FastProNGS: fast preprocessing of next-generation sequencing reads

BACKGROUND: Next-generation sequencing technology is developing rapidly and the vast amount of data that is generated needs to be preprocessed for downstream analyses. However, until now, software that can efficiently make all the quality assessments and filtration of raw data is still lacking. RESU...

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Autores principales: Liu, Xiaoshuang, Yan, Zhenhe, Wu, Chao, Yang, Yang, Li, Xiaomin, Zhang, Guangxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580563/
https://www.ncbi.nlm.nih.gov/pubmed/31208325
http://dx.doi.org/10.1186/s12859-019-2936-9
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author Liu, Xiaoshuang
Yan, Zhenhe
Wu, Chao
Yang, Yang
Li, Xiaomin
Zhang, Guangxin
author_facet Liu, Xiaoshuang
Yan, Zhenhe
Wu, Chao
Yang, Yang
Li, Xiaomin
Zhang, Guangxin
author_sort Liu, Xiaoshuang
collection PubMed
description BACKGROUND: Next-generation sequencing technology is developing rapidly and the vast amount of data that is generated needs to be preprocessed for downstream analyses. However, until now, software that can efficiently make all the quality assessments and filtration of raw data is still lacking. RESULTS: We developed FastProNGS to integrate the quality control process with automatic adapter removal. Parallel processing was implemented to speed up the process by allocating multiple threads. Compared with similar up-to-date preprocessing tools, FastProNGS is by far the fastest. Read information before and after filtration can be output in plain-text, JSON, or HTML formats with user-friendly visualization. CONCLUSIONS: FastProNGS is a rapid, standardized, and user-friendly tool for preprocessing next-generation sequencing data within minutes. It is an all-in-one software that is convenient for bulk data analysis. It is also very flexible and can implement different functions using different user-set parameter combinations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2936-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-65805632019-06-24 FastProNGS: fast preprocessing of next-generation sequencing reads Liu, Xiaoshuang Yan, Zhenhe Wu, Chao Yang, Yang Li, Xiaomin Zhang, Guangxin BMC Bioinformatics Software BACKGROUND: Next-generation sequencing technology is developing rapidly and the vast amount of data that is generated needs to be preprocessed for downstream analyses. However, until now, software that can efficiently make all the quality assessments and filtration of raw data is still lacking. RESULTS: We developed FastProNGS to integrate the quality control process with automatic adapter removal. Parallel processing was implemented to speed up the process by allocating multiple threads. Compared with similar up-to-date preprocessing tools, FastProNGS is by far the fastest. Read information before and after filtration can be output in plain-text, JSON, or HTML formats with user-friendly visualization. CONCLUSIONS: FastProNGS is a rapid, standardized, and user-friendly tool for preprocessing next-generation sequencing data within minutes. It is an all-in-one software that is convenient for bulk data analysis. It is also very flexible and can implement different functions using different user-set parameter combinations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2936-9) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-17 /pmc/articles/PMC6580563/ /pubmed/31208325 http://dx.doi.org/10.1186/s12859-019-2936-9 Text en © The Author(s). 2019 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
Liu, Xiaoshuang
Yan, Zhenhe
Wu, Chao
Yang, Yang
Li, Xiaomin
Zhang, Guangxin
FastProNGS: fast preprocessing of next-generation sequencing reads
title FastProNGS: fast preprocessing of next-generation sequencing reads
title_full FastProNGS: fast preprocessing of next-generation sequencing reads
title_fullStr FastProNGS: fast preprocessing of next-generation sequencing reads
title_full_unstemmed FastProNGS: fast preprocessing of next-generation sequencing reads
title_short FastProNGS: fast preprocessing of next-generation sequencing reads
title_sort fastprongs: fast preprocessing of next-generation sequencing reads
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580563/
https://www.ncbi.nlm.nih.gov/pubmed/31208325
http://dx.doi.org/10.1186/s12859-019-2936-9
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