Journal
GENETIC EPIDEMIOLOGY
Volume 30, Issue 4, Pages 277-289Publisher
WILEY
DOI: 10.1002/gepi.20143
Keywords
genomic control; structured association; non-centrality parameter; false positive rate; admixture
Funding
- NIAAA NIH HHS [R01 AA013654] Funding Source: Medline
- NIDDK NIH HHS [DK-31813, DK31775] Funding Source: Medline
- NINDS NIH HHS [NS27941] Funding Source: Medline
Ask authors/readers for more resources
We present a new method, the delta-centralization (DC) method, to correct for population stratification (PS) in case-control association studies. DC works well even when there is a lot of confounding due to PS. The latter causes overdispersion in the usual chi-square statistics which then have non-central chi-square distributions. Other methods approach the noncentrality indirectly, but we deal with it directly, by estimating the non-centrality parameter tau itself. Specifically: (1) We define a quantity delta, a function of the relevant subpopulation parameters. We show that, for relatively large samples, delta exactly predicts the elevation of the false positive rate due to PS, when there is no true association between marker genotype and disease. (This quantity delta is quite different from Wright's F-ST and can be large even when F-ST is small.) (2) We show how to estimate delta, using a panel of unlinked neutral loci. (3) We then show that delta(2) corresponds to tau the noncentrality parameter of the chi-square distribution. Thus, we can centralize the chi-square using our estimate of delta; this is the DC method. (4) We demonstrate, via computer simulations, that DC works well with as few as 25-30 unlinked markers, where the markers are chosen to have allele frequencies reasonably close (within +/-.1) to those at the test locus. (5) We compare DC with genomic control and show that where as the latter becomes overconservative when there is considerable confounding due to PS (i.e. when delta is large), DC performs well for all values of delta.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available