Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data.

ABSTRACT:

Background

Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, classical t-statistic and moderated t-statistics. Even though these methods return gene lists that are often dissimilar, few direct comparisons of these exist. We present an empirical study in which we compare some of the most commonly used feature selection methods. We apply these to 9 publicly available datasets, and compare, both the gene lists produced and how these perform in class prediction of test datasets.

Results

In this study, we compared the efficiency of the feature selection methods; significance analysis of microarrays (SAM), analysis of variance (ANOVA), empirical bayes t-statistic, templ

SUBMITTER: Jeffery IB 

PROVIDER: S-EPMC1544358 | biostudies-literature | 2006 Jul

REPOSITORIES: biostudies-literature