RT Journal Article SR Electronic T1 Estimating inflation in GWAS summary statistics due to variance distortion from cryptic relatedness JF bioRxiv FD Cold Spring Harbor Laboratory SP 164939 DO 10.1101/164939 A1 Dominic Holland A1 Chun-Chieh Fan A1 Oleksandr Frei A1 Alexey A. Shadrin A1 Olav B. Smeland A1 V. S. Sundar A1 Ole A. Andreassen A1 Anders M. Dale YR 2017 UL http://biorxiv.org/content/early/2017/07/17/164939.abstract AB Cryptic relatedness is inherently a feature of large genome-wide association studies (GWAS), and can give rise to considerable inflation in summary statistics through variance distortion. It has proven difficult to disentangle these inflationary effects from true polygenic effects. Uncorrected inflation will alter the estimates of the number of causal loci associated with the phenotype and the strength of their association. Here we present results of a model that enables estimation of polygenicity, strength of association (or discoverability), and residual inflation in GWAS summary statistics. We show that there is residual inflation (“true” genomic control) of and for recent large GWAS of height and schizophrenia, respectively. In contrast, a larger GWAS for educational attainment shows no residual inflation. Additionally, we find that height has a relatively low polygenicity, with approximately 8k SNPs having causal association, more than an order of magnitude less than has been reported. Residual inflation in GWAS summary statistics can be detected and then corrected using the genomic control procedure with in place of the traditional genomic control factor.