PheWAS-ME

PheWAS-ME analyzes multimorbidity patterns in phenome-wide association studies by integrating individual-level genotype data from DNA biobanks with clinical phenotypes extracted from electronic health records to characterize multivariate gene–disease associations.


Key Features:

  • Data integration: Integrates individual-level genotype data from DNA biobanks with clinical phenotypes derived from electronic health records (EHRs).
  • Multimorbidity analysis: Detects and interrogates complex multivariate gene–disease associations that arise from comorbidities within PheWAS results.
  • Custom data input: Accepts custom PheWAS result files and corresponding individual-level genotype and phenotype datasets for tailored analyses.
  • Individual-level association analysis: Performs analysis of gene–phenotype associations at the individual level to reveal patterns that influence PheWAS interpretation.

Scientific Applications:

  • Precision medicine research: Elucidates how genetic variants associate with multiple clinical phenotypes to inform precision medicine studies.
  • Multimorbidity and comorbidity research: Enables investigation of the genetic underpinnings and interactions of comorbid diseases.
  • PheWAS result interpretation: Improves interpretability of PheWAS by identifying multivariate association patterns beyond single-phenotype analyses.

Methodology:

Integrates individual-level genotype data with clinical phenotypes recorded in EHRs to explore associations between genetic variants and multiple phenotypes and to highlight multimorbidity patterns.

Topics

Details

Programming Languages:
R
Added:
1/18/2021
Last Updated:
1/23/2021

Operations

Publications

Strayer N, Shirey-Rice JK, Shyr Y, Denny JC, Pulley JM, Xu Y. PheWAS-ME: a web-app for interactive exploration of multimorbidity patterns in PheWAS. Bioinformatics. 2020;37(12):1778-1780. doi:10.1093/bioinformatics/btaa870. PMID:33051675. PMCID:PMC8487628.

PMID: 33051675
Funding: - National Institutes of Health’s National Center for Advancing Translational Sciences: TR002243

Links