Finally, we explored the hypothesis that if a particular marker is truly associated with the investigated phenotype one would expect that close markers (in LD with the tested marker) would also present a higher chance of also being associated. In this scenario, a considerable proportion of markers flanking an associated SNP should also present significant levels of association for the phenotype under investigation. Imputed SNPs located in the same chromosomal region are inferred with similar accuracy since the same haplotypic structure information was used by the imputation algorithm. In the same hand, it is expected that a totally isolated associated marker within a well-known LD block will likely represent a false positive association. To evaluate the validity of this hypothesis, we developed an algorithm implementing a sliding window procedure that determines and collects minus log corrected association statistics of consecutive imputed markers using three different window sizes (1, 2 and 3 flanking markers) (see methods for further discussion). We determined different sliding windows size centered in the 73 imputed markers considered associated for diabetes II, these sliding windows were separated
