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On the use of general control samples for genome-wide association studies: genetic matching highlights causal variants.

ABSTRACT: 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.

SUBMITTER: Luca D 

PROVIDER: S-EPMC2427172 | biostudies-literature | 2008 Feb

REPOSITORIES: biostudies-literature

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On the use of general control samples for genome-wide association studies: genetic matching highlights causal variants.

Luca Diana D   Ringquist Steven S   Klei Lambertus L   Lee Ann B AB   Gieger Christian C   Wichmann H-Erich HE   Schreiber Stefan S   Krawczak Michael M   Lu Ying Y   Styche Alexis A   Devlin Bernie B   Roeder Kathryn K   Trucco Massimo M  

American journal of human genetics 20080124 2

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  ...[more]

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