Statistical analysis

The cFDR approach is well-established now, which has been widely applied by many other groups^4,7,8,55,56 and our group^12–14. We briefly summarized this cFDR approach as follows: after the data preparation processing, we computed the conditional empirical cumulative distribution functions (cdfs) of the corrected p-values for the x axis in conditional QQ plot. Empirical cdfs for BMI SNP p-values were conditioned on nominal p-values in T2D, and vice versa. For each nominal p-value, an estimate of the cFDR was obtained from the conditional empirical cdfs. Using this cFDR approach, we obtained two cFDR tables–cFDR result for BMI conditioned on T2D and vice versa. Using these tables we identified loci associated with BMI and T2D (cFDR < 0.05), respectively. Then a conjunction method was used to find SNPs significantly associated with both BMI and T2D. Specifically, we took the maximum of those two cFDR values above as our conjunction FDR.