Skip Navigation



Bioinformatics Advance Access published online on April 13, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl144
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
22/13/1569    most recent
btl144v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Bhasi, K.
Right arrow Articles by Ramanathan, M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Bhasi, K.
Right arrow Articles by Ramanathan, M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 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
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.