Aracari: exploration of eQTL data through visualization

Ryo Sakai, Christopher Bartlett, Dusan Popovic, William Ray, Jan Aerts

An interactive visualization tool (Aracari) was developed to analyze eQTL data. Aracari consists of two linked viewing modes: a gene expression view and a SNP view. An eQTL data set with spiked-in simulated data was analyzed; the results were assessed against the list of known spiked-in signals. Using Aracari, we were able to identify nine genes relevant to a disease while the defacto-standard biological expert’s eQTL toolkit (PLINK) could only detect six. We also identified numerous haplotype regions of relevance, highlighting a key strengths of visual analytics approach for this data.

BioVis 2012 Information

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