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Article
Exploring Gene Expression Data, Using Plots
Journal of Data Science
  • Dianne Cook, Iowa State University
  • Heike Hofmann, Iowa State University
  • Eun-Kyung Lee, Iowa State University
  • Hao Yang, Iowa State University
  • Basil Nikolau, Iowa State University
  • Eve Wurtele, Iowa State University
Document Type
Article
Publication Version
Published Version
Publication Date
1-1-2007
Abstract
This paper describes how to explore gene expression data using a combination of graphical and numerical methods. We start from the general methodology for multivariate data visualization, describing heatmaps, parallel coordinate plots and scatterplots. We propose new methods for gene expression data analysis using direct manipulation graphics. With linked scatterplots and parallel coordinate plots we explore gene expression data differently than many common practices. To check replicates in relation to treatments we introduce a new type of plot called a “replicate line” plot. There is a worked example, that focuses on an experimental study containing two two-level factors, genotype and cofactor presence, with two replicates.
Comments

This article is from Journal of Data Science 5 (2007): 151. Posted with permission.

Copyright Owner
The Authors
Language
en
File Format
application/pdf
Citation Information
Dianne Cook, Heike Hofmann, Eun-Kyung Lee, Hao Yang, et al.. "Exploring Gene Expression Data, Using Plots" Journal of Data Science Vol. 5 Iss. 2 (2007) p. 151 - 182
Available at: http://works.bepress.com/eve-wurtele/56/