Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pgen.1002886
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dc.titleA Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations
dc.contributor.authorWang C.
dc.contributor.authorZöllner S.
dc.contributor.authorRosenberg N.A.
dc.date.accessioned2019-11-06T09:28:54Z
dc.date.available2019-11-06T09:28:54Z
dc.date.issued2012
dc.identifier.citationWang 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
dc.identifier.issn15537390
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/161635
dc.description.abstractMultivariate 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.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20191101
dc.subjectAfrica
dc.subjectarticle
dc.subjectAsia
dc.subjectcontrolled study
dc.subjectEast Asia
dc.subjectEastern Hemisphere
dc.subjectEurope
dc.subjectevolution
dc.subjectgenetic association
dc.subjectgenetic distance
dc.subjectgenetic similarity
dc.subjectgenetic variability
dc.subjectgenotype
dc.subjectgeographic distribution
dc.subjectgeography
dc.subjecthuman
dc.subjectmultidimensional scaling
dc.subjectpopulation genetics
dc.subjectpopulation structure
dc.subjectprincipal component analysis
dc.subjectquality control
dc.subjectquantitative analysis
dc.subjectsingle nucleotide polymorphism
dc.subjectSouth Asia
dc.subjectSub Saharan Africa
dc.subjectgeography
dc.subjecthaplotype
dc.subjecthuman genome
dc.subjectmigration
dc.subjectsingle nucleotide polymorphism
dc.subjectEmigration and Immigration
dc.subjectGenetics, Population
dc.subjectGenome, Human
dc.subjectGeography
dc.subjectHaplotypes
dc.subjectHumans
dc.subjectPolymorphism, Single Nucleotide
dc.subjectPrincipal Component Analysis
dc.typeArticle
dc.contributor.departmentDUKE-NUS MEDICAL SCHOOL
dc.description.doi10.1371/journal.pgen.1002886
dc.description.sourcetitlePLoS Genetics
dc.description.volume8
dc.description.issue8
dc.description.pagee1002886
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