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Bioinformatics Advance Access published online on April 13, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl144
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received March 2, 2006
Revised April 9, 2006
Accepted April 10, 2006

Article

VizStruct for visualization of genome-wide SNP analyses

Kavitha Bhasi 1, Li Zhang 2, Daniel Brazeau 1, Aidong Zhang 3, and Murali Ramanathan 1 *

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


  Abstract

Motivation: The size, dimensionality and the limited range of the data values makes visualization of single nucleotide polymorphism (SNP) data sets challenging. The purpose of this study is to evaluate the usefulness of 3-D VizStruct, a novel multi-dimensional data visualization technique for analyzing patterns in SNP data sets.

Results: VizStruct is an interactive visualization technique that reduces multi-dimensional data to 2-dimensions using the complex-valued harmonics of the discrete Fourier transform. In the 3-D VizStruct extension, the multi-dimensional SNP data vectors are reduced to 3-dimensions using a combination of the discrete Fourier transform and the Kullback-Leibler divergence. The performance of 3-D VizStruct was challenged with several biologically relevant published data sets that included human Chromosome 21, the human lipoprotein lipase (LPL) gene locus and the multi-locus genotypes of coral populations. In every case, the 3-D VizStruct mapping provided an intuitive visual description of the key characteristics of the underlying multi-dimensional genotype.

Availability: Excel and MATLAB code is available.

Associate Editor: Alex Bateman
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