Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics

Benjamin Kelly(Nationwide Children's Hospital), James Fitch(Nationwide Children's Hospital), Yangqiu Hu(Nationwide Children's Hospital), Donald J. Corsmeier(Nationwide Children's Hospital), Huachun Zhong(Nationwide Children's Hospital), Amy Wetzel(Nationwide Children's Hospital), Russell D Nordquist(Nationwide Children's Hospital), David L. Newsom(Nationwide Children's Hospital), Peter White(Nationwide Children's Hospital)
Genome Biology
January 19, 2015
Cited by 143Open Access
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Abstract

While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/.


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