%0 Journal Article %1 wang2012quantitative %A Wang, Chaolong %A Zöllner, Sebastian %A Rosenberg, Noah A. %D 2012 %I Public Library of Science %J PLoS Genet %K PCA human_genome %N 8 %P e1002886 %R 10.1371/journal.pgen.1002886 %T A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations %U http://dx.doi.org/10.1371%2Fjournal.pgen.1002886 %V 8 %X The spatial pattern of human genetic variation provides a basis for investigating the history of human migrations. Statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been used to summarize spatial patterns of genetic variation, typically by placing individuals on a two-dimensional map in such a way that pairwise Euclidean distances between individuals on the map approximately reflect corresponding genetic relationships. Although similarity between these statistical maps of genetic variation and the geographic maps of sampling locations is often observed, it has not been assessed systematically across different parts of the world. In this study, we combine genome-wide SNP data from more than 100 populations worldwide to perform a formal comparison between genes and geography in different regions. By examining a worldwide sample and samples from Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, we find that significant similarity between genes and geography exists in general in different geographic regions and at different geographic levels. Surprisingly, the highest similarity is found in Asia, even though the geographic barrier of the Himalaya Mountains has created a discontinuity on the PCA map of genetic variation.

@article{wang2012quantitative, abstract = {The spatial pattern of human genetic variation provides a basis for investigating the history of human migrations. Statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been used to summarize spatial patterns of genetic variation, typically by placing individuals on a two-dimensional map in such a way that pairwise Euclidean distances between individuals on the map approximately reflect corresponding genetic relationships. Although similarity between these statistical maps of genetic variation and the geographic maps of sampling locations is often observed, it has not been assessed systematically across different parts of the world. In this study, we combine genome-wide SNP data from more than 100 populations worldwide to perform a formal comparison between genes and geography in different regions. By examining a worldwide sample and samples from Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, we find that significant similarity between genes and geography exists in general in different geographic regions and at different geographic levels. Surprisingly, the highest similarity is found in Asia, even though the geographic barrier of the Himalaya Mountains has created a discontinuity on the PCA map of genetic variation.}, added-at = {2012-08-30T05:50:46.000+0200}, author = {Wang, Chaolong and Zöllner, Sebastian and Rosenberg, Noah A.}, biburl = {https://www.bibsonomy.org/bibtex/24cb3946a29ee165b2e84aee9388f0fc9/peter.ralph}, description = {PLoS Genetics: A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations}, doi = {10.1371/journal.pgen.1002886}, interhash = {64d577e5e8240e1de516e3bce04060ac}, intrahash = {4cb3946a29ee165b2e84aee9388f0fc9}, journal = {PLoS Genet}, keywords = {PCA human_genome}, month = {08}, number = 8, pages = {e1002886}, publisher = {Public Library of Science}, timestamp = {2012-08-30T05:50:47.000+0200}, title = {A Quantitative Comparison of the Similarity between Genes and Geography in Worldwide Human Populations}, url = {http://dx.doi.org/10.1371%2Fjournal.pgen.1002886}, volume = 8, year = 2012 }