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Molecular Ecology
Article . 2018 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Molecular Ecology
Article
License: CC BY
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PubMed Central
Article . 2018
Data sources: PubMed Central
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How quantitative is metabarcoding: A meta‐analytical approach

Authors: Philip D. Lamb; Ewan Hunter; John K. Pinnegar; Simon Creer; Richard G. Davies; Martin I. Taylor;

How quantitative is metabarcoding: A meta‐analytical approach

Abstract

AbstractMetabarcoding 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.

Country
United Kingdom
Keywords

What Community Features Can and Cannot Be Quantified by Sequence Data, 570, Ecology, Species Specificity, DNA Barcoding, Taxonomic, Biomass, Diet

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
372
Top 0.1%
Top 1%
Top 0.1%
Green
hybrid