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Bioinformatics Advance Access published online on January 29, 2004
Bioinformatics, doi:10.1093/bioinformatics/bth011
Bioinformatics © Oxford University Press 2004; all rights reserved
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Received July 29, 2003
Revised October 15, 2003
Accepted October 16, 2003

Article

Finding coexpressed genes in counts-based data: an improved measure with validation experiments

Morgan N. Price 1* Eleanor Rieffel 1

1 FX Palo Alto Laboratory, 3400 Hillview Ave. Bldg. 4, Palo Alto CA 94304

* To whom correspondence should be addressed. E-mail: mprice{at}cs.cmu.edu.


  Abstract

Motivation: EST data reects variation in gene expression, but previous methods for finding coexpressed genes in EST data are subject to bias and vastly overstate the statistical significance of putatively coexpressed genes.

Results: We introduce a new method (LNP) that reports reasonable p-values and also detects more biological relationships in human dbEST than do previous methods. In simulations with human dbEST library sizes, previous methods report p-values as low as 10-30 on 1/1,000 uncorrelated pairs, while LNP reports significance correctly. We validate the analysis on real human genes by comparing coexpressed pairs to GO annotations and find that LNP is more sensitive than three previous methods. We also find a small but statistically significant level of coexpression between interacting proteins relative to randomized controls. The LNP method is based on a log-normal prior on the distribution of expression levels.

Availability: Source code in Java or R is available at http://ests.sourceforge.net/

Supplementary information: Included at the back; to be posted.


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