Coexpression Analysis of Human Genes Across Many Microarray Data Sets

Overview

Journal Genome Res

Specialty Genetics

Date 2004 Jun 3

PMID 15173114

Citations 399

Authors

Homin K Lee

Amy K Hsu

Jon Sajdak

Jie Qin

Paul Pavlidis

Affiliations

Soon will be listed here.

Abstract

We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function.

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