diff --git a/tools/multivariate_stats/cca.py b/tools/multivariate_stats/cca.py
index 5ea69c6cb57..32f41c859d8 100644
--- a/tools/multivariate_stats/cca.py
+++ b/tools/multivariate_stats/cca.py
@@ -124,33 +124,33 @@ for i in range(ncomps):
 
 ftest=ftest.as_py()
 print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
-print >>fout, "#Correlation\t%s" %("\t".join(["%s" % el for el in corr]))
-print >>fout, "#F-statistic\t%s" %("\t".join(["%s" % el for el in ftest['statistic']]))
-print >>fout, "#p-value\t%s" %("\t".join(["%s" % el for el in ftest['p.value']]))
+print >>fout, "#Correlation\t%s" %("\t".join(["%.4g" % el for el in corr]))
+print >>fout, "#F-statistic\t%s" %("\t".join(["%.4g" % el for el in ftest['statistic']]))
+print >>fout, "#p-value\t%s" %("\t".join(["%.4g" % el for el in ftest['p.value']]))
 
 print >>fout, "#X-Coefficients\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for i,val in enumerate(summary['xcoef']):
-    print >>fout, "%s\t%s" %(xlab[i], "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(xlab[i], "\t".join(["%.4g" % el for el in val]))
 
 print >>fout, "#Y-Coefficients\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for i,val in enumerate(summary['ycoef']):
-    print >>fout, "%s\t%s" %(ylab[i], "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(ylab[i], "\t".join(["%.4g" % el for el in val]))
        
 print >>fout, "#X-Loadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for i,val in enumerate(summary['xstructcorr']):
-    print >>fout, "%s\t%s" %(xlab[i], "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(xlab[i], "\t".join(["%.4g" % el for el in val]))
 
 print >>fout, "#Y-Loadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for i,val in enumerate(summary['ystructcorr']):
-    print >>fout, "%s\t%s" %(ylab[i], "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(ylab[i], "\t".join(["%.4g" % el for el in val]))
 
 print >>fout, "#X-CrossLoadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for i,val in enumerate(summary['xcrosscorr']):
-    print >>fout, "%s\t%s" %(xlab[i], "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(xlab[i], "\t".join(["%.4g" % el for el in val]))
 
 print >>fout, "#Y-CrossLoadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for i,val in enumerate(summary['ycrosscorr']):
-    print >>fout, "%s\t%s" %(ylab[i], "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(ylab[i], "\t".join(["%.4g" % el for el in val]))
 
 r.pdf( outfile2, 8, 8 )
 #r.plot(cc)
diff --git a/tools/multivariate_stats/kcca.py b/tools/multivariate_stats/kcca.py
index 620ba862ca9..ac63946e4f8 100644
--- a/tools/multivariate_stats/kcca.py
+++ b/tools/multivariate_stats/kcca.py
@@ -135,12 +135,12 @@ ycoef = r.ycoef(kcc)
 
 print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 
-print >>fout, "#Correlation\t%s" %("\t".join(["%s" % el for el in kcor]))
+print >>fout, "#Correlation\t%s" %("\t".join(["%.4g" % el for el in kcor]))
     
 print >>fout, "#Estimated X-coefficients\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for obs,val in enumerate(xcoef):
-    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
 
 print >>fout, "#Estimated Y-coefficients\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for obs,val in enumerate(ycoef):
-    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
diff --git a/tools/multivariate_stats/kpca.py b/tools/multivariate_stats/kpca.py
index e9987c159a0..8edd2a1ff30 100644
--- a/tools/multivariate_stats/kpca.py
+++ b/tools/multivariate_stats/kpca.py
@@ -116,15 +116,15 @@ for i in range(ncomps):
 
 print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 
-print >>fout, "#Eigenvalue\t%s" %("\t".join(["%s" % el for el in eig.values()]))
+print >>fout, "#Eigenvalue\t%s" %("\t".join(["%.4g" % el for el in eig.values()]))
     
 print >>fout, "#Principal component vectors\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for obs,val in enumerate(pcv):
-    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
 
 print >>fout, "#Rotated values\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 for obs,val in enumerate(rotated):
-    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in val]))
 
 r.pdf( outfile2, 8, 8 )
 if ncomps != 1:
diff --git a/tools/multivariate_stats/pca.py b/tools/multivariate_stats/pca.py
index 7b1db8a6a85..f6824d5b71d 100644
--- a/tools/multivariate_stats/pca.py
+++ b/tools/multivariate_stats/pca.py
@@ -40,13 +40,18 @@ for ind,line in enumerate( file( infile )):
     if line and not line.startswith( '#' ):
         try:
             fields = line.strip().split("\t")
+            valid_line = True
             for k,col in enumerate(x_cols):
                 try:
                     xval = float(fields[col])
                 except:
-                    #xval = r('NA')
-                    xval = NaN#
-                x_vals[k].append(xval)
+                    skipped += 1 
+                    valid_line = False
+                    break
+            if valid_line:
+                for k,col in enumerate(x_cols):
+                    xval = float(fields[col])
+                    x_vals[k].append(xval)
         except:
             skipped += 1
 
@@ -71,7 +76,7 @@ for i in range(ncomps):
     sd[comps.index('Comp.%s' %(i+1))] = summary['sdev'].values()[i]
 
 print >>fout, "#Component\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
-print >>fout, "#Std. deviation\t%s" %("\t".join(["%s" % el for el in sd]))
+print >>fout, "#Std. deviation\t%s" %("\t".join(["%.4g" % el for el in sd]))
 total_var = 0
 vars = []
 for s in sd:
@@ -81,17 +86,17 @@ for s in sd:
 for i,var in enumerate(vars):
     vars[i] = vars[i]/total_var
        
-print >>fout, "#Proportion of variance explained\t%s" %("\t".join(["%s" % el for el in vars]))
+print >>fout, "#Proportion of variance explained\t%s" %("\t".join(["%.4g" % el for el in vars]))
 
 print >>fout, "#Loadings\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 xcolnames = ["c%d" %(el+1) for el in x_cols]
 for i,val in enumerate(summary['loadings']):
-    print >>fout, "%s\t%s" %(xcolnames[i], "\t".join(["%s" % el for el in val]))
+    print >>fout, "%s\t%s" %(xcolnames[i], "\t".join(["%.4g" % el for el in val]))
 
 print >>fout, "#Scores\t%s" %("\t".join(["%s" % el for el in range(1,ncomps+1)]))
 
 for obs,sc in enumerate(summary['scores']):
-    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%s" % el for el in sc]))
+    print >>fout, "%s\t%s" %(obs+1, "\t".join(["%.4g" % el for el in sc]))
 
 r.pdf( outfile2, 8, 8 )
 r.biplot(pc)