Statistical models for haplotype sharing in case-parent trio data.
BACKGROUND
Haplotype sharing statistics have been introduced in an ad-hoc way, often relying heavily on permutation testing. As a result, applying these approaches to whole genome association studies or to evaluate their properties in extensive simulation experiments is problematic. Further, permutation testing may be inappropriate in the presence of phase ambiguity and population stratification.


OBJECTIVE
To present a simple framework for a class of haplotype sharing statistics useful for association mapping in case-parent trio data. This framework allows derivation of novel haplotype sharing tests as well as simple variance estimators and asymptotic distributions for haplotype sharing tests.


CONCLUSIONS
We validated that our approach is appropriately sized using simulated data, and illustrate the methodology by analyzing a Crohn's disease dataset. We find that haplotype-based analyses are much more powerful than single-locus analyses for these data.
Allen
Andrew S
AS
Department of Bioinformatics and Biostatistics, Duke University, North Carolina, USA.
Satten
Glen A
GA
D003424:Crohn Disease / Q000235:genetics*; D005260:Female; D020022:Genetic Predisposition to Disease; D006239:Haplotypes; D006801:Humans; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D010290:Parents; D020641:Polymorphism, Single Nucleotide