henhaobio
Sign in

Cancer ResearchBioinformaticsPeer-reviewed journal article

CRAVAT 4: Cancer-Related Analysis of Variants Toolkit

David L. Masica, Christopher Blair DouvilleiD, Collin J. TokheimiD, Rohit BhattacharyaiD, RyangGuk Kim, Kyle Moad, Michaël RyaniD, Rachel KarchiniD

PDFDOIPreprint

Abstract

Cancer sequencing studies are increasingly comprehensive and well-powered, returning long lists of somatic mutations that can be difficult to sort and interpret. Diligent analysis and quality control can require multiple computational tools of distinct utility and producing disparate output, creating additional challenges for the investigator. The Cancer-Related Analysis of Variants Toolkit (CRAVAT) is an evolving suite of informatics tools for mutation interpretation that includes mutation projecting and quality control, impact prediction and extensive annotation, gene- and mutation-level interpretation including joint prioritization of all nonsilent consequence types, and structural and mechanistic visualization. Results from CRAVAT submissions are explored in an interactive, user-friendly web-environment with dynamic filtering and sorting designed to highlight the most informative mutation, even in the context of very large studies. CRAVAT can be run on a public web-portal, in the cloud, or downloaded for local use, and is easily integrated with other methods for cancer omics analysis.\n\nConflict of interestAll authors declare no potential conflict of interest.

Citations
74
FWCI
2.11
Field percentile
top 13%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISPagel '19Nakken '17Howard '20Dominguez '26Wang '17Wang '24
60% semantic matchBioinformatics
Kymberleigh A. Pagel, Rick Kim, Kyle Moad+6 more·bioRxiv·Oct 6, 2019· 7 citations