elPrep 4: A multithreaded framework for sequence analysis.

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...

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Main Authors: Charlotte Herzeel, Pascal Costanza, Dries Decap, Jan Fostier, Wilfried Verachtert
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0209523
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spelling doaj-bda0ea80751f403986c770b651ecce0c2021-03-03T20:53:06ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01142e020952310.1371/journal.pone.0209523elPrep 4: A multithreaded framework for sequence analysis.Charlotte HerzeelPascal CostanzaDries DecapJan FostierWilfried VerachtertWe 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.https://doi.org/10.1371/journal.pone.0209523
collection DOAJ
language English
format Article
sources DOAJ
author Charlotte Herzeel
Pascal Costanza
Dries Decap
Jan Fostier
Wilfried Verachtert
spellingShingle Charlotte Herzeel
Pascal Costanza
Dries Decap
Jan Fostier
Wilfried Verachtert
elPrep 4: A multithreaded framework for sequence analysis.
PLoS ONE
author_facet Charlotte Herzeel
Pascal Costanza
Dries Decap
Jan Fostier
Wilfried Verachtert
author_sort Charlotte Herzeel
title elPrep 4: A multithreaded framework for sequence analysis.
title_short elPrep 4: A multithreaded framework for sequence analysis.
title_full elPrep 4: A multithreaded framework for sequence analysis.
title_fullStr elPrep 4: A multithreaded framework for sequence analysis.
title_full_unstemmed elPrep 4: A multithreaded framework for sequence analysis.
title_sort elprep 4: a multithreaded framework for sequence analysis.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description 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.
url https://doi.org/10.1371/journal.pone.0209523
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