Genomic Analysis, Visualization and Informatics Lab-space (AnVIL)

The AnVIL will facilitate integration and computing on and across large datasets generated by NHGRI programs, as well as initiatives funded by National Institutes of Health (NIH), or by other agencies that support human genomics research.

In addition, the AnVIL will be a component of the emerging NIH Data Commons, and is expected to collaborate and integrate with other genomic data resources through the adoption of the FAIR (Findable, Accessible, Interoperable, Reusable) principles, as their specifications emerge from the scientific community. The AnVIL will provide a collaborative environment, where datasets and analysis workflows can be shared within a consortium and be prepared for public release to the broad scientific community through AnVIL user interfaces. The AnVIL will be tailored for both users that have limited computational expertise as well as sophisticated data scientist users. The AnVIL is currently slated for its initial launch in Q1 2019.

Specifically, the AnVIL resource will provide genomic researchers with the following key elements:

• Cloud-based infrastructure and software platform
• Shared analysis and computing environment
• Interoperability and compliance with the NIH Data Commons
• Cloud services cost control
• Genomic datasets, phenotypes, and metadata
• Data access and data security
• User training and outreach
• Incorporation of scientific and technology advance for storing, accessing, sharing and computing on large genomic datasets

For AnVIL related comments or questions please contact NHGRI at: anvil@mail.nih.gov

Applications were submitted in response to the NHGRI AnVIL Funding Opportunity Announcement (FOA): RFA-HG-17-011 and two awards were made.

The AnVIL Data Ecosystem - U24HG010262

• Data Sciences Platform, Broad Institute: Anthony Philippakis (contact PI), Daniel MacArthur (co-I)
• Genomics Institute, University of California Santa Cruz: Benedict Paten (PI), David Haussler (co-I)
• Center for Data Intensive Science, University of Chicago: Robert Grossman (PI)
• McDonnell Genome Institute, Washington University in St. Louis: Ira Hall (PI), Larson David (co-I)   
• Vanderbilt University Medical Center: Robert Carroll (PI), Joshua Denny (co-I)
• Institute for Precision Cardiovascular Medicine, American Heart Association: Jennifer Hall (PI)

Implementing the Genomic Data Science Analysis, Visualization, and Informatics Lab-Space (ANVIL) - U24HG010263

• Department of Biology, Johns Hopkins University: James Taylor (contact PI), Jeffrey Leek (PI), Michael Schatz (PI), Enis Afgan (co-I), Kasper Hansen (co-I)
• Department of Biomedical Engineering, Oregon Health & Sciences University: Jeremy Goeks (PI), Kyle Ellrott (co-I)
• Huck Institute of the Life Sciences, Pennsylvania State University: Anton Nekrutenko (PI)
• Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute: Martin Morgan (PI)
• Department of Medicine, Brigham & Women's Hospital: Vincent Carey (PI)
• Institute for Implementation Science in Population Health, City University of New York: Levi Waldron (PI)