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Nucleic Acids Research Advance Access originally published online on May 22, 2009
Nucleic Acids Research 2009 37(Web Server issue):W305-W311; doi:10.1093/nar/gkp427
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Nucleic Acids Research, 2009, Vol. 37, No. suppl_2 W305-W311
© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Articles

ToppGene Suite for gene list enrichment analysis and candidate gene prioritization

Jing Chen1, Eric E. Bardes2, Bruce J. Aronow2,3 and Anil G. Jegga2,3,*

1Department of Environmental Health, University of Cincinnati, 2Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center and 3Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA

*To whom correspondence should be addressed. Tel: +1 513 636 0261; Fax: +1 513 636 2056; Email: anil.jegga{at}cchmc.org

Received January 28, 2009. Revised April 24, 2009. Accepted May 11, 2009.

ToppGene Suite (http://toppgene.cchmc.org; this web site is free and open to all users and does not require a login to access) is a one-stop portal for (i) gene list functional enrichment, (ii) candidate gene prioritization using either functional annotations or network analysis and (iii) identification and prioritization of novel disease candidate genes in the interactome. Functional annotation-based disease candidate gene prioritization uses a fuzzy-based similarity measure to compute the similarity between any two genes based on semantic annotations. The similarity scores from individual features are combined into an overall score using statistical meta-analysis. A P-value of each annotation of a test gene is derived by random sampling of the whole genome. The protein–protein interaction network (PPIN)-based disease candidate gene prioritization uses social and Web networks analysis algorithms (extended versions of the PageRank and HITS algorithms, and the K-Step Markov method). We demonstrate the utility of ToppGene Suite using 20 recently reported GWAS-based gene–disease associations (including novel disease genes) representing five diseases. ToppGene ranked 19 of 20 (95%) candidate genes within the top 20%, while ToppNet ranked 12 of 16 (75%) candidate genes among the top 20%.


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