Scaling computational genomics to millions of individuals with GPUs

Scaling computational genomics to millions of individuals with GPUs

Abstract Current genomics methods are designed to handle tens to thousands of samples but will need to scale to millions to match the pace of data and hypothesis generation in biomedical science. Here, we show that high efficiency at low cost can be achieved by leveraging general-purpose libraries f...

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Bibliographic Details
Main Authors: Amaro Taylor-Weiner, François Aguet, Nicholas J. Haradhvala, Sager Gosai, Shankara Anand, Jaegil Kim, Kristin Ardlie, Eliezer M. Van Allen, Gad Getz
Format: Article
Language:English
Published: BMC 2019-11-01
Series:Genome Biology
Online Access:http://link.springer.com/article/10.1186/s13059-019-1836-7

Internet

http://link.springer.com/article/10.1186/s13059-019-1836-7

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