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Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade
Phylogenetic placement refers to a family of tools and methods to analyze, visualize, and interpret the tsunami of metagenomic sequencing data generated by high-throughput sequencing. Compared to alternative (e. g., similarity-based) methods, it puts metabarcoding sequences into a phylogenetic conte...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580882/ https://www.ncbi.nlm.nih.gov/pubmed/36304302 http://dx.doi.org/10.3389/fbinf.2022.871393 |
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author | Czech, Lucas Stamatakis, Alexandros Dunthorn, Micah Barbera, Pierre |
author_facet | Czech, Lucas Stamatakis, Alexandros Dunthorn, Micah Barbera, Pierre |
author_sort | Czech, Lucas |
collection | PubMed |
description | Phylogenetic placement refers to a family of tools and methods to analyze, visualize, and interpret the tsunami of metagenomic sequencing data generated by high-throughput sequencing. Compared to alternative (e. g., similarity-based) methods, it puts metabarcoding sequences into a phylogenetic context using a set of known reference sequences and taking evolutionary history into account. Thereby, one can increase the accuracy of metagenomic surveys and eliminate the requirement for having exact or close matches with existing sequence databases. Phylogenetic placement constitutes a valuable analysis tool per se, but also entails a plethora of downstream tools to interpret its results. A common use case is to analyze species communities obtained from metagenomic sequencing, for example via taxonomic assignment, diversity quantification, sample comparison, and identification of correlations with environmental variables. In this review, we provide an overview over the methods developed during the first 10 years. In particular, the goals of this review are 1) to motivate the usage of phylogenetic placement and illustrate some of its use cases, 2) to outline the full workflow, from raw sequences to publishable figures, including best practices, 3) to introduce the most common tools and methods and their capabilities, 4) to point out common placement pitfalls and misconceptions, 5) to showcase typical placement-based analyses, and how they can help to analyze, visualize, and interpret phylogenetic placement data. |
format | Online Article Text |
id | pubmed-9580882 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95808822022-10-26 Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade Czech, Lucas Stamatakis, Alexandros Dunthorn, Micah Barbera, Pierre Front Bioinform Bioinformatics Phylogenetic placement refers to a family of tools and methods to analyze, visualize, and interpret the tsunami of metagenomic sequencing data generated by high-throughput sequencing. Compared to alternative (e. g., similarity-based) methods, it puts metabarcoding sequences into a phylogenetic context using a set of known reference sequences and taking evolutionary history into account. Thereby, one can increase the accuracy of metagenomic surveys and eliminate the requirement for having exact or close matches with existing sequence databases. Phylogenetic placement constitutes a valuable analysis tool per se, but also entails a plethora of downstream tools to interpret its results. A common use case is to analyze species communities obtained from metagenomic sequencing, for example via taxonomic assignment, diversity quantification, sample comparison, and identification of correlations with environmental variables. In this review, we provide an overview over the methods developed during the first 10 years. In particular, the goals of this review are 1) to motivate the usage of phylogenetic placement and illustrate some of its use cases, 2) to outline the full workflow, from raw sequences to publishable figures, including best practices, 3) to introduce the most common tools and methods and their capabilities, 4) to point out common placement pitfalls and misconceptions, 5) to showcase typical placement-based analyses, and how they can help to analyze, visualize, and interpret phylogenetic placement data. Frontiers Media S.A. 2022-05-26 /pmc/articles/PMC9580882/ /pubmed/36304302 http://dx.doi.org/10.3389/fbinf.2022.871393 Text en Copyright © 2022 Czech, Stamatakis, Dunthorn and Barbera. https://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(s) 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 | Bioinformatics Czech, Lucas Stamatakis, Alexandros Dunthorn, Micah Barbera, Pierre Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade |
title | Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade |
title_full | Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade |
title_fullStr | Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade |
title_full_unstemmed | Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade |
title_short | Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade |
title_sort | metagenomic analysis using phylogenetic placement—a review of the first decade |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580882/ https://www.ncbi.nlm.nih.gov/pubmed/36304302 http://dx.doi.org/10.3389/fbinf.2022.871393 |
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