Robust gene network analysis reveals alteration of the STAT5a network as a hallmark of prostate cancer.

ABSTRACT: We develop a general method to identify gene networks from pair-wise correlations between genes in a microarray data set and apply it to a public prostate cancer gene expression data from 69 primary prostate tumors. We define the degree of a node as the number of genes significantly associated with the node and identify hub genes as those with the highest degree. The correlation network was pruned using transcription factor binding information in VisANT (http://visant.bu.edu/) as a biological filter. The reliability of hub genes was determined using a strict permutation test. Separate networks for normal prostate samples, and prostate cancer samples from African Americans (AA) and European Americans (EA) were generated and compared. We found that the same hubs control disease progression i

SUBMITTER: Reddy A 

PROVIDER: S-EPMC6035043 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature