Evidence map›Paper›PMID 32753664›Full record

ReviewHeredity2020

The influence of a priori grouping on inference of genetic clusters: simulation study and literature review of the DAPC method.

Joshua M Miller, Catherine I Cullingham, Rhiannon M Peery

Abstract readReview
In one paragraph

Review in Heredity, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.

0numbers the graph read from it
0cells of the map it votes in
70citing 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

70 citing papers in PubMed.

  1. Article
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  4. Genetic Structure of Blue Ling,Ecology and evolution · 2026
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10 more citing papers are in PubMed but not listed here.

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

3 authors.

Joshua M MillerDepartment of Biological Sciences, University of Alberta, Edmonton, AB, Canada. jmm1@ualberta.ca.ORCID http://orcid.org/0000-0002-4019-7675
Catherine I CullinghamDepartment of Biology, Carleton University, Ottawa, ON, Canada.
Rhiannon M PeeryDepartment of Biological Sciences, University of Alberta, Edmonton, AB, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inference of genetic clusters is a key aim of population genetics, sparking development of numerous analytical methods. Within these, there is a conceptual divide between finding de novo structure versus assessment of a priori groups. Recently developed, Discriminant Analysis of Principal Components (DAPC), combines discriminant analysis (DA) with principal component (PC) analysis. When applying DAPC, the groups used in the DA (specified a priori or described de novo) need to be carefully assessed. While DAPC has rapidly become a core technique, the sensitivity of the method to misspecification of groups and how it is being empirically applied, are unknown. To address this, we conducted a simulation study examining the influence of a priori versus de novo group designations, and a literature review of how DAPC is being applied. We found that with a priori groupings, distance between genetic clusters reflected underlying F

Indexed as

Discriminant AnalysisGenetics, PopulationPrincipal Component AnalysisCluster Analysis

Identifiers

PMID32753664
PMCPMC7553915

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.