Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 344

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

The Confounding Effect of Population Structure on Bayesian Skyline Plot Inferences of Demographic History

Heller, Rasmus, Chikhi, Lounes, Siegismund, Hans Redlef·2013·PLoS ONE
DOI 10.1371/journal.pone.0062992PMC PMC3646956
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0062992

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 The structure effect in a 40-deme constant-size island model. For each scenario, 100 replicate data sets were generated and analysed with EBSPs. Light blue lines represent the median inferred female effective population size through time from each replicate. Time is measured in kya or thousands of years ago and is based on a molecular clock for buffalo D-loop sequences. Bold black lines represent the simulated size of the structured population (500 females * 40 demes = 20,000 females). Insert into each panel is a histogram of PSC values (on x-axis; see main text) across replicates. Dashed lines show the prior distribution for PSC. The y-axis in the insert histograms marks the frequency of occurrence in each PSC bin out of 100 replicates.
Figure 1 The structure effect in a 40-deme constant-size island model. For each scenario, 100 replicate data sets were generated and analysed with EBSPs. Light blue lines represent the median inferred female effective population size through time from each replicate. Time is measured in kya or thousands of years ago and is based on a molecular clock for buffalo D-loop sequences. Bold black lines represent the simulated size of the structured population (500 females * 40 demes = 20,000 females). Insert into each panel is a histogram of PSC values (on x-axis; see main text) across replicates. Dashed lines show the prior distribution for PSC. The y-axis in the insert histograms marks the frequency of occurrence in each PSC bin out of 100 replicates.CC BY · PubMed Central
Figure 2 The structure effect in a 40-deme island model with demographic change. As Fig. 1, but the bold black line shows the simulated demographic change scenarios (see main text) with one or two changes in population size. Only the intermediary level of gene flow (Nfm = 1.25) is shown.
Figure 2 The structure effect in a 40-deme island model with demographic change. As Fig. 1, but the bold black line shows the simulated demographic change scenarios (see main text) with one or two changes in population size. Only the intermediary level of gene flow (Nfm = 1.25) is shown.CC BY · PubMed Central
Figure 3 Two demographic scenarios under a real data informed island model. As Figs. 1 and 2, but the island model was modified to conform to the migration matrix estimated for a real biological system, the African buffalo. Only pooled and scattered sampling is shown. Bold lines mark the appropriate simulated population size. Replication was slightly different from Fig. 1 and 2 because it now matters which demes were included in the sample, see main text. Note also that the number of demes was 34, so the sum of the deme size differs from Fig. 1 and 2 (17,000 as opposed to 20,000 females).
Figure 3 Two demographic scenarios under a real data informed island model. As Figs. 1 and 2, but the island model was modified to conform to the migration matrix estimated for a real biological system, the African buffalo. Only pooled and scattered sampling is shown. Bold lines mark the appropriate simulated population size. Replication was slightly different from Fig. 1 and 2 because it now matters which demes were included in the sample, see main text. Note also that the number of demes was 34, so the sum of the deme size differs from Fig. 1 and 2 (17,000 as opposed to 20,000 females).CC BY · PubMed Central
Figure 4 Three different sampling strategies for real data from the buffalo. Local, pooled and scattered sampling of real D-loop data from 34 African buffalo populations. The replication of each sampling strategy involved random drawing of the appropriate number of samples from demes as explained in the main text.
Figure 4 Three different sampling strategies for real data from the buffalo. Local, pooled and scattered sampling of real D-loop data from 34 African buffalo populations. The replication of each sampling strategy involved random drawing of the appropriate number of samples from demes as explained in the main text.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 27

