Main logo
tutorial arrow
Create your own tool library
Bookmark tools and put favorites into folders to find them easily.

Cancer-Related Analysis of Variants Toolkit CRAVAT

Alternative name: CRAVAT 4 | CRAVAT 5

Performs cancer-related analysis of variants. CRAVAT returns mutation interpretations in a dynamic interactive web environment for sorting, visualizing and inferring mechanism. The software (i) performs all projecting and assigns sequence ontology, (ii) predicts mutation impact using multiple bioinformatics classifiers normalized, (iii) allows for joint prioritization of all non-silent mutation types, organizes annotation from many sources on graphical displays of protein sequence and 3D structure, and (iv) facilitates dynamic filtering. It is suitable for both large and small studies and developed for easy integration with other software.

User report

tutorial arrow
Vote up tools and offer feedback
Give value to tools and make your expertise visible
Give your feedback on this tool
Sign up for free to join and share with the community

0 user reviews

0 user reviews

No review has been posted.

CRAVAT forum

tutorial arrow
Communicate with other users
Participate in the forum to get support for using tools. Ask questions about technical specifications.
Take part in the discussion
Sign up for free to ask question and share your advices

No open topic.

CRAVAT classification

CRAVAT specifications

Web user interface, Application programming interface
Input data:
Variant calls from sequencing studies in either genomic coordinates (hg18 or hg19) or transcript coordinates—NCBI Refseq, CCDS and Ensembl.
Computer skills:
Restrictions to use:
Input format:
VCF, CRAVAT format


  • CHASM (Cancer-specific High-throughput Annotation of Somatic Mutations)
  • VEST
  • SNVGet

CRAVAT distribution


CRAVAT support


  • Rachel Karchin <>

Additional information


tutorial arrow
Promote your skills
Define all the tasks you managed and assign your profile the appropriate badges. Become an active member.
Promote your work
Sign up for free to badge your contributorship



Department of Biomedical Engineering, Department of Computer Science, The Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, USA; In Silico Solutions, Falls Church, VA, USA; Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA

Funding source(s)

National Institutes of Health CA 152432; National Science Foundation DBI 0845275

Link to literature

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.