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The K = 2 conundrum.

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TLDR
This review suggests that many studies may have been over‐ or underestimating population genetic structure; both scenarios have serious consequences, particularly with respect to conservation and management.
Abstract
Assessments of population genetic structure have become an increasing focus as they can provide valuable insight into patterns of migration and gene flow structure, the most highly cited of several clustering-based methods, was developed to provide robust estimates without the need for populations to be determined a priori structure introduces the problem of selecting the optimal number of clusters, and as a result, the ΔK method was proposed to assist in the identification of the "true" number of clusters In our review of 1,264 studies using structure to explore population subdivision, studies that used ΔK were more likely to identify K = 2 (54%, 443/822) than studies that did not use ΔK (21%, 82/386) A troubling finding was that very few studies performed the hierarchical analysis recommended by the authors of both ΔK and structure to fully explore population subdivision Furthermore, extensions of earlier simulations indicate that, with a representative number of markers, ΔK frequently identifies K = 2 as the top level of hierarchical structure, even when more subpopulations are present This review suggests that many studies may have been over- or underestimating population genetic structure; both scenarios have serious consequences, particularly with respect to conservation and management We recommend publication standards for population structure results so that readers can assess the implications of the results given their own understanding of the species biology

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Citations
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A tutorial on how not to over-interpret STRUCTURE and ADMIXTURE bar plots

TL;DR: An approach is implemented to assess the goodness of fit of the model using the ancestry “palettes” estimated by CHROMOPAINTER and apply it to both simulated data and real case studies, allowing a richer and more robust analysis of recent demographic history.
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The influence of a priori grouping on inference of genetic clusters: simulation study and literature review of the DAPC method.

TL;DR: It was found that with a priori groupings, distance between genetic clusters reflected underlying FST, and when migration rates were high and groups were described de novo there was considerable inaccuracy, both in terms of the number of genetic clusters suggested and placement of individuals into those clusters.
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OptM: estimating the optimal number of migration edges on population trees using Treemix.

TL;DR: In this paper, an optimal value of m can be inferred from the second-order rate of change in likelihood (Δm) across incremental values of m. This method has been implemented in a freely available R package called "OptM" and as a web application (https://rfitak.shinyapps.io/OptM/) to interface directly with the output files of Treemix.
References
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Journal ArticleDOI

Clumpak: a program for identifying clustering modes and packaging population structure inferences across K

TL;DR: Clumpak, available at http://clumpak.tau.ac.il, simplifies the use of model-based analyses of population structure in population genetics and molecular ecology by automating the postprocessing of results of model‐based population structure analyses.
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Detecting immigration by using multilocus genotypes

TL;DR: The test has power to detect immigrant ancestors, for these data, up to two generations in the past even though the overall differentiation of allele frequencies among populations is low.
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Microsatellite analysis of population structure in Canadian polar bears.

TL;DR: Using eight hypervariable microsatellite loci to study the genetic relationships between four Canadian polar bear populations indicates that gene flow between local populations is restricted despite the long‐distance seasonal movements undertaken by polar bears.
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Considering evolutionary processes in conservation biology.

TL;DR: This work argues for a broader categorization of population distinctiveness based on concepts of ecological and genetic exchangeability (sensu Templeton), which are more relevant for conservation.
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What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity.

TL;DR: It is suggested several quantitative criteria that might be used to determine when groups of individuals are different enough to be considered ‘populations’, and a simple algorithm based on a multilocus contingency test of allele frequencies in pairs of samples has high power to detect the true number of populations but requires more rigorous statistical evaluation.
Related Papers (5)
Trending Questions (1)
What are the detriments of k 10 2?

The provided paper does not mention any detriments of k = 2. The paper discusses the use of the ΔK method to identify the optimal number of clusters in population genetic structure studies.