TY - JOUR
T1 - CRAVAT 4
T2 - Cancer-related analysis of variants toolkit
AU - Masica, David L.
AU - Douville, Christopher
AU - Tokheim, Collin
AU - Bhattacharya, Rohit
AU - Kim, Ryang Guk
AU - Moad, Kyle
AU - Ryan, Michael C.
AU - Karchin, Rachel
N1 - Funding Information:
This work was supported by NIH, NCI grant U24CA204817-01 to R. Karchin.
Publisher Copyright:
© 2017 American Association for Cancer Research.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - 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-RelatedAnalysis of Variants Toolkit (CRAVAT) is an evolving suite of informatics tools for mutation interpretation that includes mutation mapping and quality control, impact prediction and extensive annotation, gene- and mutationlevel interpretation, including joint prioritization of all nonsilent mutation 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 mutations, 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. Cancer Res; 77(21); e35-38.
AB - 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-RelatedAnalysis of Variants Toolkit (CRAVAT) is an evolving suite of informatics tools for mutation interpretation that includes mutation mapping and quality control, impact prediction and extensive annotation, gene- and mutationlevel interpretation, including joint prioritization of all nonsilent mutation 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 mutations, 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. Cancer Res; 77(21); e35-38.
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U2 - 10.1158/0008-5472.CAN-17-0338
DO - 10.1158/0008-5472.CAN-17-0338
M3 - Article
C2 - 29092935
AN - SCOPUS:85035031441
SN - 0008-5472
VL - 77
SP - e35-e38
JO - Cancer Research
JF - Cancer Research
IS - 21
ER -