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DrugPattern: a web-based tool for drug set enrichment analysis

By Chuanbo Huang, Weili Yang, Junpei Wang, Yuan Zhou, Bin Geng, Georgios Kararigas, Jichun Yang, Qinghua Cui

Posted 20 Aug 2017
bioRxiv DOI: 10.1101/178632 (published DOI: 10.1016/j.jgg.2018.07.002)

Set enrichment analysis based methods (e.g. gene set enrichment analysis) have provided great helps in mining patterns in biomedical datasets, however, tools for inferring regular patterns in drug-related datasets are still limited. For the above purpose, here we developed a web-based tool, DrugPattern. DrugPattern first collected and curated 7019 drug sets, including indications, adverse reaction, targets, pathways etc. For a list of interested drugs, DrugPattern then evaluates the significance of the enrichment of these drugs in each of the 7019 drug sets. To validate DrugPattern, we applied it to predict the potential protective roles of oxidized low-density lipoprotein (oxLDL), a widely accepted deleterious factor for the body. We predicted that oxLDL has beneficial effects on some diseases, most of which were supported by literature except type 2 diabetes (T2D), in which oxLDL was previously believed to be a risk factor. Animal experiments further validated that oxLDL indeed has beneficial effects on T2D. These data confirmed the prediction accuracy of our approach and revealed unexpected protective roles for oxLDL in various diseases including T2D. This study provides a tool to infer regular patterns in biomedical datasets based on drug set enrichment analysis.

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