A model-based approach for analysis of spatial structure in genetic data

Wen Yun Yang, John Novembre, Eleazar Eskin*, Eran Halperin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Characterizing genetic diversity within and between populations has broad applications in studies of human disease and evolution. We propose a new approach, spatial ancestry analysis, for the modeling of genotypes in two-or three-dimensional space. In spatial ancestry analysis (SPA), we explicitly model the spatial distribution of each SNP by assigning an allele frequency as a continuous function in geographic space. We show that the explicit modeling of the allele frequency allows individuals to be localized on the map on the basis of their genetic information alone. We apply our SPA method to a European and a worldwide population genetic variation data set and identify SNPs showing large gradients in allele frequency, and we suggest these as candidate regions under selection. These regions include SNPs in the well-characterized LCT region, as well as at loci including FOXP2, OCA2 and LRP1B.

Original languageEnglish
Pages (from-to)725-731
Number of pages7
JournalNature Genetics
Issue number6
StatePublished - Jun 2012


FundersFunder number
National Science Foundation0731455, 0513612, 0729049, 1065276, 0933731, 0916676
National Institutes of HealthPO1 HL28481, K25 HL080079, U01 DA024417
National Heart, Lung, and Blood InstituteP01HL030568
International Business Machines Corporation
Searle Scholars Program
Israel Science Foundation04514831
Tel Aviv University


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