Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 33,908

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Inference of Population Structure Using Multilocus Genotype Data

Pritchard, Jonathan K, Stephens, Matthew, Donnelly, Peter·2000·Genetics
DOI 10.1093/genetics/155.2.945
Open this paper in CoChat — free account

Abstract

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.

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 · 10.1093/genetics/155.2.945

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

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

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

Show all 2 references

Research works printed but not linked: 28

  1. Balding, 1994, DNA profile match probability calculations: how to allow for population stratification, relatedness, database selection and single bands, Forensic Sci. Int., 64, 125, 10.1016/0379-0738(94)90222-4 · DOI
  2. Balding, 1995, A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity, Genetica, 96, 3, 10.1007/BF01441146 · DOI · Paper page
  3. Bowcock, 1994, High resolution of human evolutionary trees with polymorphic microsatellites, Nature, 368, 455, 10.1038/368455a0 · DOI · Paper page
  4. Cavalli-Sforza, 1994, The History and Geography of Human Genes
  5. Chib, 1995, Marginal likelihood from the Gibbs output, J. Am. Stat. Assoc., 90, 1313, 10.1080/01621459.1995.10476635 · DOI · Paper page
  6. Chib, 1995, Understanding the Metropolis-Hastings algorithm, Am. Stat., 49, 327, 10.1080/00031305.1995.10476177 · DOI
  7. Davies, 1999, Determining the source of individuals: multilocus genotyping in nonequilibrium population genetics, TREE, 14, 17
  8. DiCiccio, 1997, Computing Bayes factors by posterior simulation and asymptotic approximations, J. Am. Stat. Assoc., 92, 903, 10.1080/01621459.1997.10474045 · DOI
  9. Ewens, 1995, The transmission/disequilibrium test: history, subdivision, and admixture, Am. J. Hum. Genet., 57, 455
  10. Felsenstein, 1993, PHYLIP (phylogeny inference package) version 3.5c. Technical report
  11. Foreman, 1997, Bayesian analysis of DNA profiling data in forensic identification applications, J. R. Stat. Soc. A, 160, 429, 10.1111/j.1467-985X.1997.00074.x · DOI
  12. Galbusera, 2000, Effective population size and gene flow in the globally, critically endangered Taita thrush, Turdus helleri, Conserv. Genet.
  13. Gilks, 1996, Introducing Markov chain Monte Carlo, 1
  14. Gilks, 1996, Markov Chain Monte Carlo in Practice
  15. Goldstein, 1997, Launching microsatellites: a review of mutation processes and methods of phylogenetic inference, J. Hered., 88, 335, 10.1093/oxfordjournals.jhered.a023114 · DOI · Paper page
  16. Green, 1995, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, 82, 711, 10.1093/biomet/82.4.711 · DOI
  17. Hudson, 1990, Gene genealogies and the coalescent process, 1
  18. Jorde, 1995, Origins and affinities of modern humans: a comparison of mitochondrial and nuclear genetic data, Am. J. Hum. Genet., 57, 523
  19. Mountain, 1997, Multilocus genotypes, a tree of individuals, and human evolutionary history, Am. J. Hum. Genet., 61, 705, 10.1086/515510 · DOI
  20. Paetkau, 1995, Microsatellite analysis of population structure in Canadian polar bears, Mol. Ecol., 4, 347, 10.1111/j.1365-294X.1995.tb00227.x · DOI
  21. Parra, 1998, Estimating African American admixture proportions by use of population-specific alleles, Am. J. Hum. Genet., 63, 1839, 10.1086/302148 · DOI · Paper page
  22. Raftery, 1996, Hypothesis testing and model selection, 163
  23. Rannala, 1997, Detecting immigration by using multilocus genotypes, Proc. Natl. Acad. Sci. USA, 94, 9197, 10.1073/pnas.94.17.9197 · DOI
  24. Richardson, 1997, On Bayesian analysis of mixtures with an unknown number of components, J. R. Stat. Soc. Ser. B, 59, 731, 10.1111/1467-9868.00095 · DOI · Paper page
  25. Roeder, 1998, Measuring heterogeneity in forensic databases using hierarchical Bayes models, Biometrika, 85, 269, 10.1093/biomet/85.2.269 · DOI
  26. Smouse, 1990, A genetic mixture analysis for use with incomplete source population-data, Can. J. Fish. Aquat. Sci., 47, 620, 10.1139/f90-070 · DOI
  27. Stephens, 2000, Bayesian analysis of mixtures with an unknown number of components—an alternative to reversible jump methods, Ann. Stat., 10.1214/aos/1016120364 · DOI
  28. Stephens, 2000, Dealing with label-switching in mixture models, J. R. Stat. Soc. Ser. B, 10.1111/1467-9868.00265 · DOI · Paper page

Cited by

Metadata

Authors
Pritchard, J. K., Stephens, M., & Donnelly, P.
Venue
Genetics
Publisher
Oxford University Press (OUP)
Published
2000-06-01
Volume
155
Issue
2
Pages
945-959
ISSN
  • 0016-6731 (ISSN-L)
  • 1943-2631
DOI
10.1093/genetics/155.2.945
OpenAlex
W2098126593
Cited by
33,908
References
2
FWCI
48.24
Type
journal article
Language
en
Open access
closed
Licence
academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)

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

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.