Evidence map›Paper›PMID 16355252›Full record

ArticlePLoS genetics2005

Clines, clusters, and the effect of study design on the inference of human population structure.

Noah A Rosenberg, Saurabh Mahajan, Sohini Ramachandran, Chengfeng Zhao, Jonathan K Pritchard, Marcus W Feldman

Abstract read
In one paragraph

Article in PLoS genetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 234 papers.

0numbers the graph read from it
0cells of the map it votes in
234citing 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

234 citing papers in PubMed.

  1. Article
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  5. Genetic and genomic insights of the Comcáac people.Journal of community genetics · 2025
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  9. The risk of biological race.History and philosophy of the life sciences · 2025
    Article
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  13. Article
  14. Article
  15. Impediments to countering racist pseudoscience.Evolutionary human sciences · 2025
    Article
  16. Genes, culture, and scientific racism.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  17. Article
  18. Article
  19. Article
  20. Article

174 more citing papers are in PubMed but not listed here.

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

6 authors.

Noah A RosenbergDepartment of Human Genetics, Bioinformatics Program, and the Life Sciences Institute, University of Michigan, Ann Arbor, Michigan, USA. rnoah@umich.edu
Saurabh Mahajan
Sohini Ramachandran
Chengfeng Zhao
Jonathan K Pritchard
Marcus W Feldman

Funding

INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
MAMMALIAN GENOTYPING SERVICEN01HV048141 · HV · MARSHFIELD CLINIC RESEARCH FOUNDATION · PI WEBER, JAMES L. · 1994 to 2000
$3.1M
POPULATION GENETICS THEORYR01GM028016 · NIGMS · STANFORD UNIVERSITY · PI FELDMAN, MARCUS W · 1985 to 2010
$2.5M
NHGRI NIH HHS T32 HG000044NHGRI NIH HHS T32 HG00044NHLBI NIH HHS HV48141NHLBI NIH HHS N01 HV048141NIGMS NIH HHS GM28016NIGMS NIH HHS R01 GM028016
6 · The paper itself

Abstract

Previously, we observed that without using prior information about individual sampling locations, a clustering algorithm applied to multilocus genotypes from worldwide human populations produced genetic clusters largely coincident with major geographic regions. It has been argued, however, that the degree of clustering is diminished by use of samples with greater uniformity in geographic distribution, and that the clusters we identified were a consequence of uneven sampling along genetic clines. Expanding our earlier dataset from 377 to 993 markers, we systematically examine the influence of several study design variables--sample size, number of loci, number of clusters, assumptions about correlations in allele frequencies across populations, and the geographic dispersion of the sample--on the "clusteredness" of individuals. With all other variables held constant, geographic dispersion is seen to have comparatively little effect on the degree of clustering. Examination of the relationship between genetic and geographic distance supports a view in which the clusters arise not as an artifact of the sampling scheme, but from small discontinuous jumps in genetic distance for most population pairs on opposite sides of geographic barriers, in comparison with genetic distance for pairs on the same side. Thus, analysis of the 993-locus dataset corroborates our earlier results: if enough markers are used with a sufficiently large worldwide sample, individuals can be partitioned into genetic clusters that match major geographic subdivisions of the globe, with some individuals from intermediate geographic locations having mixed membership in the clusters that correspond to neighboring regions.

Indexed as

Multigene FamilyAllelesCluster AnalysisGene FrequencyGenetics, PopulationGenome, HumanGenotypeGeographyHumansModels, GeneticModels, StatisticalPopulation Groups

Identifiers

PMID16355252
PMCPMC1310579

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.