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Significance analysis of microarrays applied to the ionizing radiation response

Proceedings of the National Academy of Sciences · 2001 · Vol. 98(9) · pp. 5116–5121
Virginia Goss TusherRobert TibshiraniGilbert Chu

Abstract

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.

Gene expression and cancer classificationGenomics and Chromatin DynamicsMolecular Biology Techniques and ApplicationsDNA microarrayGeneSignificance analysis of microarraysBiologyIonizing radiationGene expressionDNA repairGeneticsMicroarrayGene expression profiling

MeSH terms

Cell CycleDNA DamageDNA RepairGene Expression RegulationHumansRadiation, IonizingRNA, MessengerStatistics as TopicTumor Cells, CulturedReproducibility of ResultsDown-RegulationUp-RegulationApoptosisOligonucleotide Array Sequence AnalysisGene Expression Profiling
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References
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1995 · 106,483 citations
Cluster analysis and display of genome-wide expression patterns
Proceedings of the National Academy of Sciences · 1998 · 16,353 citations
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