Bivariate microarray analysis: statistical interpretation of two-channel functional genomics data.

ABSTRACT: Conventional statistical methods for interpreting microarray data require large numbers of replicates in order to provide sufficient levels of sensitivity. We recently described a method for identifying differentially-expressed genes in one-channel microarray data 1. Based on the idea that the variance structure of microarray data can itself be a reliable measure of noise, this method allows statistically sound interpretation of as few as two replicates per treatment condition. Unlike the one-channel array, the two-channel platform simultaneously compares gene expression in two RNA samples. This leads to covariation of the measured signals. Hence, by accounting for covariation in the variance model, we can significantly increase the power of the statistical test. We believe that this appro

SUBMITTER: Hsiao A 

PROVIDER: S-EPMC2735646 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature