Evidence map›Paper›PMID 23504127›Full record

ArticleGenetica2013

Tests of two methods for identifying founder effects in metapopulations reveal substantial type II error.

R Graham Reynolds, Benjamin M Fitzpatrick

Abstract read
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In one paragraph

Article in Genetica, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
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

2 citing papers in PubMed, 13 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

R Graham ReynoldsDepartment of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996, USA. rgraham.reynolds@umb.edu
Benjamin M Fitzpatrick
University of Tennessee at Knoxville · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic analysis has been promoted as a way to reconstruct recent historical dynamics ("historical demography") by screening for signatures of events, such as bottlenecks, that disrupt equilibrium patterns of variation. Such analyses might also identify "metapopulation" processes like extinction and recolonization or source-sink dynamics, but this potential remains largely unrealized. Here we use simulations to test the ability of two currently used strategies to distinguish between a set of interconnected subpopulations (demes) that have undergone bottlenecks or extinction and recolonization events (metapopulation dynamics) from a set of static demes. The first strategy, decomposed pairwise regression, provides a holistic test for heterogeneity among demes in their patterns of isolation-by-distance. This method suffered from a type II error rate of 59-100 %, depending on parameter conditions. The second strategy tests for deviations from mutation-drift equilibrium on a deme-by-deme basis to identify sites likely to have experienced recent bottlenecks or founder effects. Although bottleneck tests have good statistical power for single populations with recent population declines, their validity in structured populations has been called into question, and they have not been tested in a metapopulation context with immigration (or colonization) and population recovery. Our simulations of hypothetical metapopulations show that population recovery can rapidly eliminate the statistical signature of a bottleneck, and that moderate levels of gene flow can generate a false signal of recent population growth for demes in equilibrium. Although we did not cover all possible metapopulation scenarios, the performance of the tests was disappointing. Our results indicate that these methods might often fail to identify population bottlenecks and founder effects if population recovery and/or gene flow are influential demographic features of the study system.

Indexed as

Founder EffectModels, GeneticAnimalsGene FlowGenetic DriftGenetics, PopulationHumans

Identifiers

PMID23504127
OpenAlexW2067355825

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.