CARMA: A platform for analyzing microarray datasets that incorporate replicate measures

Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust experimental design coupled with an analysis of variance (ANOVA) incorporating a model that accounts for known sources of experimental variability can significantly improve the determination of differences in gene expression and estimations of their significance. Results: To realize the full benefits of performing analysis of variance on microarray data we have developed CARMA, a microarray analysis platform that reads data files generated by most microarray image processing software packages, performs ANOVA using a user-defined linear model, and produces easily interpretable graphical and numeric results. No pre-processing of the data is required and user-specified parameters control most aspects of the analysis including statistical significance criterion. The software also performs location and intensity dep...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Kevin A. Greer, Matthew R. McReynolds, Heddwen L. Brooks, James B. Hoying
• Keywords: Analysis, BMCBI 2006, Microarray Analysis Platform, Microarray Data