Ranking analysis of F-statistics for microarray data.

ABSTRACT:

Background

Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, identification of genes differentially expressed in microarray experiments is challenging because of their potentially high type I error rate. Methods for large-scale statistical analyses have been developed but most of them are applicable to two-sample or two-condition data.

Results

We developed a large-scale multiple-group F-test based method, named ranking analysis of F-statistics (RAF), which is an extension of ranking analysis of microarray data (RAM) for two-sample t-test. In this method, we proposed a novel random splitting approach to generate the null distribution instead of using permutation,

SUBMITTER: Tan YD 

PROVIDER: S-EPMC2323973 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature