Evidence map›Paper›PMID 29938015›Full record

ArticleMethods in ecology and evolution2018

A fast likelihood solution to the genetic clustering problem.

Marie-Pauline Beugin, Thibault Gayet, Dominique Pontier, Sébastien Devillard, Thibaut Jombart

Abstract read
In one paragraph

Article in Methods in ecology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

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  18. A community genomics approach to natural hybridization.Proceedings. Biological sciences · 2023
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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

5 authors.

Marie-Pauline BeuginUniv Lyon Laboratoire de Biométrie et Biologie Evolutive CNRS Université Claude Bernard Lyon 1 Villeurbanne France.
Thibault GayetUniv Lyon Laboratoire de Biométrie et Biologie Evolutive CNRS Université Claude Bernard Lyon 1 Villeurbanne France.
Dominique PontierUniv Lyon Laboratoire de Biométrie et Biologie Evolutive CNRS Université Claude Bernard Lyon 1 Villeurbanne France.
Sébastien DevillardUniv Lyon Laboratoire de Biométrie et Biologie Evolutive CNRS Université Claude Bernard Lyon 1 Villeurbanne France.
Thibaut JombartDepartment of Infectious Disease Epidemiology School of Public Health MRC Centre for Outbreak Analysis and Modelling Imperial College London London UK.ORCID 0000-0003-2226-8692

Funding

Medical Research Council MR/R015600/1
6 · The paper itself

Abstract

The investigation of genetic clusters in natural populations is an ubiquitous problem in a range of fields relying on the analysis of genetic data, such as molecular ecology, conservation biology and microbiology. Typically, genetic clusters are defined as distinct panmictic populations, or parental groups in the context of hybridisation. Two types of methods have been developed for identifying such clusters: model-based methods, which are usually computer-intensive but yield results which can be interpreted in the light of an explicit population genetic model, and geometric approaches, which are less interpretable but remarkably faster.Here, we introduce

Indexed as

EM algorithmgenetic assignmentgenetic clusteringhybridisationmicrosatellitespopulation membershiprelative performancesSNP

Identifiers

PMID29938015
PMCPMC5993310

What OpenQuestion holds

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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.