Evaluating strategies for marker ranking in genome-wide association studies of complex traits.
BACKGROUND
Genome-wide association studies (GWAS) were highly successful in identifying new susceptibility loci of complex traits. Such studies usually start with genotyping fixed arrays of genetic markers in an initial sample. Out of these markers, some are selected which will be further genotyped in independent samples. Due to the very low a priori probability of a true positive association, the vast majority of all marker signals will turn out to be false positive. Thus, several methods to sort marker data have been proposed which will be evaluated here.


OBJECTIVE
We compared statistical properties of ranking by p-values, q-values, the False Positive Report Probability (FPRP) and the Bayesian False-Discovery Probability (BFDP).


METHODS
We performed simulation studies for a genomic region derived from GWAS data sets and calculated descriptive statistics as well as mean square errors with regard to the true marker ranking. Additionally, we applied all measures to a GWAS for early onset extreme obesity superimposing a priori information on candidate genes.


RESULTS
Despite the known, more extreme probability results for traditional p-values, we observed that both p-values and the BFDP were more precise in reconstructing the "true" order of the markers in a region. In addition, the BFDP was useful to attenuate unexpected effects at a genome-wide scale.


CONCLUSIONS
For the purpose of selecting markers from an initial GWAS and within the limits of this study, we recommend either ranking by p-values or the application of a full Bayesian approach for which the BFDP is a first approximation.
Scherag
A
A
André Scherag, Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Hufelandstr. 55, 45122 Essen, Germany. andre.scherag@uk-essen.de
Hebebrand
J
J
Wichmann
H-E
HE
Jöckel
K-H
KH
D004194:Disease / Q000235:genetics; D005260:Female; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D019655:Quantitative Trait, Heritable
D005819:Genetic Markers