Using ancestry-informative markers to identify fine structure across 15 populations of European origin

The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may hel...

Full description

Bibliographic Details
Authors: Huckins, Laura M.; Boraska, Vesna; Franklin, Christopher S.; Floyd, James A. B.; Southam, Lorraine; GCAN; WTCCC3; Sullivan, Patrick F.; Bulik, Cynthia M.; Collier, David A.; Tyler-Smith, Chris; Zeggini, Eleftheria; Tachmazidou, Ioanna
Format: Article
Status:Published version
Publication date:2014
Country:España
Institution:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repository:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/58798
Online Access:http://hdl.handle.net/10230/58798
http://dx.doi.org/10.1038/ejhg.2014.1
Access Level:Open access
Keyword:Population stratification
AIMs
Principal component analysis
Description
Summary:The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia.