Genome Biology · 2015 · 143 citations · 28 references
Life SciencesBioinformaticsGeneticsGenomic Data AnalysisGenomicsParallel ComputingData ParallelismDna SequencingGenome SequencingNext-generation SequencingVariant AnalysisVariant DetectionCloud Computing ResourcesGenome Sequencing AnalysisMethod ReproducibilityNext-generation Sequencing AnalysisParallel SequencingParallelizationVariant Calling From Long ReadsWhole-genome Sequencing Analysis
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/.
28
The Sequence Alignment/Map format and SAMtools
Heng Li, Alec Wysoker, Tim Fennell et al. · Bioinformatics · 2009 · 67.5K citations · Full text
Fast and accurate short read alignment with Burrows–Wheeler transform
Heng Li, Richard Durbin · Bioinformatics · 2009 · 62.8K citations · Full text
A framework for variation discovery and genotyping using next-generation DNA sequencing data
Mark A. DePristo, Eric Banks, Ryan Poplin et al. · Nature Genetics · 2011 · 12.4K citations · Full text
Index for rating diagnostic tests
W. J. Youden · Cancer · 1950 · 11.5K citations · Full text
Education, Educational Assessment, Educational Measurement +11