Abstract

A main task in computational cancer analysis is the identification of patient subgroups (i.e. cohorts) based on metadata attributes (patient stratification) or genomic markers of response (biomarkers). Coral is a web-based cohort analysis tool that is designed to support this task: Users can interactively create and refine cohorts, which can then be compared, characterized and inspected down to the level of single items. Coral visualizes the evolution of cohorts and also provides intuitive access to prevalence information. Furthermore, findings can be stored, shared and reproduced via the integrated session management. Coral is pre-loaded with data from over 128000 samples from the AACR Project GENIE, the Cancer Genome Atlas and the Cell Line Encyclopedia. Coral is publicly available at https://coral.caleydoapp.org. The source code is released at https://github.com/Caleydo/coral. Supplementary data are available at Bioinformatics online.

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