About | OpenCRAVAT
About Us
OpenCRAVAT is a new open source, scalable decision support system to support variant and gene prioritization. It offers a dynamic GUI, allowing users to easily, download tools from an extensive resource catalog, create customized pipelines, run jobs at speeds that exceed current variant annotation API services, and explore results in a richly detailed viewing environment. OpenCRAVAT is distinguished from similar tools by the amount and diversity of data resources and computational prediction methods available, which span germline, somatic, common, rare, coding and non-coding variants. We have designed the OpenCRAVAT resource catalog to be open and modular to maximize community and developer involvement, and as a result the catalog is being actively developed and growing larger every month.
Testimonials for OpenCRAVAT
“Great tool for quick processing annotation of variants. Very user-friendly and flexible” Kazan Federal University-RIKEN
“The OpenCRAVAT webserver makes it vastly easier to quickly check variant annotations.” Research Fellow, Dana-Farber Cancer Institute
“Brilliant design.” Professor of Medicine, Harvard Medical School
“Perhaps the most comprehensive workflow for variant annotation and exploitation” Postdoctoral Researcher, German Cancer Research Center
“Makes annotation super simple and importantly standardized. Many thanks for creating this. Excited to cite this and share this resource with trainees (especially when teaching undergrads new to learning computational biology)” Assistant Professor, Emory University School of Medicine
“OpenCRAVAT has greatly enabled matching genotypes with therapeutic options especially for un-vetted, not thoroughly biochemically characterized variants.” Assistant Professor of Oncology, Sidney Kimmel Cancer Center
“I found about the CRAVAT software during the AACR meeting and started using it today. This is so amazing! Thanks for putting all this effort to facilitate the analysis for people like me” Associate Professor, Louisiana Cancer Research Center
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How to Cite
Pagel KA et al. Integrated Informatics Analysis of Cancer-Related Variants. JCO Clinical Cancer Informatics 2020 4, 310-317.
OpenCRAVAT users are encouraged to cite individual annotations used in their study analysis.
Our Team
![Rachel Karchin Photo](images/rachelServer.jpg)
Rachel Karchin
Principal InvestigatorJohns Hopkins University
![Jelte van Baren Photo](images/people-jeltje.jpeg)
Jeltje van Baren
Bioinformatics ScientistJohns Hopkins University
![Jasmine Baker Photo](images/Jasmine_Baker.jpg)
Jasmine Baker
Research ScientistJohns Hopkins University
![Supra Gajjala Photo](images/Supra_Gajjala.jpg)
Supra Gajjala
Research ScientistJohns Hopkins University
![Kyle Moad Photo](images/kmoad.jpg)
Kyle Moad
Lead Software EngineerPotomac IT
![Madison Larsen Photo](images/people-madison.png)
Madison Larsen
Software EngineerPotomac IT
![Kyle Anderson Photo](images/ska_portrait.jpg)
Kyle Anderson
Software EngineerPotomac IT
![Ben Busby Photo](images/ben-busbyphd.png)
Ben Busby
Biomedical Data Science Consultant![James Higgins Photo](images/people-james.png)
James Higgins
Software EngineerPotomac IT