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elPrep 4 : a multithreaded framework for sequence analysis

(2019) PLOS ONE. 14(2). p.1-16
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Abstract
We present elPrep 4, a reimplementation from scratch of the elPrep framework for processing sequence alignment map files in the Go programming language. elPrep 4 includes multiple new features allowing us to process all of the preparation steps defined by the GATK Best Practice pipelines for variant calling. This includes new and improved functionality for sorting, (optical) duplicate marking, base quality score recalibration, BED and VCF parsing, and various filtering options. The implementations of these options in elPrep 4 faithfully reproduce the outcomes of their counterparts in GATK 4, SAMtools, and Picard, even though the underlying algorithms are redesigned to take advantage of elPrep's parallel execution framework to vastly improve the runtime and resource use compared to these tools. Our benchmarks show that elPrep executes the preparation steps of the GATK Best Practices up to 13x faster on WES data, and up to 7.4x faster for WGS data compared to running the same pipeline with GATK 4, while utilizing fewer compute resources.
Keywords
ALIGNMENT

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Please use this url to cite or link to this publication:

Chicago
Herzeel, Charlotte, Pascal Costanza, Dries Decap, Jan Fostier, and Wilfried Verachtert. 2019. “elPrep 4 : a Multithreaded Framework for Sequence Analysis.” Plos One 14 (2): 1–16.
APA
Herzeel, C., Costanza, P., Decap, D., Fostier, J., & Verachtert, W. (2019). elPrep 4 : a multithreaded framework for sequence analysis. PLOS ONE, 14(2), 1–16.
Vancouver
1.
Herzeel C, Costanza P, Decap D, Fostier J, Verachtert W. elPrep 4 : a multithreaded framework for sequence analysis. PLOS ONE. San francisco: Public Library Science; 2019;14(2):1–16.
MLA
Herzeel, Charlotte et al. “elPrep 4 : a Multithreaded Framework for Sequence Analysis.” PLOS ONE 14.2 (2019): 1–16. Print.
@article{8606445,
  abstract     = {We present elPrep 4, a reimplementation from scratch of the elPrep framework for processing sequence alignment map files in the Go programming language. elPrep 4 includes multiple new features allowing us to process all of the preparation steps defined by the GATK Best Practice pipelines for variant calling. This includes new and improved functionality for sorting, (optical) duplicate marking, base quality score recalibration, BED and VCF parsing, and various filtering options. The implementations of these options in elPrep 4 faithfully reproduce the outcomes of their counterparts in GATK 4, SAMtools, and Picard, even though the underlying algorithms are redesigned to take advantage of elPrep's parallel execution framework to vastly improve the runtime and resource use compared to these tools. Our benchmarks show that elPrep executes the preparation steps of the GATK Best Practices up to 13x faster on WES data, and up to 7.4x faster for WGS data compared to running the same pipeline with GATK 4, while utilizing fewer compute resources.},
  articleno    = {e0209523},
  author       = {Herzeel, Charlotte and Costanza, Pascal and Decap, Dries and Fostier, Jan and Verachtert, Wilfried},
  issn         = {1932-6203},
  journal      = {PLOS ONE},
  language     = {eng},
  number       = {2},
  pages        = {e0209523:1--e0209523:16},
  publisher    = {Public Library Science},
  title        = {elPrep 4 : a multithreaded framework for sequence analysis},
  url          = {http://dx.doi.org/10.1371/journal.pone.0209523},
  volume       = {14},
  year         = {2019},
}

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