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Bioinformatics. 2010 Feb 1;26(3):348-54. doi: 10.1093/bioinformatics/btp672. Epub 2009 Dec 8.

A new gene selection procedure based on the covariance distance.

Author information

  • 1Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Box 630, Rochester, NY 14642, USA. huruizg@hotmail.com

Abstract

MOTIVATION:

Very little attention has been given to gene selection procedures based on intergene correlation structure, which is often neglected in the context of differential gene expression analysis. We propose a statistical procedure to select genes that have different associations with others across different phenotypes. This procedure is based on a new gene association score, called the covariance distance.

RESULTS:

We apply the proposed method, along with two alternative methods, to several simulated datasets and find out that our method is much more powerful than the other two. For biological data, we demonstrate that the analysis of differentially associated genes complements the analysis of differentially expressed genes. Combining both procedures provides a more comprehensive functional interpretation of the experimental results.

AVAILABILITY:

The code is downloadable from http://www.urmc.rochester.edu/biostat/people/faculty/hu.cfm.

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
19996162
[PubMed - indexed for MEDLINE]
PMCID:
PMC2815661
Free PMC Article

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