A commonly accepted source of bias is the use of not well consolidated haplotypic information as an input for imputation algorithms. This could lead to imputed allelic frequencies not coherent to the population under study and, consequently strongly biased association tests. To explore this hypothesis we determined haplotypic blocks centered in each marker of the WTCCC dataset that were also present in the HapMap database. The comparison between the observed biases and four different summary statistics, representing haplotypic block consistency, showed a modest success when variance and maximum values were tested as predictors. Interestingly, the comparison between mean and median values of linkage disequilibrium as predictors showed that imputed markers located in regions showing weaker linkage disequilibrium structure are prone to higher bias. Their imputation and subsequent analysis under different genetic models of inheritance should be carefully done especially if the imputed marker is to be considered strongly associated to the phenotype under study. A similar result was suggested by Bakker P. I.W et al, when constructing a guide to the use of imputed information in meta-analysis of genome wide association studies[6].
