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An integrated software for virus community sequencing data analysis
BACKGROUND: A virus community is the spectrum of viral strains populating an infected host, which plays a key role in pathogenesis and therapy response in viral infectious diseases. However automatic and dedicated pipeline for interpreting virus community sequencing data has not been developed yet....
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7227348/ https://www.ncbi.nlm.nih.gov/pubmed/32414327 http://dx.doi.org/10.1186/s12864-020-6744-4 |
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author | Wang, Mingjie Li, Jianfeng Zhang, Xiaonan Han, Yue Yu, Demin Zhang, Donghua Yuan, Zhenghong Yang, Zhitao Huang, Jinyan Zhang, Xinxin |
author_facet | Wang, Mingjie Li, Jianfeng Zhang, Xiaonan Han, Yue Yu, Demin Zhang, Donghua Yuan, Zhenghong Yang, Zhitao Huang, Jinyan Zhang, Xinxin |
author_sort | Wang, Mingjie |
collection | PubMed |
description | BACKGROUND: A virus community is the spectrum of viral strains populating an infected host, which plays a key role in pathogenesis and therapy response in viral infectious diseases. However automatic and dedicated pipeline for interpreting virus community sequencing data has not been developed yet. RESULTS: We developed Quasispecies Analysis Package (QAP), an integrated software platform to address the problems associated with making biological interpretations from massive viral population sequencing data. QAP provides quantitative insight into virus ecology by first introducing the definition “virus OTU” and supports a wide range of viral community analyses and results visualizations. Various forms of QAP were developed in consideration of broader users, including a command line, a graphical user interface and a web server. Utilities of QAP were thoroughly evaluated with high-throughput sequencing data from hepatitis B virus, hepatitis C virus, influenza virus and human immunodeficiency virus, and the results showed highly accurate viral quasispecies characteristics related to biological phenotypes. CONCLUSIONS: QAP provides a complete solution for virus community high throughput sequencing data analysis, and it would facilitate the easy analysis of virus quasispecies in clinical applications. |
format | Online Article Text |
id | pubmed-7227348 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72273482020-05-27 An integrated software for virus community sequencing data analysis Wang, Mingjie Li, Jianfeng Zhang, Xiaonan Han, Yue Yu, Demin Zhang, Donghua Yuan, Zhenghong Yang, Zhitao Huang, Jinyan Zhang, Xinxin BMC Genomics Software BACKGROUND: A virus community is the spectrum of viral strains populating an infected host, which plays a key role in pathogenesis and therapy response in viral infectious diseases. However automatic and dedicated pipeline for interpreting virus community sequencing data has not been developed yet. RESULTS: We developed Quasispecies Analysis Package (QAP), an integrated software platform to address the problems associated with making biological interpretations from massive viral population sequencing data. QAP provides quantitative insight into virus ecology by first introducing the definition “virus OTU” and supports a wide range of viral community analyses and results visualizations. Various forms of QAP were developed in consideration of broader users, including a command line, a graphical user interface and a web server. Utilities of QAP were thoroughly evaluated with high-throughput sequencing data from hepatitis B virus, hepatitis C virus, influenza virus and human immunodeficiency virus, and the results showed highly accurate viral quasispecies characteristics related to biological phenotypes. CONCLUSIONS: QAP provides a complete solution for virus community high throughput sequencing data analysis, and it would facilitate the easy analysis of virus quasispecies in clinical applications. BioMed Central 2020-05-15 /pmc/articles/PMC7227348/ /pubmed/32414327 http://dx.doi.org/10.1186/s12864-020-6744-4 Text en © The Author(s). 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data. |
spellingShingle | Software Wang, Mingjie Li, Jianfeng Zhang, Xiaonan Han, Yue Yu, Demin Zhang, Donghua Yuan, Zhenghong Yang, Zhitao Huang, Jinyan Zhang, Xinxin An integrated software for virus community sequencing data analysis |
title | An integrated software for virus community sequencing data analysis |
title_full | An integrated software for virus community sequencing data analysis |
title_fullStr | An integrated software for virus community sequencing data analysis |
title_full_unstemmed | An integrated software for virus community sequencing data analysis |
title_short | An integrated software for virus community sequencing data analysis |
title_sort | integrated software for virus community sequencing data analysis |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7227348/ https://www.ncbi.nlm.nih.gov/pubmed/32414327 http://dx.doi.org/10.1186/s12864-020-6744-4 |
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