Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pgen.1002886
Title: A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations
Authors: Wang C. 
Zöllner S.
Rosenberg N.A.
Keywords: Africa
article
Asia
controlled study
East Asia
Eastern Hemisphere
Europe
evolution
genetic association
genetic distance
genetic similarity
genetic variability
genotype
geographic distribution
geography
human
multidimensional scaling
population genetics
population structure
principal component analysis
quality control
quantitative analysis
single nucleotide polymorphism
South Asia
Sub Saharan Africa
geography
haplotype
human genome
migration
single nucleotide polymorphism
Emigration and Immigration
Genetics, Population
Genome, Human
Geography
Haplotypes
Humans
Polymorphism, Single Nucleotide
Principal Component Analysis
Issue Date: 2012
Citation: Wang C., Zöllner S., Rosenberg N.A. (2012). A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations. PLoS Genetics 8 (8) : e1002886. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pgen.1002886
Rights: Attribution 4.0 International
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. © 2012 Wang et al.
Source Title: PLoS Genetics
URI: https://scholarbank.nus.edu.sg/handle/10635/161635
ISSN: 15537390
DOI: 10.1371/journal.pgen.1002886
Rights: Attribution 4.0 International
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