  1. OG Pybus, 2000, An integrated framework for the inference of viral population history from reconstructed genealogies, Genetics, 155, 1429, 10.1093/genetics/155.3.1429 · DOI
  2. AJ Drummond, 2005, Bayesian coalescent inference of past population dynamics from molecular sequences, Mol Biol Evol, 22, 1185, 10.1093/molbev/msi103 · DOI
  3. QD Atkinson, 2008, mtDNA variation predicts population size in humans and reveals a major southern Asian chapter in human prehistory, Mol Biol Evol, 25, 468, 10.1093/molbev/msm277 · DOI
  4. NJR Fagundes, 2008, A reevaluation of the native American mtDNA genome diversity and its bearing on the models of early colonization of Beringia, PLoS One, 3(9), e3157, 10.1371/journal.pone.0003157 · DOI
  5. B Shapiro, 2004, Rise and fall of the Beringian steppe bison, Science, 306, 1561, 10.1126/science.1101074 · DOI
  6. ED Lorenzen, 2011, Species-specific responses of Late Quaternary megafauna to climate and humans, Nature, 479, 359, 10.1038/nature10574 · DOI · Paper page
  7. T Städler, 2009, The impact of sampling schemes on the site frequency spectrum in nonequilibrium subdivided populations, Genetics, 182, 205, 10.1534/genetics.108.094904 · DOI
  8. L Chikhi, 2010, The confounding effects of population structure, genetic diversity and the sampling scheme on the detection and quantification of population size changes, Genetics, 186, 983, 10.1534/genetics.110.118661 · DOI
  9. MB Peter, 2010, Distinguishing between population bottleneck and population subdivision by a Bayesian model choice procedure, Mol Ecol, 19, 4648, 10.1111/j.1365-294X.2010.04783.x · DOI
  10. Heled J, Drummond AJ (2008) Bayesian inference of population size history from multiple loci. BMC Evol Biol 8:doi:10.1186/1471-2148-8-289. · DOI
  11. SYW Ho, 2011, Skyline-plot methods for estimating demographic history from nucleotide sequences, Mol Ecol Resour, 11, 423, 10.1111/j.1755-0998.2011.02988.x · DOI
  12. J Wakeley, 1999, Non-equilibrium migration in human history, Genetics, 153, 1836, 10.1093/genetics/153.4.1863 · DOI
  13. MA Beaumont, 2004, Recent developments in genetic data analysis: What can they tell us about human demographic history?, Heredity, 92, 365, 10.1038/sj.hdy.6800447 · DOI
  14. R Nielsen, 2009, Statistical inferences in phylogeography, Mol Ecol, 18, 1034, 10.1111/j.1365-294X.2008.04059.x · DOI
  15. JR Pannell, 2003, Coalescence in a metapopulation with recurrent local extinction and recolonization, Evolution, 57, 949, 10.1111/j.0014-3820.2003.tb00307.x · DOI
  16. MA Beaumont, 1999, Detecting population expansion and decline using microsatellites, Genetics, 153, 2013, 10.1093/genetics/153.4.2013 · DOI
  17. Smitz N, Berthouly C, Cornelis D, Heller R, Van Hooft WF, <etal>et al</etal>.. (2013) Pan-African genetic structure in the African buffalo (Syncerus caffer): Investigating intraspecific divergence. Accepted for publication, PLoS One. · DOI
  18. R Heller, 2008, Mid-Holocene decline in African buffalos inferred from Bayesian coalescent-based analyses of microsatellites and mitochondrial DNA, Mol Ecol, 17, 4845, 10.1111/j.1365-294X.2008.03961.x · DOI
  19. R Heller, 2012, Cape buffalo mitogenomics reveals a Holocene shift in the African human-megafauna dynamics, Mol Ecol, 21, 3947, 10.1111/j.1365-294X.2012.05671.x · DOI
  20. YL Chan, 2006, Bayesian estimation of the timing and severity of a population bottleneck from ancient DNA, PLoS Genet, 2(4), e59, 10.1371/journal.pgen.0020059 · DOI
  21. RR Hudson, 1992, Estimation of levels of gene flow from DNA sequence data, Genetics, 132, 583, 10.1093/genetics/132.2.583 · DOI
  22. MC Whitlock, 1999, Indirect measures of gene flow and migration: FST ≠ 1/(4Nm +1), Heredity, 82, 117, 10.1038/sj.hdy.6884960 · DOI
  23. N Ray, 2003, Intra-deme molecular diversity in spatially expanding populations, Mol Biol Evol, 29, 76, 10.1093/molbev/msg009 · DOI
  24. Nordborg M, Krone SM (2002) Separation of time scales and convergence to the coalescent in structured populations, 194–232 in Modern Developments in Theoretical Population Genetics: The Legacy of Gustave Malécot, edited by M. Slatkin and M. Veuille. Oxford University Press, Oxford. · DOI
  25. P Sjödin, 2005, On the meaning and existence of an effective population size, Genetics, 169, 1061, 10.1534/genetics.104.026799 · DOI
  26. MK Kuhner, 2006, LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters, Bioinformatics, 22, 768, 10.1093/bioinformatics/btk051 · DOI
  27. J Hey, 2007, Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics, Proc Natl Acad Sci USA, 104, 2785, 10.1073/pnas.0611164104 · DOI

Cited by

See all 344

Metadata

Authors
Heller, R., Chikhi, L., & Siegismund, H. R.
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2013-05-07
Volume
8
Issue
5
Pages
e62992
ISSN
1932-6203
DOI
10.1371/journal.pone.0062992
PMC
PMC3646956
Cited by
344
References
3
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (unspecified)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review