A general co-expression network-based approach to gene expression analysis: comparison and applications.

ABSTRACT:

Background

Co-expression network-based approaches have become popular in analyzing microarray data, such as for detecting functional gene modules. However, co-expression networks are often constructed by ad hoc methods, and network-based analyses have not been shown to outperform the conventional cluster analyses, partially due to the lack of an unbiased evaluation metric.

Results

Here, we develop a general co-expression network-based approach for analyzing both genes and samples in microarray data. Our approach consists of a simple but robust rank-based network construction method, a parameter-free module discovery algorithm and a novel reference network-based metric for module evaluation. We report some interesting topological properties of rank-based co-expression network

SUBMITTER: Ruan J 

PROVIDER: S-EPMC2829495 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature