Motivation: Most trait-associated genetic variants identified in genome-wide association studies (GWASs) are located in non-coding regions of the genome and thought to act through their regulatory roles. Results: To account for enriched association signals in DNA regulatory elements, we propose a novel and general gene-based association testing strategy that integrates enhancer-target gene pairs and methylation quantitative trait locus data with GWAS summary results; it aims to both boost statistical power for new discoveries and enhance mechanistic interpretability of any new discovery. By reanalyzing two large-scale schizophrenia GWAS summary datasets, we demonstrate that the proposed method could identify some significant and novel genes (containing no genome-wide significant SNPs nearby) that would have been missed by other competing approaches, including the standard and some integrative gene-based association methods, such as one incorporating enhancer-target gene pairs and one integrating expression quantitative trait loci. Availability and implementation: Software: wuchong.org/egmethyl.html Supplementary information: Supplementary data are available at Bioinformatics online.
Bibliographical noteFunding Information:
This work was supported by the National Institutes of Health grants [R21AG057038, R01HL116720, R01GM113250, R01GM126002 and R01HL105397].
© 2019 The Author(s). Published by Oxford University Press. All rights reserved.