Bioinformatics · 2014 · 513 citations · 8 references
Phenome‑wide association studies (PheWAS) have been used to replicate known genetic associations and discover new phenotype associations for genetic variants. The package enables users to translate ICD‑9 codes into case/control groups, analyze phenotypes with covariate adjustments, and plot results. The R package, freely available under GPL‑3, implements ICD‑9 code translation, covariate‑adjusted phenotype analysis, and result plotting, and is demonstrated via a replication of rs3135388 and a novel WBC PheWAS. The package reproduces rs3135388 associations with greater significance, identifies WBC links to infections, myeloproliferative disorders, and anemia, and showcases the improved classification scheme’s performance and PheWAS flexibility. Contact phewas@vanderbilt.edu and supplementary data are available online.
Summary: Phenome-wide association studies (PheWAS) have been used to replicate known genetic associations and discover new phenotype associations for genetic variants. This PheWAS implementation allows users to translate ICD-9 codes to PheWAS case and control groups, perform analyses using these and/or other phenotypes with covariate adjustments and plot the results. We demonstrate the methods by replicating a PheWAS on rs3135388 (near HLA-DRB, associated with multiple sclerosis) and performing a novel PheWAS using an individual’s maximum white blood cell count (WBC) as a continuous measure. Our results for rs3135388 replicate known associations with more significant results than the original study on the same dataset. Our PheWAS of WBC found expected results, including associations with infections, myeloproliferative diseases and associated conditions, such as anemia. These results demonstrate the performance of the improved classification scheme and the flexibility of PheWAS encapsulated in this package. Availability and implementation: This R package is freely available under the Gnu Public License (GPL-3) from http://phewascatalog.org. It is implemented in native R and is platform independent. Contact: phewas@vanderbilt.edu Supplementary information: Supplementary Data are available at Bioinformatics online.
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PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses
Shaun Purcell, Benjamin M. Neale, Katherine EO Todd-Brown et al. · The American Journal of Human Genetics · 2007 · 34.9K citations · Full text
Genome-wide Association Study, Whole-genome Association, Linkage Disequilibrium +12
Joshua C. Denny, Lisa Bastarache, Marylyn D. Ritchie et al. · Nature Biotechnology · 2013 · 1.1K citations · Full text
Genome-wide Association Study, Health Informatics, Genotype-phenotype Association +12