Evidence map›Paper›PMID 32620910›Full record

ArticleScientific data2020

MARES, a replicable pipeline and curated reference database for marine eukaryote metabarcoding.

Vanessa Arranz, William S Pearman, J David Aguirre, Libby Liggins

Abstract readDataset
In one paragraph

Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
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  4. Principles for Constructing DNA Barcode Reference Libraries.Methods in molecular biology (Clifton, N.J.) · 2024
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  5. Article
  6. Review
  7. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Vanessa Arranz *School of Natural and Computational Sciences, Massey University Auckland, Albany, Auckland, 0745, New Zealand. vanearranz@hotmail.com.ORCID http://orcid.org/0000-0002-3404-5317
William S Pearman *School of Natural and Computational Sciences, Massey University Auckland, Albany, Auckland, 0745, New Zealand.ORCID http://orcid.org/0000-0002-7265-8499
J David AguirreSchool of Natural and Computational Sciences, Massey University Auckland, Albany, Auckland, 0745, New Zealand.ORCID http://orcid.org/0000-0001-7520-441X
Libby LigginsSchool of Natural and Computational Sciences, Massey University Auckland, Albany, Auckland, 0745, New Zealand.ORCID http://orcid.org/0000-0003-1143-2346

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of DNA metabarcoding to characterise the biodiversity of environmental and community samples has exploded in recent years. However, taxonomic inferences from these studies are contingent on the quality and completeness of the sequence reference database used to characterise sample species-composition. In response, studies often develop custom reference databases to improve species assignment. The disadvantage of this approach is that it limits the potential for database re-use, and the transferability of inferences across studies. Here, we present the MARine Eukaryote Species (MARES) reference database for use in marine metabarcoding studies, created using a transparent and reproducible pipeline. MARES includes all COI sequences available in GenBank and BOLD for marine taxa, unified into a single taxonomy. Our pipeline facilitates the curation of sequences, synonymization of taxonomic identifiers used by different repositories, and formatting these data for use in taxonomic assignment tools. Overall, MARES provides a benchmark COI reference database for marine eukaryotes, and a standardised pipeline for (re)producing reference databases enabling integration and fair comparison of marine DNA metabarcoding results.

Indexed as

Databases, FactualDNA Barcoding, TaxonomicAnimalsAquatic OrganismsEukaryota

Identifiers

PMID32620910
PMCPMC7334202

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.