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Overview of Virus Metagenomic Classification Methods and Their Biological Applications
Metagenomics poses opportunities for clinical and public health virology applications by offering a way to assess complete taxonomic composition of a clinical sample in an unbiased way. However, the techniques required are complicated and analysis standards have yet to develop. This, together with t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5924777/ https://www.ncbi.nlm.nih.gov/pubmed/29740407 http://dx.doi.org/10.3389/fmicb.2018.00749 |
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author | Nooij, Sam Schmitz, Dennis Vennema, Harry Kroneman, Annelies Koopmans, Marion P. G. |
author_facet | Nooij, Sam Schmitz, Dennis Vennema, Harry Kroneman, Annelies Koopmans, Marion P. G. |
author_sort | Nooij, Sam |
collection | PubMed |
description | Metagenomics poses opportunities for clinical and public health virology applications by offering a way to assess complete taxonomic composition of a clinical sample in an unbiased way. However, the techniques required are complicated and analysis standards have yet to develop. This, together with the wealth of different tools and workflows that have been proposed, poses a barrier for new users. We evaluated 49 published computational classification workflows for virus metagenomics in a literature review. To this end, we described the methods of existing workflows by breaking them up into five general steps and assessed their ease-of-use and validation experiments. Performance scores of previous benchmarks were summarized and correlations between methods and performance were investigated. We indicate the potential suitability of the different workflows for (1) time-constrained diagnostics, (2) surveillance and outbreak source tracing, (3) detection of remote homologies (discovery), and (4) biodiversity studies. We provide two decision trees for virologists to help select a workflow for medical or biodiversity studies, as well as directions for future developments in clinical viral metagenomics. |
format | Online Article Text |
id | pubmed-5924777 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-59247772018-05-08 Overview of Virus Metagenomic Classification Methods and Their Biological Applications Nooij, Sam Schmitz, Dennis Vennema, Harry Kroneman, Annelies Koopmans, Marion P. G. Front Microbiol Microbiology Metagenomics poses opportunities for clinical and public health virology applications by offering a way to assess complete taxonomic composition of a clinical sample in an unbiased way. However, the techniques required are complicated and analysis standards have yet to develop. This, together with the wealth of different tools and workflows that have been proposed, poses a barrier for new users. We evaluated 49 published computational classification workflows for virus metagenomics in a literature review. To this end, we described the methods of existing workflows by breaking them up into five general steps and assessed their ease-of-use and validation experiments. Performance scores of previous benchmarks were summarized and correlations between methods and performance were investigated. We indicate the potential suitability of the different workflows for (1) time-constrained diagnostics, (2) surveillance and outbreak source tracing, (3) detection of remote homologies (discovery), and (4) biodiversity studies. We provide two decision trees for virologists to help select a workflow for medical or biodiversity studies, as well as directions for future developments in clinical viral metagenomics. Frontiers Media S.A. 2018-04-23 /pmc/articles/PMC5924777/ /pubmed/29740407 http://dx.doi.org/10.3389/fmicb.2018.00749 Text en Copyright © 2018 Nooij, Schmitz, Vennema, Kroneman and Koopmans. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Nooij, Sam Schmitz, Dennis Vennema, Harry Kroneman, Annelies Koopmans, Marion P. G. Overview of Virus Metagenomic Classification Methods and Their Biological Applications |
title | Overview of Virus Metagenomic Classification Methods and Their Biological Applications |
title_full | Overview of Virus Metagenomic Classification Methods and Their Biological Applications |
title_fullStr | Overview of Virus Metagenomic Classification Methods and Their Biological Applications |
title_full_unstemmed | Overview of Virus Metagenomic Classification Methods and Their Biological Applications |
title_short | Overview of Virus Metagenomic Classification Methods and Their Biological Applications |
title_sort | overview of virus metagenomic classification methods and their biological applications |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5924777/ https://www.ncbi.nlm.nih.gov/pubmed/29740407 http://dx.doi.org/10.3389/fmicb.2018.00749 |
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