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Bioinformatics Advance Access originally published online on November 15, 2007
Bioinformatics 2008 24(2):265-271; doi:10.1093/bioinformatics/btm558
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Gaining confidence in biological interpretation of the microarray data: the functional consistence of the significant GO categories

Da Yang 1,{dagger}, Yanhui Li 2,{dagger}, Hui Xiao 1,{dagger}, Qing Liu 1, Min Zhang 1, Jing Zhu 2, Wencai Ma 1, Chen Yao 1, Jing Wang 1, Dong Wang 1, Zheng Guo 1,2,* and Baofeng Yang 1

1Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086 and 2Bioinformatics Centre and School of Life Science, University of Electronic Science and Technology of China, Chengdu, 610054, China

*To whom correspondence should be addressed.


  Abstract

Motivation: In microarray studies, numerous tools are available for functional enrichment analysis based on GO categories. Most of these tools, due to their requirement of a prior threshold for designating genes as differentially expressed genes (DEGs), are categorized as threshold-dependent methods that often suffer from a major criticism on their changing results with different thresholds.

Results: In the present article, by considering the inherent correlation structure of the GO categories, a continuous measure based on semantic similarity of GO categories is proposed to investigate the functional consistence (or stability) of threshold-dependent methods. The results from several datasets show when simply counting overlapping categories between two groups, the significant category groups selected under different DEG thresholds are seemingly very different. However, based on the semantic similarity measure proposed in this article, the results are rather functionally consistent for a wide range of DEG thresholds. Moreover, we find that the functional consistence of gene lists ranked by SAM metric behaves relatively robust against changing DEG thresholds.

Availability: Source code in R is available on request from the authors.

Contact: guoz{at}ems.hrbmu.edu.cn

Supplementary information: Supplementary data are available at Bioinformatics online.

{dagger}The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors.

Associate Editor: Martin Bishop

Received on July 21, 2007; revised on November 3, 2007; accepted on November 4, 2007

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