The finding that marker-specific inflation factors vary substantially across the genome has notable implications for meta-analyses and multistage analyses. Such studies typically combine the test statistics after correcting for potential inflation using genomic control30,31,38. The disadvantages of using the same global correction rather than a marker-specific one can become more serious when this step is done repeatedly. To better understand these effects in the context of meta-analysis, we first compared the marker-specific inflation factors between the two WTCCC control groups, collected from essentially the same population. We observed a very strong correlation (r = 0.95; Supplementary Fig. 5a). We further compared the inflation factors across different populations and different genotyping platforms using the NFBC66 samples and WTCCC control samples. We observed a strong correlation of r = 0.70 (Supplementary Fig. 5b), suggesting that the marker-specific inflation factors can be correlated across the multiple data sets used in meta-analysis or multistage analysis owing to the shared genetic history. If this is the case, the standard approach that corrects with genomic control before merging the P values from different studies may lead
