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16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing
BACKGROUND: Pathogen detection in clinical samples based on 16S metagenomic sequencing technology in microbiology laboratories is an important strategy for clinical diagnosis, public health surveillance, and investigations of outbreaks. However, the implementation of the technology is limited by its...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751400/ https://www.ncbi.nlm.nih.gov/pubmed/29297318 http://dx.doi.org/10.1186/s12859-017-1975-3 |
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author | Miao, Jiaojiao Han, Na Qiang, Yujun Zhang, Tingting Li, Xiuwen Zhang, Wen |
author_facet | Miao, Jiaojiao Han, Na Qiang, Yujun Zhang, Tingting Li, Xiuwen Zhang, Wen |
author_sort | Miao, Jiaojiao |
collection | PubMed |
description | BACKGROUND: Pathogen detection in clinical samples based on 16S metagenomic sequencing technology in microbiology laboratories is an important strategy for clinical diagnosis, public health surveillance, and investigations of outbreaks. However, the implementation of the technology is limited by its accuracy and the time required for bioinformatics analysis. Therefore, a simple, standardized, and rapid analysis pipeline from the receipt of clinical samples to the generation of a test report is needed to increase the use of metagenomic analyses in clinical settings. RESULTS: We developed a comprehensive bioinformatics analysis pipeline for the identification of pathogens in clinical samples based on 16S metagenomic sequencing data, named 16SPIP. This pipeline offers two analysis modes (fast and sensitive mode) for the rapid conversion of clinical 16S metagenomic data to test reports for pathogen detection. The pipeline includes tools for data conversion, quality control, merging of paired-end reads, alignment, and pathogen identification. We validated the feasibility and accuracy of the pipeline using a combination of culture and whole-genome shotgun (WGS) metagenomic analyses. CONCLUSIONS: 16SPIP may be effective for the analysis of 16S metagenomic sequencing data for real-time, rapid, and unbiased pathogen detection in clinical samples. |
format | Online Article Text |
id | pubmed-5751400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57514002018-01-05 16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing Miao, Jiaojiao Han, Na Qiang, Yujun Zhang, Tingting Li, Xiuwen Zhang, Wen BMC Bioinformatics Research BACKGROUND: Pathogen detection in clinical samples based on 16S metagenomic sequencing technology in microbiology laboratories is an important strategy for clinical diagnosis, public health surveillance, and investigations of outbreaks. However, the implementation of the technology is limited by its accuracy and the time required for bioinformatics analysis. Therefore, a simple, standardized, and rapid analysis pipeline from the receipt of clinical samples to the generation of a test report is needed to increase the use of metagenomic analyses in clinical settings. RESULTS: We developed a comprehensive bioinformatics analysis pipeline for the identification of pathogens in clinical samples based on 16S metagenomic sequencing data, named 16SPIP. This pipeline offers two analysis modes (fast and sensitive mode) for the rapid conversion of clinical 16S metagenomic data to test reports for pathogen detection. The pipeline includes tools for data conversion, quality control, merging of paired-end reads, alignment, and pathogen identification. We validated the feasibility and accuracy of the pipeline using a combination of culture and whole-genome shotgun (WGS) metagenomic analyses. CONCLUSIONS: 16SPIP may be effective for the analysis of 16S metagenomic sequencing data for real-time, rapid, and unbiased pathogen detection in clinical samples. BioMed Central 2017-12-28 /pmc/articles/PMC5751400/ /pubmed/29297318 http://dx.doi.org/10.1186/s12859-017-1975-3 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 | Research Miao, Jiaojiao Han, Na Qiang, Yujun Zhang, Tingting Li, Xiuwen Zhang, Wen 16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing |
title | 16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing |
title_full | 16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing |
title_fullStr | 16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing |
title_full_unstemmed | 16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing |
title_short | 16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing |
title_sort | 16spip: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16s metagenomic sequencing |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751400/ https://www.ncbi.nlm.nih.gov/pubmed/29297318 http://dx.doi.org/10.1186/s12859-017-1975-3 |
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