Extracting abundance information from DNA‐based data

Luo, Mingjie, Yinqiu, Ji, Warton, David and Yu, Douglas W. (2022) Extracting abundance information from DNA‐based data. Molecular Ecology Resources. ISSN 1755-098X

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Abstract

The accurate extraction of species-abundance information from DNA-based data (metabarcoding, metagenomics) could contribute usefully to diet analysis and foodweb reconstruction, the inference of species interactions, the modelling of population dynamics and species distributions, the biomonitoring of environmental state and change, and the inference of false positives and negatives. However, multiple sources of bias and noise in sampling and processing combine to inject error into DNA-based data sets. To understand how to extract abundance information, it is useful to distinguish two concepts. (i) Within-sample across-species quantification describes relative species abundances in one sample. (ii) Across-sample within-species quantification describes how the abundance of each individual species varies from sample to sample, such as over a time series, an environmental gradient or different experimental treatments. First, we review the literature on methods to recover across-species abundance information (by removing what we call “species pipeline biases”) and within-species abundance information (by removing what we call “pipeline noise”). We argue that many ecological questions can be answered with just within-species quantification, and we therefore demonstrate how to use a “DNA spike-in” to correct for pipeline noise and recover within-species abundance information. We also introduce a modelbased estimator that can be used on data sets without a physical spike-in to approximate and correct for pipeline noise.

Item Type: Article
Faculty \ School: Faculty of Science > School of Biological Sciences
Depositing User: LivePure Connector
Date Deposited: 29 Sep 2022 08:30
Last Modified: 21 Oct 2022 01:44
URI: https://ueaeprints.uea.ac.uk/id/eprint/88705
DOI: 10.1111/1755-0998.13703

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