Genomics | Bioinformatics
SNPsyn: Detection and exploration of SNP–SNP interactions
Tomaž Curk*, Gregor Rot, Blaž Zupan
*Corresponding author: Tomaž Curk
Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia
F1000Posters 2011, 2: 1493 (poster) [ENGLISH]
Poster [1.21 MB] | Resulting articles
Presented at
19th Annual International Conference on Intelligent Systems for Molecular Biology and 10th European Conference on Computational Biology 2011 (ISMB/ECCB),
17 - 19 Jul 2011, L15
SNPsyn is an interactive web-based application for the discovery of synergistic pairs of single nucleotide polymorphisms (SNPs) in large genome-wide case-control association studies (GWAS) of complex diseases. SNPsyn is both a stand-alone C++/Flash application and a web server. The computationally intensive part is implemented in C++ and can run in parallel on a dedicated cluster or grid.
We have developed the graphical user interface in Adobe Flash Builder 4 so that it can run in standard web browsers or as a stand-alone application.
The SNPsyn web server receives GWAS data submissions, invokes the interaction analysis and serves the results for rendering at the client site. Synergies of pairs of SNPs are estimated through interaction analysis, an information-theoretic approach. Synergy occurs when a combination of SNPs carries more information than the sum of information provided by individual SNPs. Several heuristics and GO term-based selection approaches have been implemented to limit the number of investigated SNPs and speed-up the analysis.
SNPsyn web application has a graphical visual analytics interface. Users can view the synergy and informativity scores, select a subset of most synergistic pairs, browse through the detailed lists of SNPs that are also linked to NCBI and HapMap, perform GO term enrichment analysis on selected pairs, and interact with the constructed SNP synergy network.
SNPsyn aims to complement the present set of gene interaction analysis programs. It’s simple and intuitive graphical interface should allow biomedical researchers to effortlessly upload, analyze and gain insight into their own data.
No relevant conflicts of interest declared.
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