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一种模拟基因数据的分布的新途径

Nature GeneticsVolume:44,Pages:725–731 DOI:doi:10.1038/ng.2285
A model-based approach for analysis of spatial structure in genetic data
Wen-Yun Yang,1, 2 John Novembre,1, 3 Eleazar Eskin1, 2, 4, 8 & Eran Halperin5, 6, 7, 8

Abstract
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.
发表:
http://www.nature.com/ng/journal/v44/n6/abs/ng.2285.html

描述遗传标记的多样性,在研究人类疾病和进化方面有很大的应用。本文创立了一种“空间祖先分析”的方法,可以根据某一个体的SNP的数据,来判断他归属于哪一个大陆或者国家的人。  用这个方法,也再次确认了人类基因组中一些受选择的区域,比如LCT,FOXP2, OCA2 and LRP1B.

注:所研究的对象并不新颖:祖先信息位点, AIM. 但此文创建了一种在二维和三维空间坐标上定位某一个个体的方法。
自问,于民于家何用?
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