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 5c9a86fea..c210ef699 100755
--- a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantGaussianMixtureModel.java
+++ b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantGaussianMixtureModel.java
@@ -65,9 +65,10 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
 
     private final double[][] mu; // The means for each cluster
     private final Matrix[] sigma; // The covariance matrix for each cluster
-    private final Matrix[] sigmaInverse;
+    private final double[][][] sigmaInverse;
     private double[] pClusterLog10;
     private final double[] determinant;
+    private final double[] sqrtDeterminantLog10;
     private final double stdThreshold;
     private double singletonFPRate = -1; // Estimated FP rate for singleton calls.  Used to estimate FP rate as a function of AC
 
@@ -78,6 +79,8 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
     private final double[] hyperParameter_b;
     private final double[] hyperParameter_lambda;
 
+    private final double CONSTANT_GAUSSIAN_DENOM_LOG10;
+
     private static final Pattern COMMENT_PATTERN = Pattern.compile("^##.*");
     private static final Pattern ANNOTATION_PATTERN = Pattern.compile("^@!ANNOTATION.*");
     private static final Pattern CLUSTER_PATTERN = Pattern.compile("^@!CLUSTER.*");
@@ -93,10 +96,12 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
         sigma = null;
         sigmaInverse = null;
         determinant = null;
+        sqrtDeterminantLog10 = null;
         stdThreshold = 0;
         hyperParameter_a = null;
         hyperParameter_b = null;
         hyperParameter_lambda = null;
+        CONSTANT_GAUSSIAN_DENOM_LOG10 = 0.0;
     }
 
     public VariantGaussianMixtureModel( final VariantDataManager _dataManager, final int _maxGaussians, final int _maxIterations,
@@ -108,6 +113,7 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
         mu = new double[maxGaussians][];
         sigma = new Matrix[maxGaussians];
         determinant = new double[maxGaussians];
+        sqrtDeterminantLog10 = null;
         pClusterLog10 = new double[maxGaussians];
         stdThreshold = _stdThreshold;
         FORCE_INDEPENDENT_ANNOTATIONS = _forceIndependent;
@@ -116,6 +122,7 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
         hyperParameter_lambda = new double[maxGaussians];
         sigmaInverse = null; // This field isn't used during GenerateVariantClusters pass
 
+        CONSTANT_GAUSSIAN_DENOM_LOG10 =  Math.log10(Math.pow(2.0 * Math.PI, ((double)dataManager.numAnnotations) / 2.0));
         SHRINKAGE = _shrinkage;
         DIRICHLET_PARAMETER = _dirichlet;
     }
@@ -149,15 +156,17 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
         hyperParameter_a = null;
         hyperParameter_b = null;
         hyperParameter_lambda = null;
+        determinant = null;
 
         // BUGBUG: move this parsing out of the constructor
+        CONSTANT_GAUSSIAN_DENOM_LOG10 =  Math.log10(Math.pow(2.0 * Math.PI, ((double)dataManager.numAnnotations) / 2.0));
         maxGaussians = clusterLines.size();
         mu = new double[maxGaussians][dataManager.numAnnotations];
         final double sigmaVals[][][] = new double[maxGaussians][dataManager.numAnnotations][dataManager.numAnnotations];
         sigma = new Matrix[maxGaussians];
-        sigmaInverse = new Matrix[maxGaussians];
+        sigmaInverse = new double[maxGaussians][dataManager.numAnnotations][dataManager.numAnnotations];
         pClusterLog10 = new double[maxGaussians];
-        determinant = new double[maxGaussians];
+        sqrtDeterminantLog10 = new double[maxGaussians];
 
         int kkk = 0;
         for( final String line : clusterLines ) {
@@ -171,8 +180,8 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
             }
             
             sigma[kkk] = new Matrix(sigmaVals[kkk]);
-            sigmaInverse[kkk] = sigma[kkk].inverse(); // Precompute all the inverses and determinants for use later
-            determinant[kkk] = sigma[kkk].det();
+            sigmaInverse[kkk] = sigma[kkk].inverse().getArray(); // Precompute all the inverses and determinants for use later
+            sqrtDeterminantLog10[kkk] = Math.log10(Math.pow(sigma[kkk].det(), 0.5)); // Precompute for use later
             kkk++;
         }
 
