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- Title
Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data.
- Authors
Martin, Dietmar E.; Demougin, Philippe; Hall, Michael N.; Bellis, Michel
- Abstract
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals between two biological conditions. Results: We describe a new method, Rank Difference Analysis of Microarrays (RDAM), which estimates the total number of truly varying genes and assigns a p-value to each signal variation. Information on a group of differentially expressed genes includes the sensitivity and the false discovery rate. We demonstrate the feasibility and efficiency of our approach by applying it to a large synthetic expression data set and to a biological data set obtained by comparing vegetatively-growing wild type and tor2-mutant yeast strains. In both cases we observed a significant improvement of the power of analysis when our method is compared to another popular nonparametric method. Conclusions: This study provided a valuable new statistical method to analyze microarray data. We conclude that the good quality of the results obtained by RDAM is mainly due to the quasi-perfect equalization of variation distribution, which is related to the standardization procedure used and to the measurement of variation by rank difference.
- Subjects
DNA microarrays; STATISTICS; GENES; GENE expression; BIOLOGY
- Publication
BMC Bioinformatics, 2004, Vol 5, p148
- ISSN
1471-2105
- Publication type
Article
- DOI
10.1186/1471-2105-5-148