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OpenContami: a web-based application for detecting microbial contaminants in next-generation sequencing data
SUMMARY: Microorganisms infect and contaminate eukaryotic cells during the course of biological experiments. Because microbes influence host cell biology and may therefore lead to erroneous conclusions, a computational platform that facilitates decontamination is indispensable. Recent studies show t...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479661/ https://www.ncbi.nlm.nih.gov/pubmed/33576798 http://dx.doi.org/10.1093/bioinformatics/btab101 |
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author | Park, Sung-Joon Nakai, Kenta |
author_facet | Park, Sung-Joon Nakai, Kenta |
author_sort | Park, Sung-Joon |
collection | PubMed |
description | SUMMARY: Microorganisms infect and contaminate eukaryotic cells during the course of biological experiments. Because microbes influence host cell biology and may therefore lead to erroneous conclusions, a computational platform that facilitates decontamination is indispensable. Recent studies show that next-generation sequencing (NGS) data can be used to identify the presence of exogenous microbial species. Previously, we proposed an algorithm to improve detection of microbes in NGS data. Here, we developed an online application, OpenContami, which allows researchers easy access to the algorithm via interactive web-based interfaces. We have designed the application by incorporating a database comprising analytical results from a large-scale public dataset and data uploaded by users. The database serves as a reference for assessing user data and provides a list of genera detected from negative blank controls as a ‘blacklist’, which is useful for studying human infectious diseases. OpenContami offers a comprehensive overview of exogenous species in NGS datasets; as such, it will increase our understanding of the impact of microbial contamination on biological and pathological traits. AVAILABILITY AND IMPLEMENTATION: OpenContami is freely available at: https://openlooper.hgc.jp/opencontami/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8479661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84796612021-09-30 OpenContami: a web-based application for detecting microbial contaminants in next-generation sequencing data Park, Sung-Joon Nakai, Kenta Bioinformatics Applications Notes SUMMARY: Microorganisms infect and contaminate eukaryotic cells during the course of biological experiments. Because microbes influence host cell biology and may therefore lead to erroneous conclusions, a computational platform that facilitates decontamination is indispensable. Recent studies show that next-generation sequencing (NGS) data can be used to identify the presence of exogenous microbial species. Previously, we proposed an algorithm to improve detection of microbes in NGS data. Here, we developed an online application, OpenContami, which allows researchers easy access to the algorithm via interactive web-based interfaces. We have designed the application by incorporating a database comprising analytical results from a large-scale public dataset and data uploaded by users. The database serves as a reference for assessing user data and provides a list of genera detected from negative blank controls as a ‘blacklist’, which is useful for studying human infectious diseases. OpenContami offers a comprehensive overview of exogenous species in NGS datasets; as such, it will increase our understanding of the impact of microbial contamination on biological and pathological traits. AVAILABILITY AND IMPLEMENTATION: OpenContami is freely available at: https://openlooper.hgc.jp/opencontami/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-02-12 /pmc/articles/PMC8479661/ /pubmed/33576798 http://dx.doi.org/10.1093/bioinformatics/btab101 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Park, Sung-Joon Nakai, Kenta OpenContami: a web-based application for detecting microbial contaminants in next-generation sequencing data |
title | OpenContami: a web-based application for detecting microbial contaminants in next-generation sequencing data |
title_full | OpenContami: a web-based application for detecting microbial contaminants in next-generation sequencing data |
title_fullStr | OpenContami: a web-based application for detecting microbial contaminants in next-generation sequencing data |
title_full_unstemmed | OpenContami: a web-based application for detecting microbial contaminants in next-generation sequencing data |
title_short | OpenContami: a web-based application for detecting microbial contaminants in next-generation sequencing data |
title_sort | opencontami: a web-based application for detecting microbial contaminants in next-generation sequencing data |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479661/ https://www.ncbi.nlm.nih.gov/pubmed/33576798 http://dx.doi.org/10.1093/bioinformatics/btab101 |
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