Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data

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 vegetativelygrowing 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 tha...

• Type: Journal
• Year: 2004
• Where: BMCBI
• Authors: Dietmar E. Martin, Philippe Demougin, Michael N. Hall, Michel Bellis
• Keywords: BMCBI 2004, Popular Nonparametric Method, Rank Difference, Rank Difference Analysis