diff --git a/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantDataManager.java b/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantDataManager.java
index d4304d147..1df3bc321 100644
--- a/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantDataManager.java
+++ b/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantDataManager.java
@@ -99,23 +99,37 @@ public class VariantDataManager {
         this.data = data;
     }
 
+    public void setNormalization(final Map<String, Double> anMeans, final Map<String, Double> anStdDevs) {
+        for (int i = 0; i < this.annotationKeys.size(); i++) {
+            meanVector[i] = anMeans.get(annotationKeys.get(i));
+            varianceVector[i] = anStdDevs.get(annotationKeys.get(i));
+        }
+    }
+
     public List<VariantDatum> getData() {
         return data;
     }
 
-    public void normalizeData() {
+    public void normalizeData(final boolean calculateMeans) {
         boolean foundZeroVarianceAnnotation = false;
         for( int iii = 0; iii < meanVector.length; iii++ ) {
-            final double theMean = mean(iii, true);
-            final double theSTD = standardDeviation(theMean, iii, true);
-            logger.info( annotationKeys.get(iii) + String.format(": \t mean = %.2f\t standard deviation = %.2f", theMean, theSTD) );
-            if( Double.isNaN(theMean) ) {
-                throw new UserException.BadInput("Values for " + annotationKeys.get(iii) + " annotation not detected for ANY training variant in the input callset. VariantAnnotator may be used to add these annotations.");
-            }
+            final double theMean, theSTD;
+            if (calculateMeans) {
+                theMean = mean(iii, true);
+                theSTD = standardDeviation(theMean, iii, true);
+                if (Double.isNaN(theMean)) {
+                    throw new UserException.BadInput("Values for " + annotationKeys.get(iii) + " annotation not detected for ANY training variant in the input callset. VariantAnnotator may be used to add these annotations.");
+                }
 
-            foundZeroVarianceAnnotation = foundZeroVarianceAnnotation || (theSTD < 1E-5);
-            meanVector[iii] = theMean;
-            varianceVector[iii] = theSTD;
+                foundZeroVarianceAnnotation = foundZeroVarianceAnnotation || (theSTD < 1E-5);
+                meanVector[iii] = theMean;
+                varianceVector[iii] = theSTD;
+            }
+            else {
+                theMean = meanVector[iii];
+                theSTD = varianceVector[iii];
+            }
+            logger.info(annotationKeys.get(iii) + String.format(": \t mean = %.2f\t standard deviation = %.2f", theMean, theSTD));
             for( final VariantDatum datum : data ) {
                 // Transform each data point via: (x - mean) / standard deviation
                 datum.annotations[iii] = ( datum.isNull[iii] ? 0.1 * Utils.getRandomGenerator().nextGaussian() : ( datum.annotations[iii] - theMean ) / theSTD );
diff --git a/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibrator.java b/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibrator.java
index 546c0f05b..4a03b568d 100644
--- a/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibrator.java
+++ b/protected/gatk-tools-protected/src/main/java/org/broadinstitute/gatk/tools/walkers/variantrecalibration/VariantRecalibrator.java
@@ -370,12 +370,18 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
             final GATKReportTable pmcTable = reportIn.getTable("PositiveModelCovariances");
             final GATKReportTable pmmTable = reportIn.getTable("PositiveModelMeans");
             final GATKReportTable pPMixTable = reportIn.getTable("GoodGaussianPMix");
+            final GATKReportTable anMeansTable = reportIn.getTable("AnnotationMeans");
+            final GATKReportTable anStDevsTable = reportIn.getTable("AnnotationStdevs");
             final int numAnnotations = dataManager.annotationKeys.size();
 
             if( numAnnotations != pmmTable.getNumColumns()-1 || numAnnotations != nmmTable.getNumColumns()-1 ) { // -1 because the first column is the gaussian number.
                 throw new UserException.CommandLineException( "Annotations specified on the command line do not match annotations in the model report." );
             }
 
+            final Map<String, Double> anMeans = getMapFromVectorTable(anMeansTable);
+            final Map<String, Double> anStdDevs = getMapFromVectorTable(anStDevsTable);
+            dataManager.setNormalization(anMeans, anStdDevs);
+
             goodModel = GMMFromTables(pmmTable, pmcTable, pPMixTable, numAnnotations);
             badModel = GMMFromTables(nmmTable, nmcTable, nPMixTable, numAnnotations);
         }
@@ -512,7 +518,7 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
         for (int i = 1; i <= max_attempts; i++) {
             try {
                 dataManager.setData(reduceSum);
-                dataManager.normalizeData(); // Each data point is now (x - mean) / standard deviation
+                dataManager.normalizeData(inputModel.isEmpty()); // Each data point is now (x - mean) / standard deviation
 
                 final List<VariantDatum> positiveTrainingData = dataManager.getTrainingData();
                 final List<VariantDatum> negativeTrainingData;
@@ -638,38 +644,18 @@ public class VariantRecalibrator extends RodWalker<ExpandingArrayList<VariantDat
 
     }
 
-    private double[] getStandardDeviationsFromTable(GATKReportTable astdTable){
-        double[] stdVector = {};
+    private Map<String, Double> getMapFromVectorTable(GATKReportTable vectorTable){
+        Map<String, Double> dataMap = new HashMap<>();
 
-        for (GATKReportColumn reportColumn : astdTable.getColumnInfo() ) {
-            if (reportColumn.getColumnName().equals("Standarddeviation")) {
-                stdVector = new double[astdTable.getNumRows()];
-                for (int row = 0; row < astdTable.getNumRows(); row++) {
-                    stdVector[row] =  (Double) astdTable.get(row, reportColumn.getColumnName());
-                }
-            }
+        //do a row-major traversal
+        for (int i = 0; i < vectorTable.getNumRows(); i++) {
+            dataMap.put((String) vectorTable.get(i, 0), (Double) vectorTable.get(i, 1));
         }
-
-        return stdVector;
-    }
-
-    private double[] getMeansFromTable(GATKReportTable amTable){
-        double[] meanVector = {};
-
-        for (GATKReportColumn reportColumn : amTable.getColumnInfo() ) {
-            if (reportColumn.getColumnName().equals("Mean")) {
-                meanVector = new double[amTable.getNumRows()];
-                for (int row = 0; row < amTable.getNumRows(); row++) {
-                    meanVector[row] = (Double) amTable.get(row, reportColumn.getColumnName());
-                }
-            }
-        }
-
-        return meanVector;
+        return dataMap;
     }
 
     protected GATKReport writeModelReport(final GaussianMixtureModel goodModel, final GaussianMixtureModel badModel, List<String> annotationList) {
-        final String formatString = "%.8E";
+        final String formatString = "%.16E";
         final GATKReport report = new GATKReport();
 
         if (dataManager != null) {  //for unit test