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LW-FQZip 2: a parallelized reference-based compression of FASTQ files

BACKGROUND: The rapid progress of high-throughput DNA sequencing techniques has dramatically reduced the costs of whole genome sequencing, which leads to revolutionary advances in gene industry. The explosively increasing volume of raw data outpaces the decreasing disk cost and the storage of huge s...

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Autores principales: Huang, Zhi-An, Wen, Zhenkun, Deng, Qingjin, Chu, Ying, Sun, Yiwen, Zhu, Zexuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5359991/
https://www.ncbi.nlm.nih.gov/pubmed/28320326
http://dx.doi.org/10.1186/s12859-017-1588-x
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author Huang, Zhi-An
Wen, Zhenkun
Deng, Qingjin
Chu, Ying
Sun, Yiwen
Zhu, Zexuan
author_facet Huang, Zhi-An
Wen, Zhenkun
Deng, Qingjin
Chu, Ying
Sun, Yiwen
Zhu, Zexuan
author_sort Huang, Zhi-An
collection PubMed
description BACKGROUND: The rapid progress of high-throughput DNA sequencing techniques has dramatically reduced the costs of whole genome sequencing, which leads to revolutionary advances in gene industry. The explosively increasing volume of raw data outpaces the decreasing disk cost and the storage of huge sequencing data has become a bottleneck of downstream analyses. Data compression is considered as a solution to reduce the dependency on storage. Efficient sequencing data compression methods are highly demanded. RESULTS: In this article, we present a lossless reference-based compression method namely LW-FQZip 2 targeted at FASTQ files. LW-FQZip 2 is improved from LW-FQZip 1 by introducing more efficient coding scheme and parallelism. Particularly, LW-FQZip 2 is equipped with a light-weight mapping model, bitwise prediction by partial matching model, arithmetic coding, and multi-threading parallelism. LW-FQZip 2 is evaluated on both short-read and long-read data generated from various sequencing platforms. The experimental results show that LW-FQZip 2 is able to obtain promising compression ratios at reasonable time and memory space costs. CONCLUSIONS: The competence enables LW-FQZip 2 to serve as a candidate tool for archival or space-sensitive applications of high-throughput DNA sequencing data. LW-FQZip 2 is freely available at http://csse.szu.edu.cn/staff/zhuzx/LWFQZip2 and https://github.com/Zhuzxlab/LW-FQZip2. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1588-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-53599912017-03-24 LW-FQZip 2: a parallelized reference-based compression of FASTQ files Huang, Zhi-An Wen, Zhenkun Deng, Qingjin Chu, Ying Sun, Yiwen Zhu, Zexuan BMC Bioinformatics Software BACKGROUND: The rapid progress of high-throughput DNA sequencing techniques has dramatically reduced the costs of whole genome sequencing, which leads to revolutionary advances in gene industry. The explosively increasing volume of raw data outpaces the decreasing disk cost and the storage of huge sequencing data has become a bottleneck of downstream analyses. Data compression is considered as a solution to reduce the dependency on storage. Efficient sequencing data compression methods are highly demanded. RESULTS: In this article, we present a lossless reference-based compression method namely LW-FQZip 2 targeted at FASTQ files. LW-FQZip 2 is improved from LW-FQZip 1 by introducing more efficient coding scheme and parallelism. Particularly, LW-FQZip 2 is equipped with a light-weight mapping model, bitwise prediction by partial matching model, arithmetic coding, and multi-threading parallelism. LW-FQZip 2 is evaluated on both short-read and long-read data generated from various sequencing platforms. The experimental results show that LW-FQZip 2 is able to obtain promising compression ratios at reasonable time and memory space costs. CONCLUSIONS: The competence enables LW-FQZip 2 to serve as a candidate tool for archival or space-sensitive applications of high-throughput DNA sequencing data. LW-FQZip 2 is freely available at http://csse.szu.edu.cn/staff/zhuzx/LWFQZip2 and https://github.com/Zhuzxlab/LW-FQZip2. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1588-x) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-20 /pmc/articles/PMC5359991/ /pubmed/28320326 http://dx.doi.org/10.1186/s12859-017-1588-x Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Huang, Zhi-An
Wen, Zhenkun
Deng, Qingjin
Chu, Ying
Sun, Yiwen
Zhu, Zexuan
LW-FQZip 2: a parallelized reference-based compression of FASTQ files
title LW-FQZip 2: a parallelized reference-based compression of FASTQ files
title_full LW-FQZip 2: a parallelized reference-based compression of FASTQ files
title_fullStr LW-FQZip 2: a parallelized reference-based compression of FASTQ files
title_full_unstemmed LW-FQZip 2: a parallelized reference-based compression of FASTQ files
title_short LW-FQZip 2: a parallelized reference-based compression of FASTQ files
title_sort lw-fqzip 2: a parallelized reference-based compression of fastq files
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5359991/
https://www.ncbi.nlm.nih.gov/pubmed/28320326
http://dx.doi.org/10.1186/s12859-017-1588-x
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