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Günter Jäger, Florian Battke, Karsten Borgwardt, Kay Nieselt (Center for Bioinformatics Tübingen, University of Tübingen, Germany; Max-Planck-Institute for Intelligent Systems, Tübingen, Germany )Reveal is a visual analytics toolkit for data from eQTL studies. In these haplotype data is combined with patient phenotype data describing the impact of a specific disease and gene expression values for genes that may be correlated with the disease. These diverse data types give rise to three levels of complexity: the first level comprises SNP-gene association data (either single- or two-locus data) correlating the presence of SNPs (or SNP pairs) with changes in gene expression. The second level involves the comparison of the allele distributions of different cohorts in order to find conspicuous loci that differ between the cohorts. The third level arises from the investigation of SNP-derived changes in gene expression levels. Reveal offers methods for the analysis and visualization for all three levels of complexity to provide insight into the mechanisms triggering the onset and magnitude of the disease: a matrix-based visualization for single- and two-locus SNP-gene associations, a genotype view displaying cohort allele distributions together with an aggregation view for easy identification of suspicious loci and a heatmap for the visualization of SNP-derived gene expression.