Maurano et al. [10] use enrichment of SNPs passing P-value thresholds of increasing stringency to identify important cell types. Using this method, Maurano et al. found striking patterns of cell-type-specific enrichment. However, this approach implicitly assumes that the functional annotation at a GWAS SNP matches the functional annotation at the causal SNP, which could be true for functional annotations composed of very wide regions, but is not likely to be true for functional annotations composed of smaller regions, such as conserved regions. Moreover, the method does not account for total LD, and so could give biased results if used to compare functional annotations with different average amounts of total LD [1]. We implemented a “top SNPs” method analogous to the method of Maurano et al. that tests for enrichment of the functional category among SNPs that pass statistical significance. Because the method is not intended to control for any other annotations, it had a high rejection rate for the null baseline simulations, detecting cell-type-specific signal where there was none. Thus, its high rejection rate for the cell-type-specific simulations were not
