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Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL)

Authors :
Casey Overby Taylor
Jennifer Vessio
Ting Wang
Levi Waldron
Anthony A. Philippakis
Jeremy Goecks
Candace Patterson
Kyle Ellrott
Alessandro Culotti
Vincent J. Carey
Enis Afgan
Frederick J. Tan
Anton Nekrutenko
Martin Morgan
Benedict Paten
Eric Banks
Kasper D. Hansen
Kristin Wuichet
Michael C. Schatz
Robert J. Carroll
Ira M. Hall
Jonathan Lawson
Robert L. Grossman
Stephen Mosher
Anne O’Donnell Luria
AnVIL Team
Brian O'Connor
Kevin Osborn
Jeffrey T. Leek
Publication Year :
2021
Publisher :
Cold Spring Harbor Laboratory, 2021.

Abstract

The traditional model of genomic data analysis - downloading data from centralized warehouses for analysis with local computing resources - is increasingly unsustainable. Not only are transfers slow and cost prohibitive, but this approach also leads to redundant and siloed compute infrastructure that makes it difficult to ensure security and compliance of protected data. The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) inverts this model, providing a unified cloud computing environment for data storage, management, and analysis. AnVIL eliminates the need for data movement, allows for active threat detection and monitoring, and provides scalable, shared computing resources that can be acquired by researchers as needed. This presents many new opportunities for collaboration and data sharing that will ultimately lead to scientific discoveries at scales not previously possible.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........54f4b7e70f84f97c3ebf01478de8c6c4
Full Text :
https://doi.org/10.1101/2021.04.22.436044