BiCluster viewer: A visualization tool for analyzing gene expression data

Abstract

Exploring data sets by applying biclustering algorithms was first introduced in gene expression analysis. While the generated biclustered data grows with increasing rates due to the technological progress in measuring gene expression data, the visualization of the computed biclusters still remains an open issue. For efficiently analyzing the vast amount of gene expression data, we propose an algorithm to generate and layout biclusters with a minimal number of row and column duplications on the one hand and a visualization tool for interactively exploring the uncovered biclusters on the other hand. In this paper, we illustrate how the BiCluster Viewer may be applied to highlight detected biclusters generated from the original data set by using heatmaps and parallel coordinate plots. Many interactive features are provided such as ordering functions, color codings, zooming, details-on-demand, and the like. We illustrate the usefulness of our tool in a case study where yeast data is analyzed. Furthermore, we conducted a small user study with 4 participants to demonstrate that researchers are able to learn und use our tool to find insights in gene expression data very rapidly. © 2011 Springer-Verlag.