Haplotype uncertainty in association studies

Inferring haplotypes from genotype data is commonly undertaken in population genetic association studies. Within such studies the importance of accounting for uncertainty in the inference of haplotypes is well recognised. We investigate the effectiveness of correcting for uncertainty using simple methods based on the output provided by the PHASE haplotype inference methodology. In case-control analyses investigating non-Hodgkin lymphoma and haplotypes associated with immune regulation we find little effect of making adjustment for uncertainty in inferred haplotypes. Using simulation we introduce a higher degree of haplotype uncertainty than was present in our study data. The simulation represents two genetic loci, physically close on a chromosome, forming haplotypes. Considering a range of allele frequencies, degrees of linkage between the loci, and frequency of missing genotype data, we detail the characteristics of genetic regions which may be susceptible to the influence of haplotype uncertainty. Within our evaluation we find that bias is avoided by considering haplotype probabilities or using multiple imputation, provided that for each of these methods haplotypes are inferred separately for case and control populations; furthermore using multiple imputation provides the facility to incorporate haplotype uncertainty in the estimation of confidence intervals. We discuss the implications of our findings within the context of the complexity of haplotype inference for larger marker rich regions as would typically be encountered in genetic analyses.