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Open Access Software

SEURAT: Visual analytics for the integrated analysis of microarray data

Alexander Gribov1, Martin Sill2, Sonja Lück3, Frank Rücker3, Konstanze Döhner3, Lars Bullinger3, Axel Benner2 and Antony Unwin1*

Author Affiliations

1 Department of Computer Oriented Statistics and Data Analysis, University of Augsburg, Universitätsstr. 14, 86159 Augsburg, Germany

2 Division of Biostatistics, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany

3 Department of Internal Medicine III, University Hospital of Ulm, Albert-Einstein-Allee 23, D-89081 Ulm, Germany

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BMC Medical Genomics 2010, 3:21  doi:10.1186/1755-8794-3-21

Published: 3 June 2010

Abstract

Background

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required.

Results

We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms.

Conclusions

The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.