" + PRIOR_DBSNP);
                 foundDBSNP = true;
+            } else if ( d.getName().equals("hapmap") ) {
+                logger.info("Found HapMap track with prior probability = Q" + PRIOR_HAPMAP);
+                foundDBSNP = true;
+            } else if ( d.getName().equals("1kg") ) {
+                logger.info("Found 1KG track for with prior probability = Q" + PRIOR_1KG);
+                foundDBSNP = true;
+            } else {
+                logger.info("Not evaluating ROD binding " + d.getName());
             }
         }
 
@@ -191,21 +204,33 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
             return mapList;
         }
 
-        for( final VariantContext vc : tracker.getAllVariantContexts(ref, null, context.getLocation(), false, false) ) {
-            if( vc != null && !vc.getName().equals(DbSNPHelper.STANDARD_DBSNP_TRACK_NAME) && vc.isSNP() ) {
+        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())) ) {
                     final VariantDatum variantDatum = new VariantDatum();
                     variantDatum.isTransition = VariantContextUtils.getSNPSubstitutionType(vc).compareTo(BaseUtils.BaseSubstitutionType.TRANSITION) == 0;
 
                     final DbSNPFeature dbsnp = DbSNPHelper.getFirstRealSNP(tracker.getReferenceMetaData(DbSNPHelper.STANDARD_DBSNP_TRACK_NAME));
-                    variantDatum.isKnown = dbsnp != null;
-                    variantDatum.alleleCount = vc.getChromosomeCount(vc.getAlternateAllele(0)); // BUGBUG: assumes file has genotypes. Also, what to do about tri-allelic sites?
+                    final VariantContext vcHapMap = tracker.getVariantContext(ref, "hapmap", null, context.getLocation(), false);
+                    final VariantContext vc1KG = tracker.getVariantContext(ref, "1kg", null, context.getLocation(), false);
 
-                    final double acPrior = theModel.getAlleleCountPrior( variantDatum.alleleCount );
-                    double knownPrior = variantDatum.isKnown ? QualityUtils.qualToProb(KNOWN_QUAL_PRIOR) : QualityUtils.qualToProb(NOVEL_QUAL_PRIOR);
-                    if(variantDatum.isKnown && DbSNPHelper.isHapmap( dbsnp ) ) {
-                        knownPrior = QualityUtils.qualToProb(HAPMAP_QUAL_PRIOR);
+                    variantDatum.isKnown = false;
+                    double knownPrior_qScore = PRIOR_NOVELS;
+                    if( vcHapMap != null ) {
+                        variantDatum.isKnown = true;
+                        knownPrior_qScore = PRIOR_HAPMAP;
+                    } else if( vc1KG != null ) {
+                        variantDatum.isKnown = true;
+                        knownPrior_qScore = PRIOR_1KG;
+                    } else if( dbsnp != null ) {
+                        variantDatum.isKnown = true;
+                        knownPrior_qScore = PRIOR_DBSNP;
                     }
+                    final double knownPrior = QualityUtils.qualToProb(knownPrior_qScore);
+
+                    final int alleleCount = vc.getChromosomeCount(vc.getAlternateAllele(0)); // BUGBUG: assumes file has genotypes. Also, what to do about tri-allelic sites?
+
+                    final double acPrior = theModel.getAlleleCountPrior( alleleCount );
                     final double totalPrior = 1.0 - ((1.0 - acPrior) * (1.0 - knownPrior));
 
                     if( MathUtils.compareDoubles(totalPrior, 1.0, 1E-8) == 0 || MathUtils.compareDoubles(totalPrior, 0.0, 1E-8) == 0 ) {
diff --git a/java/test/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrationWalkersIntegrationTest.java b/java/test/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrationWalkersIntegrationTest.java
index 532fc174c..843281fbc 100755
--- a/java/test/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrationWalkersIntegrationTest.java
+++ b/java/test/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrationWalkersIntegrationTest.java
@@ -14,7 +14,7 @@ public class VariantRecalibrationWalkersIntegrationTest extends WalkerTest {
     @Test
     public void testGenerateVariantClusters() {
         HashMap<String, String> e = new HashMap<String, String>();
-        e.put( validationDataLocation + "yri.trio.gatk_glftrio.intersection.annotated.filtered.chr1.vcf", "e6724946c3298b3d74bb1ba1396a9190" );
+        e.put( validationDataLocation + "yri.trio.gatk_glftrio.intersection.annotated.filtered.chr1.vcf", "79727fb46bb60be30eae2666e4f792b6" );
 
         for ( Map.Entry<String, String> entry : e.entrySet() ) {
             String vcf = entry.getKey();
@@ -28,6 +28,7 @@ public class VariantRecalibrationWalkersIntegrationTest extends WalkerTest {
                             " -L 1:1-100,000,000" +
                             " --ignore_filter GATK_STANDARD" +
                             " -an QD -an HRun -an SB" +
+                            " -weightDBSNP 1.0" +
                             " -clusterFile %s",
                     1, // just one output file
                     Arrays.asList(md5));
@@ -39,7 +40,7 @@ public class VariantRecalibrationWalkersIntegrationTest extends WalkerTest {
     @Test
     public void testVariantRecalibrator() {
         HashMap<String, String> e = new HashMap<String, String>();
-        e.put( validationDataLocation + "yri.trio.gatk_glftrio.intersection.annotated.filtered.chr1.vcf", "b97ab64b86ce8c8698855058d32853ce" );
+        e.put( validationDataLocation + "yri.trio.gatk_glftrio.intersection.annotated.filtered.chr1.vcf", "446f0de46f59344ec5579d0c8b54ee66" );
         
         for ( Map.Entry<String, String> entry : e.entrySet() ) {
             String vcf = entry.getKey();
@@ -61,7 +62,7 @@ public class VariantRecalibrationWalkersIntegrationTest extends WalkerTest {
                                 " -tranchesFile %s" +
                                 " -reportDatFile %s",                                
                         3, // two output file
-                        Arrays.asList(md5, "f603aa2052ae6e81a6bde63a8a3f9539","951a17f9c11de391763b9a8cb239205a"));
+                        Arrays.asList(md5, "d979864c46ae237f52f1002f0ec19b16","ab438d03e276a053d7534056f62c83f3"));
                 List<File> result = executeTest("testVariantRecalibrator", spec).getFirst();
                 inputVCFFiles.put(vcf, result.get(0).getAbsolutePath());
                 tranchesFiles.put(vcf, result.get(1).getAbsolutePath());
@@ -74,7 +75,7 @@ public class VariantRecalibrationWalkersIntegrationTest extends WalkerTest {
     @Test
     public void testApplyVariantCuts() {
         HashMap<String, String> e = new HashMap<String, String>();
-        e.put( validationDataLocation + "yri.trio.gatk_glftrio.intersection.annotated.filtered.chr1.vcf", "e80f26d68be2b183fd7f062039cef28a" );
+        e.put( validationDataLocation + "yri.trio.gatk_glftrio.intersection.annotated.filtered.chr1.vcf", "b25c2a563362897271bbee9db3f9c3af" );
 
         for ( Map.Entry<String, String> entry : e.entrySet() ) {
             String vcf = entry.getKey();