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使用PheTK对大规模生物样本库数据进行全表型组关联研究分析。

PheWAS analysis on large-scale biobank data with PheTK.

作者信息

Tran Tam C, Schlueter David J, Zeng Chenjie, Mo Huan, Carroll Robert J, Denny Joshua C

出版信息

medRxiv. 2024 Feb 13:2024.02.12.24302720. doi: 10.1101/2024.02.12.24302720.

Abstract

SUMMARY

With the rapid growth of genetic data linked to electronic health record 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 electronic health record (EHR) data. Previous PheWAS packages were developed mostly in the days of smaller biobanks 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 Researcher Workbench ( ) or the UK Biobank (UKB) Research Analysis Platform (RAP).

AVAILABILITY AND IMPLEMENTATION

The PheTK package is freely available on the Python Package Index (PyPi) and on GitHub under GNU Public License (GPL-3) at https://github.com/nhgritctran/PheTK . It is implemented in Python and platform independent. The demonstration workspace for will be made available in the future as a featured workspace.

CONTACT

PheTK@mail.nih.gov.

摘要

摘要

随着与大型队列电子健康记录数据相关的遗传数据快速增长,大规模全表型组关联研究(PheWAS)已成为生物医学研究中强大的发现工具。PheWAS是一种利用纵向电子健康记录(EHR)数据研究表型关联的分析方法。以前的PheWAS软件包大多是在生物样本库规模较小且采用早期PheWAS方法的时期开发的。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语言的PheWAS软件包所需时间少64%。PheTK可以在本地运行,也可以在诸如Researcher Workbench( )或英国生物样本库(UKB)研究分析平台(RAP)等云平台上运行。

可用性与实现

PheTK软件包可在Python软件包索引(PyPi)上免费获取,并在GitHub上根据GNU通用公共许可证(GPL-3)在https://github.com/nhgritctran/PheTK 上获取。它用Python实现,与平台无关。 的演示工作区将在未来作为特色工作区提供。

联系方式

PheTK@mail.nih.gov

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