@@ -381,7 +390,7 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
 
             logger.info("Finished iteration " + ttt );
             ttt++;
-            if( Math.abs(currentLikelihood - previousLikelihood) < MIN_PROB_CONVERGENCE) {
+            if( Math.abs(currentLikelihood - previousLikelihood) < MIN_PROB_CONVERGENCE ) {
                 logger.info("Convergence!");
                 break;
             }
@@ -452,59 +461,6 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
         return sum;
     }
 
-   public final void outputClusterReports( final String outputPrefix ) {
-        final double STD_STEP = 0.2;
-        final double MAX_STD = 4.0;
-        final double MIN_STD = -4.0;
-        final int NUM_BINS = (int)Math.floor((Math.abs(MIN_STD) + Math.abs(MAX_STD)) / STD_STEP);
-        final int numAnnotations = dataManager.numAnnotations;
-        int totalCountsKnown = 0;
-        int totalCountsNovel = 0;
-
-        final int counts[][][] = new int[numAnnotations][NUM_BINS][2];
-        for( int jjj = 0; jjj < numAnnotations; jjj++ ) {
-            for( int iii = 0; iii < NUM_BINS; iii++ ) {
-                counts[jjj][iii][0] = 0;
-                counts[jjj][iii][1] = 0;
-            }
-        }
-
-        for( final VariantDatum datum : dataManager.data ) {
-            final int isKnown = ( datum.isKnown ? 1 : 0 );
-            for( int jjj = 0; jjj < numAnnotations; jjj++ ) {
-                int histBin = (int)Math.round((datum.annotations[jjj]-MIN_STD) * (1.0 / STD_STEP));
-                if(histBin < 0) { histBin = 0; }
-                if(histBin > NUM_BINS-1) { histBin = NUM_BINS-1; }
-                if(histBin >= 0 && histBin <= NUM_BINS-1) {
-                    counts[jjj][histBin][isKnown]++;
-                }
-            }
-            if( isKnown == 1 ) { totalCountsKnown++; }
-            else { totalCountsNovel++; }
-        }
-
-        int annIndex = 0;
-        for( final String annotation : dataManager.annotationKeys ) {
-            PrintStream outputFile;
-            File file = new File(outputPrefix + "." + annotation + ".dat");
-            try {
-                outputFile = new PrintStream( file );
-            } catch (FileNotFoundException e) {
-                throw new UserException.CouldNotCreateOutputFile( file, e );
-            }
-
-            outputFile.println("annotationValue,knownDist,novelDist");
-
-            for( int iii = 0; iii < NUM_BINS; iii++ ) {
-                final double annotationValue = (((double)iii * STD_STEP)+MIN_STD) * dataManager.varianceVector[annIndex] + dataManager.meanVector[annIndex];
-                outputFile.println( annotationValue + "," + ( ((double)counts[annIndex][iii][1])/((double)totalCountsKnown) ) +
-                                                      "," + ( ((double)counts[annIndex][iii][0])/((double)totalCountsNovel) ));
-            }
-
-            annIndex++;
-        }
-    }
-
     public final void outputOptimizationCurve( final VariantDatum[] data, final PrintStream outputReportDatFile, final PrintStream tranchesOutputFile,
                                                final int desiredNumVariants, final Double[] FDRtranches, final double QUAL_STEP ) {
 
@@ -721,9 +677,8 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
 
         final int numAnnotations = annotations.length;
 
-        final double evalGaussianPDFLog10[] = new double[maxGaussians];
         for( int kkk = 0; kkk < maxGaussians; kkk++ ) {
-            final double sigmaVals[][] = sigmaInverse[kkk].getArray();
+            final double sigmaVals[][] = sigmaInverse[kkk];
             double sum = 0.0;
             for( int jjj = 0; jjj < numAnnotations; jjj++ ) {
                 double value = 0.0;
@@ -733,15 +688,14 @@ public final class VariantGaussianMixtureModel extends VariantOptimizationModel
                     final double mySigma = sigmaVals[ppp][jjj];
                     value += (myAnn - myMu) * mySigma;
                 }
-                double jNorm = annotations[jjj] - mu[kkk][jjj];
-                double prod = value * jNorm;
+                final double jNorm = annotations[jjj] - mu[kkk][jjj];
+                final double prod = value * jNorm;
                 sum += prod;
             }
 
