The imputation algorithm overall accuracy for association statistics was compared and comprehensively evaluated under a diverse panel of different genetic conditions [13,3]. Here, it was showed that when allelic frequencies were imputed in markers located in low LD (linkage disequilibrium) regions, the accuracy of association statistics strongly diminishes. This restriction is probably imposed by the limited haplotypic information in these regions and to a not well consolidated haplotypic map. Based on the well known strong dependence between available haplotypic information quality and the accurate imputation of markers located in a specific haplotypic block, we developed an algorithm implementing a sliding window procedure focused in the analysis of association statistics of flanking markers as predictors for imputation quality of derived association statistics. Since the same haplotypic information is used for imputation of nearby markers it is expected that an imputed marker considered associated should be flanked by markers showing at least moderate association to the phenotype under study. Interestingly, imputed markers showing high concordance to empiric ones (for the derived association statistic) presented significantly higher total sum of association statistics as
