RESUMEN
MOTIVATION: Multi-omic profiling data, such as The Cancer Genome Atlas and pharmacogenomic data, facilitate research into cancer mechanisms and drug development. However, it is not easy for researchers to connect, integrate and analyze huge and heterogeneous data, which is a major obstacle to the utilization of cancer genomic data. RESULTS: We developed Cancer Genome Viewer (CGV), a user-friendly web service that provides functions to integrate and visualize cancer genome data and pharmacogenomic data. Users can easily select and customize the samples to be analyzed with the pre-defined selection options for patients' clinic-pathological features from multiple datasets. Using the customized dataset, users can perform subsequent data analyses comprehensively, including gene set analysis, clustering or survival analysis. CGV also provides pre-calculated drug response scores from pharmacogenomic data, which may facilitate the discovery of new cancer targets and therapeutics. AVAILABILITY AND IMPLEMENTATION: CGV web service is implemented with the R Shiny application at http://cgv.sysmed.kr and the source code is freely available at https://git.sysmed.kr/sysmed_public/cgv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