-            final double log10SqrtDet = Math.log10(Math.pow(determinant[kkk], 0.5));
-            final double denomLog10 = Math.log10(Math.pow(2.0 * Math.PI, ((double)numAnnotations) / 2.0)) + log10SqrtDet;
-            evalGaussianPDFLog10[kkk] = (( -0.5 * sum ) / Math.log(10.0)) - denomLog10;
-            double pVar1 = Math.pow(10.0, pClusterLog10[kkk] + evalGaussianPDFLog10[kkk]);
+            final double denomLog10 = CONSTANT_GAUSSIAN_DENOM_LOG10 + sqrtDeterminantLog10[kkk];
+            final double evalGaussianPDFLog10 = (( -0.5 * sum ) / Math.log(10.0)) - denomLog10;
+            final double pVar1 = Math.pow(10.0, pClusterLog10[kkk] + evalGaussianPDFLog10);
             pVarInCluster[kkk] = pVar1;
         }
 
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 227880ef3..1fc8d7bc5 100755
--- a/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrator.java
+++ b/java/src/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrator.java
@@ -38,6 +38,7 @@ import org.broadinstitute.sting.gatk.refdata.utils.helpers.DbSNPHelper;
 import org.broadinstitute.sting.gatk.walkers.RodWalker;
 import org.broadinstitute.sting.utils.*;
 import org.broadinstitute.sting.utils.collections.ExpandingArrayList;
+import org.broadinstitute.sting.utils.collections.NestedHashMap;
 import org.broadinstitute.sting.utils.exceptions.UserException;
 import org.broadinstitute.sting.utils.vcf.VCFUtils;
 
@@ -70,7 +71,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
     private PrintStream TRANCHES_FILE;
     @Output(fullName="report_dat_file", shortName="reportDatFile", doc="The output report .dat file used with Rscript to create the optimization curve PDF file", required=true)
     private File REPORT_DAT_FILE;
-    @Output(doc="File to which recalibrated variants should be written",required=true)
+    @Output(doc="File to which recalibrated variants should be written", required=true)
     private VCFWriter vcfWriter = null;
 
     /////////////////////////////
@@ -106,6 +107,8 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
     private double SINGLETON_FP_RATE = 0.5;
     @Argument(fullName="quality_scale_factor", shortName="qScale", doc="Multiply all final quality scores by this value. Needed to normalize the quality scores.", required=false)
     private double QUALITY_SCALE_FACTOR = 100.0;
+    @Argument(fullName="dontTrustACField", shortName="dontTrustACField", doc="If specified the VR will not use the AC field and will instead always parse the genotypes to figure out how many variant chromosomes there are at a given site.", required=false)
+    private boolean NEVER_TRUST_AC_FIELD = false;
 
     /////////////////////////////
     // Debug Arguments
@@ -121,6 +124,8 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
     private VariantGaussianMixtureModel theModel = null;
     private Set<String> ignoreInputFilterSet = null;
     private Set<String> inputNames = new HashSet<String>();
+    private NestedHashMap priorCache = new NestedHashMap();
+    private boolean trustACField = false;
 
     //---------------------------------------------------------------------------------------------------------------
     //
@@ -228,26 +233,56 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
                     } else if( dbsnp != null ) {
                         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 we can trust the AC field then use it instead of parsing all the genotypes. Results in a substantial speed up.
+                    final int alleleCount = (trustACField ? Integer.parseInt(vc.getAttribute("AC",-1).toString()) : vc.getChromosomeCount(vc.getAlternateAllele(0)));
+                    if( !trustACField && !NEVER_TRUST_AC_FIELD ) {
+                        if( !vc.getAttributes().containsKey("AC") ) {
+                            NEVER_TRUST_AC_FIELD = true;
+                        } else {
+                            if( alleleCount == Integer.parseInt( vc.getAttribute("AC").toString()) ) {
+                                // The AC field is correct at this record so we trust it forever
+                                trustACField = true;
+                            } else { // We found a record in which the AC field wasn't correct but we are trying to trust it
+                                throw new UserException.BadInput("AC info field doesn't match the variant chromosome count so we can't trust it! Please run with --dontTrustACField which will force the walker to parse the genotypes for each record, drastically increasing the runtime." +
+                                            "First observed at " + vc.getChr() + ":" + vc.getStart());
+                            }
+                        }
+                    }
+                    if( trustACField && alleleCount == -1 ) {
+                        throw new UserException.BadInput("AC info field doesn't exist for all records (although it does for some) so we can't trust it! Please run with --dontTrustACField which will force the walker to parse the genotypes for each record, drastically increasing the runtime." +
+                                "First observed at " + vc.getChr() + ":" + vc.getStart());
+                    }
 
