by Dianne Cook, Heike Hofmann, Eun-Kyung Lee, Hao Yang, Basil Nikolau and Eve Wurtele

Journal of Data Science, v.5, no.2, 151-182

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.

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