DeepPheWAS: an R package for phenotype generation and association analysis for phenome-wide association studies.

Richard J. Packer; Alex Williams; William Hennah; Micaela Eisenberg; Nick R. G. Shrine; Katherine A. Fawcett; Willow Pearson; Anna L. Guyatt; Ahmed Edris; Edward J. Hollox; Mikko Marttila; Balasubramanya Seetharama Rao; John Raymond Bratty; Louise V. Wain; Frank Dudbridge; Martin D. Tobin

doi:10.1093/bioinformatics/btad073

Genetic & Genomic MedicineBioinformaticsFeb 4, 2023

Peer-reviewed journal article

DeepPheWAS: an R package for phenotype generation and association analysis for phenome-wide association studies.

Richard J. Packer iD, Alex Williams, William Hennah iD, Micaela Eisenberg iD, Nick R. G. Shrine iD, Katherine A. Fawcett iD, Willow Pearson iD, Anna L. Guyatt iD, Ahmed Edris iD, Edward J. Hollox iD, Mikko Marttila, Balasubramanya Seetharama Rao, John Raymond Bratty, Louise V. Wain iD, Frank Dudbridge iD, Martin D. Tobin iD

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Abstract

SummaryDeepPheWAS is an R package for phenome wide association studies that creates clinically-curated composite phenotypes, and integrates quantitative phenotypes from primary care data, longitudinal trajectories of quantitative measures, disease progression, and drug response phenotypes. Tools are provided for efficient analysis of association with any genetic input, under any genetic model, with optional sex-stratified analysis, and for developing novel phenotypes. Availability and ImplementationThe DeepPheWAS R package is freely available under GNU general public licence v3.0 from at https://github.com/Richard-Packer/DeepPheWAS. Contactrichard.packer@leicester.ac.uk Supplementary informationSupplementary methods and results are available at Bioinformatics online.