-                    if( MathUtils.compareDoubles(totalPrior, 1.0, 1E-8) == 0 || MathUtils.compareDoubles(totalPrior, 0.0, 1E-8) == 0 ) {
-                        throw new UserException.CommandLineException("Something is wrong with the prior that was entered by the user:  Prior = " + totalPrior); // TODO - fix this up later
+                    final Object[] priorKey = new Object[2];
+                    priorKey[0] = alleleCount;
+                    priorKey[1] = knownPrior_qScore;
+
+                    Double priorLodFactor = (Double)priorCache.get( priorKey );
+
+                    // If this prior factor hasn't been calculated before, do so now
+                    if(priorLodFactor == null) {
+                        final double knownPrior = QualityUtils.qualToProb(knownPrior_qScore);
+                        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 ) {
+                            throw new UserException.CommandLineException("Something is wrong with the prior that was entered by the user:  Prior = " + totalPrior); // TODO - fix this up later
+                        }
+
+                        priorLodFactor = Math.log10(totalPrior) - Math.log10(1.0 - totalPrior) - Math.log10(1.0);
+
+                        priorCache.put( priorLodFactor, false, priorKey );
                     }
 
                     final double pVar = theModel.evaluateVariant( vc );
-
-                    final double lod = (Math.log10(totalPrior) + Math.log10(pVar)) - ((Math.log10(1.0 - totalPrior)) + Math.log10(1.0));
+                    final double lod = priorLodFactor + Math.log10(pVar);
                     variantDatum.qual = Math.abs( QUALITY_SCALE_FACTOR * QualityUtils.lodToPhredScaleErrorRate(lod) );
 
                     mapList.add( variantDatum );
-
-                    Map<String, Object> attrs = new HashMap<String, Object>(vc.getAttributes());
-                    attrs.put("OQ", String.format("%.2f", ((Double)vc.getPhredScaledQual())));
+                    final Map<String, Object> attrs = new HashMap<String, Object>(vc.getAttributes());
+                    attrs.put("OQ", String.format("%.2f", vc.getPhredScaledQual()));
                     attrs.put("LOD", String.format("%.4f", lod));
                     VariantContext newVC = VariantContext.modifyPErrorFiltersAndAttributes(vc, variantDatum.qual / 10.0, new HashSet<String>(), attrs);
 
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 a0a6d4d49..49e50f43c 100755
--- a/java/test/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrationWalkersIntegrationTest.java
+++ b/java/test/org/broadinstitute/sting/gatk/walkers/variantrecalibration/VariantRecalibrationWalkersIntegrationTest.java
@@ -46,7 +46,7 @@ public class VariantRecalibrationWalkersIntegrationTest extends WalkerTest {
     public void testVariantRecalibrator() {
         HashMap<String, List<String>> e = new HashMap<String, List<String>>();
         e.put( validationDataLocation + "yri.trio.gatk_glftrio.intersection.annotated.filtered.chr1.vcf",
-                Arrays.asList("0c6b5085a678b6312ab4bc8ce7b4eee4", "038c31c5bb46a4df89b8ee69ec740812","7d42bbdfb69fdfb18cbda13a63d92602")); // Each test checks the md5 of three output files
+                Arrays.asList("e94b02016e6f7936999f02979b801c30", "038c31c5bb46a4df89b8ee69ec740812","7d42bbdfb69fdfb18cbda13a63d92602")); // Each test checks the md5 of three output files
         e.put( validationDataLocation + "lowpass.N3.chr1.raw.vcf",
                 Arrays.asList("bbdffb7fa611f4ae80e919cdf86b9bc6", "661360e85392af9c97e386399871854a","371e5a70a4006420737c5ab259e0e23e")); // Each test checks the md5 of three output files
 
@@ -84,7 +84,7 @@ 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", "7429ed494131eb1dab5a9169cf65d1f0" );
+        e.put( validationDataLocation + "yri.trio.gatk_glftrio.intersection.annotated.filtered.chr1.vcf", "e06aa6b734cc3c881d95cf5ee9315664" );
         e.put( validationDataLocation + "lowpass.N3.chr1.raw.vcf", "ad8661cba3b04a7977c97a541fd8a668" );
 
         for ( Map.Entry<String, String> entry : e.entrySet() ) {