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DNA Research Advance Access originally published online on September 18, 2009
DNA Research 2009 16(5):249-260; doi:10.1093/dnares/dsp016
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© The Author 2009. Published by Oxford University Press on behalf of Kazusa DNA Research Institute
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Rank of Correlation Coefficient as a Comparable Measure for Biological Significance of Gene Coexpression

Takeshi Obayashi1 and Kengo Kinoshita1,2,*

1 Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan
2 Institute for Bioinformatics Research and Development, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012, Japan

Received 30 March 2009 ; accepted 14 August 2009.

Information regarding gene coexpression is useful to predict gene function. Several databases have been constructed for gene coexpression in model organisms based on a large amount of publicly available gene expression data measured by GeneChip platforms. In these databases, Pearson's correlation coefficients (PCCs) of gene expression patterns are widely used as a measure of gene coexpression. Although the coexpression measure or GeneChip summarization method affects the performance of the gene coexpression database, previous studies for these calculation procedures were tested with only a small number of samples and a particular species. To evaluate the effectiveness of coexpression measures, assessments with large-scale microarray data are required. We first examined characteristics of PCC and found that the optimal PCC threshold to retrieve functionally related genes was affected by the method of gene expression database construction and the target gene function. In addition, we found that this problem could be overcome when we used correlation ranks instead of correlation values. This observation was evaluated by large-scale gene expression data for four species: Arabidopsis, human, mouse and rat.

Key words: gene coexpression; Pearson's correlation coefficient; GeneChip summarization; Arabidopsis

* To whom correspondence should be addressed. Tel. +81 3-5449-5131. Fax. +81 3-5449-5133. E-mail: kino{at}ims.u-tokyo.ac.jp


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