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How quantitative is metabarcoding: A meta‐analytical approach
Metabarcoding has been used in a range of ecological applications such as taxonomic assignment, dietary analysis and the analysis of environmental DNA. However, after a decade of use in these applications there is little consensus on the extent to which proportions of reads generated corresponds to...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7379500/ https://www.ncbi.nlm.nih.gov/pubmed/30408260 http://dx.doi.org/10.1111/mec.14920 |
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author | Lamb, Philip D. Hunter, Ewan Pinnegar, John K. Creer, Simon Davies, Richard G. Taylor, Martin I. |
author_facet | Lamb, Philip D. Hunter, Ewan Pinnegar, John K. Creer, Simon Davies, Richard G. Taylor, Martin I. |
author_sort | Lamb, Philip D. |
collection | PubMed |
description | Metabarcoding has been used in a range of ecological applications such as taxonomic assignment, dietary analysis and the analysis of environmental DNA. However, after a decade of use in these applications there is little consensus on the extent to which proportions of reads generated corresponds to the original proportions of species in a community. To quantify our current understanding, we conducted a structured review and meta‐analysis. The analysis suggests that a weak quantitative relationship may exist between the biomass and sequences produced (slope = 0.52 ± 0.34, p < 0.01), albeit with a large degree of uncertainty. None of the tested moderators, sequencing platform type, the number of species used in a trial or the source of DNA, were able to explain the variance. Our current understanding of the factors affecting the quantitative performance of metabarcoding is still limited: additional research is required before metabarcoding can be confidently utilized for quantitative applications. Until then, we advocate the inclusion of mock communities when metabarcoding as this facilitates direct assessment of the quantitative ability of any given study. |
format | Online Article Text |
id | pubmed-7379500 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73795002020-07-24 How quantitative is metabarcoding: A meta‐analytical approach Lamb, Philip D. Hunter, Ewan Pinnegar, John K. Creer, Simon Davies, Richard G. Taylor, Martin I. Mol Ecol What Community Features Can and Cannot Be Quantified by Sequence Data Metabarcoding has been used in a range of ecological applications such as taxonomic assignment, dietary analysis and the analysis of environmental DNA. However, after a decade of use in these applications there is little consensus on the extent to which proportions of reads generated corresponds to the original proportions of species in a community. To quantify our current understanding, we conducted a structured review and meta‐analysis. The analysis suggests that a weak quantitative relationship may exist between the biomass and sequences produced (slope = 0.52 ± 0.34, p < 0.01), albeit with a large degree of uncertainty. None of the tested moderators, sequencing platform type, the number of species used in a trial or the source of DNA, were able to explain the variance. Our current understanding of the factors affecting the quantitative performance of metabarcoding is still limited: additional research is required before metabarcoding can be confidently utilized for quantitative applications. Until then, we advocate the inclusion of mock communities when metabarcoding as this facilitates direct assessment of the quantitative ability of any given study. John Wiley and Sons Inc. 2018-12-07 2019-01 /pmc/articles/PMC7379500/ /pubmed/30408260 http://dx.doi.org/10.1111/mec.14920 Text en © 2018 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | What Community Features Can and Cannot Be Quantified by Sequence Data Lamb, Philip D. Hunter, Ewan Pinnegar, John K. Creer, Simon Davies, Richard G. Taylor, Martin I. How quantitative is metabarcoding: A meta‐analytical approach |
title | How quantitative is metabarcoding: A meta‐analytical approach |
title_full | How quantitative is metabarcoding: A meta‐analytical approach |
title_fullStr | How quantitative is metabarcoding: A meta‐analytical approach |
title_full_unstemmed | How quantitative is metabarcoding: A meta‐analytical approach |
title_short | How quantitative is metabarcoding: A meta‐analytical approach |
title_sort | how quantitative is metabarcoding: a meta‐analytical approach |
topic | What Community Features Can and Cannot Be Quantified by Sequence Data |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7379500/ https://www.ncbi.nlm.nih.gov/pubmed/30408260 http://dx.doi.org/10.1111/mec.14920 |
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