Although the ability to impute rare variants accurately from the 1000 Genomes resource is currently limited, the completeness of the resource nevertheless increases power to detect association signals. To demonstrate the utility of imputation in disease samples, we imputed into an eQTL study of ~400 children of European ancestry30 using the low coverage pilot data and HapMap II as reference panels. By comparison to directly genotyped sites we estimated that the effective sample size at variants imputed from the pilot CEU low coverage data set is 91% of the true sample size for variants with allele frequencies above 10%, 76% in the allele frequency range 4-6%, and 54% in the range 1-2%. Imputing over 6 million variants from the low coverage project data increased the number of detected cis-eQTLs by ~16%, compared to a 9% increase with imputing from HapMap II (FDR 5%, signal within 50 kb of transcript; for an example see Fig. 4b).
