Evidence map›Paper›PMID 22927824›Full record

ArticlePLoS genetics2012

A quantitative comparison of the similarity between genes and geography in worldwide human populations.

Chaolong Wang, Sebastian Zöllner, Noah A Rosenberg

Abstract read
In one paragraph

Article in PLoS genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing 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

53 citing papers in PubMed.

  1. Article
  2. Quantifying direct genetic signal captured by principal component adjustment.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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  8. Evolutionary Influences on Local Patterns of Genetic Relatedness.bioRxiv : the preprint server for biology · 2025
    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

3 authors.

Chaolong WangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA. chaolong@umich.edu
Sebastian Zöllner
Noah A Rosenberg

Funding

Population genetics for large-scale sequencing studies of diverse populationsR01HG005855 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Noah Rosenberg, Paul A Scheet · 2010 to 2026
$5.8M
Population-Genetic Studies for Association MappingR01GM081441 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROSENBERG, NOAH · 2007 to 2011
$1.7M
Howard Hughes Medical InstituteNHGRI NIH HHS R01 HG005855NIGMS NIH HHS R01 GM081441
6 · The paper itself

Abstract

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure.

Indexed as

Genetics, PopulationGenome, HumanPolymorphism, Single NucleotideEmigration and ImmigrationGeographyHaplotypesHumansPrincipal Component Analysis

Identifiers

PMID22927824
PMCPMC3426559

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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.