Transferability of tag SNPs in genetic association studies in multiple populations View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2006-10-22

AUTHORS

Paul I W de Bakker, Noël P Burtt, Robert R Graham, Candace Guiducci, Roman Yelensky, Jared A Drake, Todd Bersaglieri, Kathryn L Penney, Johannah Butler, Stanton Young, Robert C Onofrio, Helen N Lyon, Daniel O Stram, Christopher A Haiman, Matthew L Freedman, Xiaofeng Zhu, Richard Cooper, Leif Groop, Laurence N Kolonel, Brian E Henderson, Mark J Daly, Joel N Hirschhorn, David Altshuler

ABSTRACT

A general question for linkage disequilibrium–based association studies is how power to detect an association is compromised when tag SNPs are chosen from data in one population sample and then deployed in another sample. Specifically, it is important to know how well tags picked from the HapMap DNA samples capture the variation in other samples. To address this, we collected dense data uniformly across the four HapMap population samples and eleven other population samples. We picked tag SNPs using genotype data we collected in the HapMap samples and then evaluated the effective coverage of these tags in comparison to the entire set of common variants observed in the other samples. We simulated case-control association studies in the non-HapMap samples under a disease model of modest risk, and we observed little loss in power. These results demonstrate that the HapMap DNA samples can be used to select tags for genome-wide association studies in many samples around the world. More... »

PAGES

1298-1303

Journal

TITLE

Nature Genetics

ISSUE

11

VOLUME

38

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ng1899

DOI

http://dx.doi.org/10.1038/ng1899

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020115583

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17057720


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