On the use of general control samples for genome-wide association studies: genetic matching highlights causal variants.
paper
Cited
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- Authors
- Luca, Diana; Ringquist, Steven; Klei, Lambertus; Lee, Ann B; Gieger, Christian; Wichmann, H-Erich; Schreiber, Stefan; Krawczak, Michael; Lu, Ying; Styche, Alexis; Devlin, Bernie; Roeder, Kathryn; Trucco, Massimo
- Year
- 2008
- Journal
- American journal of human genetics
- PMID
- 18252225
- DOI
- 10.1016/j.ajhg.2007.11.003
- PMCID
- PMC2427172
Resources being amassed for genome-wide association (GWA) studies include "control databases" genotyped with a large-scale SNP array. How to use these databases effectively is an open question. We develop a method to match, by genetic ancestry, controls to affected individuals (cases). The impact of this method, especially for heterogeneous human populations, is to reduce the false-positive rate, inflate other spuriously small p values, and have little impact on the p values associated with true positive loci. Thus, it highlights true positives by downplaying false positives. We perform a GWA by matching Americans with type 1 diabetes (T1D) to controls from Germany. Despite the complex study design, these analyses identify numerous loci known to confer risk for T1D.
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