{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T18:38:38Z","timestamp":1776105518285,"version":"3.50.1"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"16","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,8,15]]},"abstract":"<jats:p>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\u2019s 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.<\/jats:p>\n               <jats:p>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.<\/jats:p>\n               <jats:p>Contact: \u00a0phewas@vanderbilt.edu<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary Data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu197","type":"journal-article","created":{"date-parts":[[2014,4,15]],"date-time":"2014-04-15T01:46:51Z","timestamp":1397526411000},"page":"2375-2376","source":"Crossref","is-referenced-by-count":472,"title":["R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment"],"prefix":"10.1093","volume":"30","author":[{"given":"Robert J.","family":"Carroll","sequence":"first","affiliation":[{"name":"1 \u00a01Department of Biomedical Informatics and 2Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37212, USA"}]},{"given":"Lisa","family":"Bastarache","sequence":"additional","affiliation":[{"name":"1 \u00a01Department of Biomedical Informatics and 2Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37212, USA"}]},{"given":"Joshua C.","family":"Denny","sequence":"additional","affiliation":[{"name":"1 \u00a01Department of Biomedical Informatics and 2Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37212, USA"}]}],"member":"286","published-online":{"date-parts":[[2014,4,14]]},"reference":[{"key":"2023012711523270400_btu197-B1","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1038\/ng.401","article-title":"Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci","volume":"41","author":"De Jager","year":"2009","journal-title":"Nat. Genet."},{"key":"2023012711523270400_btu197-B2","doi-asserted-by":"crossref","first-page":"1205","DOI":"10.1093\/bioinformatics\/btq126","article-title":"PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene\u2013disease associations","volume":"26","author":"Denny","year":"2010","journal-title":"Bioinformatics"},{"key":"2023012711523270400_btu197-B3","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1016\/j.ajhg.2011.09.008","article-title":"Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome- and phenome-wide studies","volume":"89","author":"Denny","year":"2011","journal-title":"Am. J. Hum. Genet."},{"key":"2023012711523270400_btu197-B4","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1038\/nbt.2749","article-title":"Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data","volume":"31","author":"Denny","year":"2013","journal-title":"Nat. Biotechnol."},{"key":"2023012711523270400_btu197-B5","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1038\/ng2088","article-title":"A new multipoint method for genome-wide association studies by imputation of genotypes","volume":"39","author":"Marchini","year":"2007","journal-title":"Nat. Genet."},{"key":"2023012711523270400_btu197-B6","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/1756-0381-5-5","article-title":"Visually integrating and exploring high throughput phenome-wide association study (PheWAS) results using PheWAS-view","volume":"5","author":"Pendergrass","year":"2012","journal-title":"BioData Min."},{"key":"2023012711523270400_btu197-B7","doi-asserted-by":"crossref","first-page":"e1003087","DOI":"10.1371\/journal.pgen.1003087","article-title":"Phenome-wide association study (PheWAS) for detection of pleiotropy within the population architecture using genomics and epidemiology (PAGE) network","volume":"9","author":"Pendergrass","year":"2013","journal-title":"PLoS Genet."},{"key":"2023012711523270400_btu197-B8","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1086\/519795","article-title":"PLINK: a tool set for whole-genome association and population-based linkage analyses","volume":"81","author":"Purcell","year":"2007","journal-title":"Am. J. Hum. Genet."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/30\/16\/2375\/48926020\/bioinformatics_30_16_2375.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/30\/16\/2375\/48926020\/bioinformatics_30_16_2375.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,27]],"date-time":"2023-01-27T12:12:18Z","timestamp":1674821538000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/30\/16\/2375\/2748157"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,4,14]]},"references-count":8,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2014,8,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btu197","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,4,14]]}}}