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explorase: Multivariate Exploratory Analysis and Visualization for Systems Biology

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  • Lawrence, Michael
  • Cook, Dianne
  • Lee, Eun-Kyung
  • Babka, Heather
  • Wurtele, Eve Syrkin

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.

Suggested Citation

  • Lawrence, Michael & Cook, Dianne & Lee, Eun-Kyung & Babka, Heather & Wurtele, Eve Syrkin, 2008. "explorase: Multivariate Exploratory Analysis and Visualization for Systems Biology," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i09).
    • Handle: RePEc:jss:jstsof:v:025:i09
    DOI: http://hdl.handle.net/10.18637/jss.v025.i09
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    References listed on IDEAS

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    1. Swayne, Deborah F. & Lang, Duncan Temple & Buja, Andreas & Cook, Dianne, 2003. "GGobi: evolving from XGobi into an extensible framework for interactive data visualization," Computational Statistics & Data Analysis, Elsevier, vol. 43(4), pages 423-444, August.
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