Microarrays can measure the expression of
thousands of genes to identify changes in expression between different
biological states. Methods are needed to determine the significance of
these changes while accounting for the enormous number of genes. We
describe a method, Significance Analysis of Microarrays (SAM), that
assigns a score to each gene on the basis of change in gene expression
relative to the standard deviation of repeated measurements. For genes
with scores greater than an adjustable threshold, SAM uses permutations
of the repeated measurements to estimate the percentage of genes
identified by chance, the false discovery rate (FDR). When the
transcriptional response of human cells to ionizing radiation was
measured by microarrays, SAM identified 34 genes that changed at least
1.5-fold with an estimated FDR of 12%, compared with FDRs of 60 and
84% by using conventional methods of analysis. Of the 34 genes, 19
were involved in cell cycle regulation and 3 in apoptosis.
Surprisingly, four nucleotide excision repair genes were induced,
suggesting that this repair pathway for UV-damaged DNA might play a
previously unrecognized role in repairing DNA damaged by ionizing
radiation.