WebCMap: an R package for high-throughput connectivity analysis within the CMap framework

Experimentally generated drug-induced transcriptomic signatures are valuable resources to infer candidate drugs for unseen transcriptomes. The Connectivity Map (CMap) includes over 720 000 compound-induced signatures and has been widely used in drug repurposing. However, the computational resources required for an unbiased screen across all these signatures, along with the inconsistent results from different methods, presented huge challenges for the connectivity analyses.

In this study, we developed WebCMap, an R package to search for candidate compounds with similar or reverse activities across all CMap drug-induced signatures. WebCMap implements six widely used methods and a meta-score to evaluate the consistency among these methods. Through a web-accelerated framework, pre-calculated statistics for the permutation test, and multi-core parallelization, WebCMap enables fast screening and retrieval of the results on personal computers within a reasonable time.

WebCMap is available at https://github.com/geneprophet/WebCMap.