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This article is part of the supplement: Selected articles from the Ninth Asia Pacific Bioinformatics Conference (APBC 2011)

Open Access Research

Evaluation of methods for detecting conversion events in gene clusters

Giltae Song1*, Chih-Hao Hsu2, Cathy Riemer1 and Webb Miller1

Author Affiliations

1 Center for Comparative Genomics and Bioinformatics, 506 Wartik Lab, Pennsylvania State University, University Park, PA 16802, USA

2 Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health (NIH), Bethesda, MD, USA

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BMC Bioinformatics 2011, 12(Suppl 1):S45  doi:10.1186/1471-2105-12-S1-S45

Published: 15 February 2011

Abstract

Background

Gene clusters are genetically important, but their analysis poses significant computational challenges. One of the major reasons for these difficulties is gene conversion among the duplicated regions of the cluster, which can obscure their true relationships. Many computational methods for detecting gene conversion events have been released, but their performance has not been assessed for wide deployment in evolutionary history studies due to a lack of accurate evaluation methods.

Results

We designed a new method that simulates gene cluster evolution, including large-scale events of duplication, deletion, and conversion as well as small mutations. We used this simulation data to evaluate several different programs for detecting gene conversion events.

Conclusions

Our evaluation identifies strengths and weaknesses of several methods for detecting gene conversion, which can contribute to more accurate analysis of gene cluster evolution.