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

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 parallelizati...

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Bibliographic Details
Published in:Genome Biology 2015-01, Vol.16 (1), p.6-6, Article 6
Main Authors: Kelly, Benjamin J, Fitch, James R, Hu, Yangqiu, Corsmeier, Donald J, Zhong, Huachun, Wetzel, Amy N, Nordquist, Russell D, Newsom, David L, White, Peter
Format: Article
Language:English
Subjects:
Artificial chromosomes
Bioinformatics
Boundaries
Cloud Computing
Consortia
Data analysis
Data integrity
Data processing
Genetic diversity
Genetic Variation
Genetics, Population
Genome, Human
Genomes
Genomics
Genomics - methods
Haplotypes - genetics
Humans
Leukemia
Method
Mutation
Software
Time Factors
Workloads
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Summary: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/.
ISSN:1474-760X
1474-7596
1465-6906
1474-760X
1465-6914
DOI:10.1186/s13059-014-0577-x