Evaluation of gene association methods for coexpression network construction and biological knowledge discovery.

ABSTRACT:

Background

Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical.

Methods and results

In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes

SUBMITTER: Kumari S 

PROVIDER: S-EPMC3511551 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature