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explorase: Multivariate Exploratory Analysis and Visualization for Systems Biology
Journal of Statistical Software
  • Michael Lawrence, Fred Hutchinson Cancer Research Center
  • Dianne Cook, Iowa State University
  • Eun-Kyung Lee, Ulsan University
  • Heather Babka, Iowa State University
  • Eve S. Wurtele, Iowa State University
Document Type
Article
Publication Version
Published Version
Publication Date
4-1-2008
DOI
10.18637/jss.v025.i09
Abstract
The datasets being produced by high-throughput biological experiments, such as microarrays, have forced biologists to turn to sophisticated statistical analysis and visualization tools in order to understand their data. We address the particular need for an open-source exploratory data analysis tool that applies numerical methods in coordination with interactive graphics to the analysis of experimental data. The software package, known as explorase, provides a graphical user interface (GUI) on top of the R platform for statistical computing and the GGobi software for multivariate interactive graphics. The GUI is designed for use by biologists, many of whom are unfamiliar with the R language. It displays metadata about experimental design and biological entities in tables that are sortable and filterable. There are menu shortcuts to the analysis methods implemented in R, including graphical interfaces to linear modeling tools. The GUI is linked to data plots in GGobi through a brush tool that simultaneously colors rows in the entity information table and points in the GGobi plots.
Comments

This article is from Journal of Statistical Software 25 (2008): 1, doi: 10.18637/jss.v025.i09. Posted with permission.

Rights
This work is made available under a CC-BY license. For more information, please visit: http://creativecommons.org/licenses/by/3.0/
Copyright Owner
The Authors
Language
en
File Format
application/pdf
Citation Information
Michael Lawrence, Dianne Cook, Eun-Kyung Lee, Heather Babka, et al.. "explorase: Multivariate Exploratory Analysis and Visualization for Systems Biology" Journal of Statistical Software Vol. 25 Iss. 9 (2008) p. 1 - 23
Available at: http://works.bepress.com/eve-wurtele/54/