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Table 4 False positive rates

From: Comparison of small n statistical tests of differential expression applied to microarrays

   t-stat CyberT LPE BRB limma FC
HGU133A 22258 genes MAS 5.0 .064 .078 .060 .063 .062 .05
  RMA .069 .084 .044 .078 .078 .05
  gcRMA .050 .079 .031 .060 .061 .05
  dChip .093 .115 .081 .105 .105 .05
  LMGene .082 .099 .065 .095 .093 .05
  VSN .074 .091 .049 .091 .088 .05
HGU95 12614 genes MAS 5.0 .044 .05 .042 .046 .046 .05
  RMA .040 .037 .011 .035 .034 .05
  gcRMA .009 .018 .003 .017 .018 .05
  dChip .043 .041 .003 .040 .040 .05
  LMGene .040 .035 .008 .035 .033 .05
  VSN .040 .035 .008 .035 .033 .05
cDNA liver vs liver 27648 genes Loess .002 .001 0 .001 .001 .05
  Loess(BC) .01 .002 .001 .007 .007 .05
  glog Loess .007 .002 0 .002 .002 .05
  glog Loess(BC) .014 .008 .001 .011 .012 .05
  VSN .006 .001 0 .001 .001 .05
cDNA liver vs pool 27648 genes Loess .138 .135 .034 .151 .151 .05
  Loess(BC) .174 .171 .106 .169 .173 .05
  glog Loess .233 .238 .151 .251 .252 .05
  glog Loess(BC) .233 .235 .158 .238 .240 .05
  VSN .244 .249 .183 .251 .252 .05
Simulated 9900 genes Common .048 .048 .032 .046 .047 .05
  Local .044 .044 .028 .046 .045 .05
  Inverse Gamma .048 .053 .039 .048 .048 .05
  1. Average false positive rates (using a p value threshold of .05) of the six tests of differential expression. The LMGene package was used to apply the Loess normalization and glog transformation to the cDNA data. BC indicates that background correction was applied to the data before normalization.