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Nucleic Acids Research Advance Access originally published online on August 9, 2006
Nucleic Acids Research 2006 34(14):e101; doi:10.1093/nar/gkl520
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Nucleic Acids Research, 2006, Vol. 34, No. 14 e101
© 2006 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-commerical use, distribution, and reproduction in any medium, provided the original work is properly cited.

Methods Online

Information-theoretic identification of predictive SNPs and supervised visualization of genome-wide association studies

Kavitha Bhasi, Li Zhang1, Daniel Brazeau, Aidong Zhang2 and Murali Ramanathan*

Department of Pharmaceutical Sciences, Eastern Michigan University Ypsilanti, MI 48197, USA 1 Department of Computer Science, Eastern Michigan University Ypsilanti, MI 48197, USA 2 Department of Computer Science and Engineering, State University of New York Buffalo, NY 14260, USA

*To whom correspondence should be addressed. Tel: +1 716 645 2842 (ext. 242); Fax: +1 716 645 3693; Email: murali{at}acsu.buffalo.edu

Received March 9, 2006. Revised June 20, 2006. Accepted July 6, 2006.

The size, dimensionality and the limited range of the data values makes visualization of single nucleotide polymorphism (SNP) datasets challenging. The purpose of this study is to evaluate the usefulness of 3D VizStruct, a novel multi-dimensional data visualization technique for SNP datasets capable of identifying informative SNPs in genome-wide association studies. VizStruct is an interactive visualization technique that reduces multi-dimensional data to three dimensions using a combination of the discrete Fourier transform and the Kullback–Leibler divergence. The performance of 3D VizStruct was challenged with several diverse, biologically relevant published datasets including the human lipoprotein lipase (LPL) gene locus, the human Y-chromosome in several populations and a multi-locus genotype dataset of coral samples from four populations. In every case, the SNPs and or polymorphic markers identified by the 3D VizStruct mapping were predictive of the underlying biology.


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