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    PheTK is a new Python package that simplifies phenome-wide association studies (PheWAS) using electronic health records. It efficiently analyzes large biobank datasets, outperforming existing tools.

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    Area of Science:

    • Biomedical Informatics
    • Genomics
    • Computational Biology

    Background:

    • Large-scale genetic and electronic health record (EHR) data enable powerful phenome-wide association studies (PheWAS).
    • Existing PheWAS tools were developed for smaller datasets and may not scale efficiently.
    • There is a need for optimized tools to handle growing biobank-scale data.

    Approach:

    • Introduced PheTK, a Python package designed for efficient and simplified PheWAS.
    • PheTK supports a full PheWAS workflow, including data extraction from OMOP and Hail formats.
    • The package incorporates multithreading for enhanced performance and supports phecode versions 1.2 and phecodeX.

    Key Points:

    • PheTK demonstrated a 64% reduction in workflow completion time compared to the R PheWAS package.
    • The tool is platform-independent and can be run locally or on cloud platforms like the All of Us Researcher Workbench and UK Biobank RAP.
    • PheTK is freely available on PyPi and GitHub under GPL-3.

    Conclusions:

    • PheTK offers a significant improvement in efficiency for large-scale PheWAS.
    • The package facilitates broader adoption of PheWAS in biomedical research by simplifying analysis.
    • Its scalability and accessibility support advanced genetic and health data research.