VEST @ Karchin lab

VEST (Variant Effect Scoring Tool)

is a machine learning method that predicts the functional significance of missense mutations observed through genome sequencing, allowing mutations to be prioritized in subsequent functional studies, based on the probability that they impair protein activity.

Current release is VEST 3.0. Dependency: SNVBox 3.0. last updated on 05/01/2014. Our software is intended for those with substantial bioinformatics and Linux system expertise and access to a large-memory Linux server. It is free for non-commercial use. For more details please refer to our Software License. Commercial users should contact the Johns Hopkins Technology Transfer office .

Documentation for the user

This section provides documentation for the user, including instructions to download and install the source code.

Documentation for the developer

This section provides documentation for developers.

Example workflow

Short tutorial on how to run VEST from the command line


Example running VEST on real data


(L) Comparison with PPH2 and SIFT on gene holdout benchmark
(R) Utility in network-based stratification of tumors

Primary citations

If you use our software for a publication, please cite the following:

Carter H, Douville C, Yeo G, Stenson PD, Cooper DN, Karchin R (2013) Identifying Mendelian disease genes with the Variant Effect Scoring Tool BMC Genomics. 14(3) 1-16.

Software primary contact/developer

Hannah Carter  hcarte10 at gmail dot com

For issues with VEST run on the web with CRAVAT, please contact Rick Kim  rkim at insilico dot us dot com

This is a beta version of the VEST documentation page. Please contact the primary developer with feedback, suggestions, and requests to improve this page.