ESEA: Discovering the Dysregulated Pathways based on Edge Set Enrichment Analysis.

ABSTRACT: Pathway analyses are playing an increasingly important role in understanding biological mechanism, cellular function and disease states. Current pathway-identification methods generally focus on only the changes of gene expression levels; however, the biological relationships among genes are also the fundamental components of pathways, and the dysregulated relationships may also alter the pathway activities. We propose a powerful computational method, Edge Set Enrichment Analysis (ESEA), for the identification of dysregulated pathways. This provides a novel way of pathway analysis by investigating the changes of biological relationships of pathways in the context of gene expression data. Simulation studies illustrate the power and performance of ESEA under various simulated conditions. Usi

SUBMITTER: Han J 

PROVIDER: S-EPMC4533315 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature