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April 14, 2014Bioinformatics533 citationsOpen Access

R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment

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RCRobert J. CarrollLBLisa BastaracheJDJoshua C. Denny

Key Points

  • This research aims to provide tools for conducting phenome-wide association studies efficiently in the R environment.
  • Translated ICD-9 codes to case and control groups for PheWAS.
  • Performed analyses with covariate adjustments on various phenotypes.
  • Demonstrated methods by replicating a PheWAS on genetic variant rs3135388.
  • Replication of rs3135388 showed more significant results than the original study.
  • PheWAS on white blood cell count identified associations with infections and myeloproliferative diseases.
  • Results were consistent with expected associations including anemia.

Abstract

UNLABELLED: 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.

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Cite This Study

Carroll et al. (2014) studied this question.

synapsesocial.com/papers/6a000ee2da5c1eb07f2d982fhttps://doi.org/10.1093/bioinformatics/btu197
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