Improving detection of differentially expressed gene sets by applying cluster enrichment analysis to Gene Ontology.

ABSTRACT:

Background

Gene set analysis based on Gene Ontology (GO) can be a promising method for the analysis of differential expression patterns. However, current studies that focus on individual GO terms have limited analytical power, because the complex structure of GO introduces strong dependencies among the terms, and some genes that are annotated to a GO term cannot be found by statistically significant enrichment.

Results

We proposed a method for enriching clustered GO terms based on semantic similarity, namely cluster enrichment analysis based on GO (CeaGO), to extend the individual term analysis method. Using an Affymetrix HGU95aV2 chip dataset with simulated gene sets, we illustrated that CeaGO was sensitive enough to detect moderate expression changes. When compared to pare

SUBMITTER: Xu T 

PROVIDER: S-EPMC2731756 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature