Tran Tam C, Schlueter David J, Zeng Chenjie, Mo Huan, Carroll Robert J, Denny Joshua C
National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, United States.
University of Toronto, ON, M5S 1A1, Canada.
Bioinformatics. 2024 Dec 26;41(1). doi: 10.1093/bioinformatics/btae719.
With the rapid growth of genetic data linked to electronic health record (EHR) data in huge cohorts, large-scale phenome-wide association study (PheWAS) have become powerful discovery tools in biomedical research. PheWAS is an analysis method to study phenotype associations utilizing longitudinal EHR data. Previous PheWAS packages were developed mostly with smaller datasets and with earlier PheWAS approaches. PheTK was designed to simplify analysis and efficiently handle biobank-scale data. PheTK uses multithreading and supports a full PheWAS workflow including extraction of data from OMOP databases and Hail matrix tables as well as PheWAS analysis for both phecode version 1.2 and phecodeX. Benchmarking results showed PheTK took 64% less time than the R PheWAS package to complete the same workflow. PheTK can be run locally or on cloud platforms such as the All of Us Researcher Workbench (All of Us) or the UK Biobank (UKB) Research Analysis Platform (RAP).
The PheTK package is freely available on the Python Package Index, on GitHub under GNU General Public License (GPL-3) at https://github.com/nhgritctran/PheTK, and on Zenodo, DOI 10.5281/zenodo.14217954, at https://doi.org/10.5281/zenodo.14217954. PheTK is implemented in Python and platform independent.
随着与大型队列电子健康记录（EHR）数据相关的基因数据迅速增长，大规模表型组全关联研究（PheWAS）已成为生物医学研究中强大的发现工具。PheWAS是一种利用纵向EHR数据研究表型关联的分析方法。以前的PheWAS软件包大多是使用较小的数据集和早期的PheWAS方法开发的。PheTK旨在简化分析并有效处理生物样本库规模的数据。PheTK使用多线程，并支持完整的PheWAS工作流程，包括从OMOP数据库和Hail矩阵表中提取数据，以及对phecode版本1.2和phecodeX进行PheWAS分析。基准测试结果表明，在完成相同工作流程时，PheTK比R PheWAS软件包所需时间少64%。PheTK可以在本地运行，也可以在云平台上运行，如“我们所有人”研究工作台（“我们所有人”）或英国生物样本库（UKB）研究分析平台（RAP）。
PheTK软件包可在Python软件包索引、GitHub上根据GNU通用公共许可证（GPL-3）免费获取，网址为https://github.com/nhgritctran/PheTK，也可在Zenodo上获取，DOI为10.5281/zenodo.14217954，网址为https://doi.org/10.5281/zenodo.14217954。PheTK用Python实现，与平台无关。
