TY  - JOUR
AU  - Naylor, Melissa G
AU  - Weiss, Scott T
AU  - Lange, Christoph
TI  - A Bayesian approach to genetic association studies with family-based designs.
JO  - Genetic epidemiology
VL  - 34
IS  - 6
SN  - 0741-0395
CY  - New York, NY
PB  - Wiley-Liss
M1  - DZNE-2020-02433
SP  - 569-574
PY  - 2010
AB  - For genome-wide association studies with family-based designs, we propose a Bayesian approach. We show that standard transmission disequilibrium test and family-based association test statistics can naturally be implemented in a Bayesian framework, allowing flexible specification of the likelihood and prior odds. We construct a Bayes factor conditional on the offspring phenotype and parental genotype data and then use the data we conditioned on to inform the prior odds for each marker. In the construction of the prior odds, the evidence for association for each single marker is obtained at the population-level by estimating its genetic effect size by fitting the conditional mean model. Since such genetic effect size estimates are statistically independent of the effect size estimation within the families, the actual data set can inform the construction of the prior odds without any statistical penalty. In contrast to Bayesian approaches that have recently been proposed for genome-wide association studies, our approach does not require assumptions about the genetic effect size; this makes the proposed method entirely data-driven. The power of the approach was assessed through simulation. We then applied the approach to a genome-wide association scan to search for associations between single nucleotide polymorphisms and body mass index in the Childhood Asthma Management Program data.
KW  - Asthma: genetics
KW  - Bayes Theorem
KW  - Body Mass Index
KW  - Child
KW  - Genome-Wide Association Study: methods
KW  - Genotype
KW  - Humans
KW  - Linkage Disequilibrium
KW  - Models, Genetic
KW  - Models, Statistical
KW  - Phenotype
KW  - Polymorphism, Single Nucleotide
LB  - PUB:(DE-HGF)16
C6  - pmid:20818722
C2  - pmc:PMC3349938
DO  - DOI:10.1002/gepi.20513
UR  - https://pub.dzne.de/record/136111
ER  -