Journal
NATURE GENETICS
Volume 44, Issue 6, Pages 725-U163Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/ng.2285
Keywords
-
Categories
Funding
- US National Science Foundation [0513612, 0731455, 0729049, 0916676, 1065276]
- US National Institutes of Health [K25 HL080079, U01 DA024417, P01 HL30568, PO1 HL28481]
- National Science Foundation [0933731]
- Searle Scholars Program
- Israeli Science Foundation [04514831]
- IBM
- Direct For Biological Sciences [0933731] Funding Source: National Science Foundation
- Direct For Computer & Info Scie & Enginr [0729049] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations [0729049] Funding Source: National Science Foundation
- Div Of Biological Infrastructure [0933731] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [0916676] Funding Source: National Science Foundation
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available