We investigated whether similar results could be achieved with real data by analyzing whole exome sequencing data from 909 individuals of European ancestry, combining samples from the International HIV Controllers Study (IHCS) (84), Swedish Schizophrenia Study (SCZ) (503) and Autism NIHM Controls Study (AUT) (322) (Online Methods)14–18. Whole-exome studies enrich the sample DNA for genic content prior to sequencing3,19,20 and usually discard data from non-exonic regions. However, current DNA capture technologies do not yield perfect enrichment and the “off-target” data can often be substantial given the high coverage of many exome-sequencing studies. For example, in the 909 exomes, the average coverage is 0.24x for non-exonic regions and more than 60x for exons (Supplementary Note, Supplementary Figure 2). We explored whether the whole-exome data, coupled with imputation based on the 1000 Genomes Project reference dataset, could support a GWAS. We imputed genotypes at all polymorphic sites indentified in the European samples of the 1000 Genomes Project, using sequencing data together with the 762 haplotypes inferred from the European samples of the 1000 Genomes Project phase 1 (Online Methods), and quantified accuracy
