PYPE: A pipeline for phenome-wide association and Mendelian randomization in investigator-driven biobank scale analysis

被引:0
|
作者
Dalal, Taykhoom [1 ]
Patel, Chirag J. [1 ]
机构
[1] Harvard Med Sch, Dept Biomed Informat, Boston, MA 02115 USA
来源
PATTERNS | 2024年 / 5卷 / 06期
关键词
genome-wide association studies; Mendelian randomization; phenome-wide association studies; !text type='python']python[!/text;
D O I
10.1016/j.patter.2024.100982
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Phenome-wide association studies (PheWASs) serve as a way of documenting the relationship between genotypes and multiple phenotypes, helping to uncover unexplored genotype -phenotype associations (known as pleiotropy). Secondly, Mendelian randomization (MR) can be harnessed to make causal statements about a pair of phenotypes by comparing their genetic architecture. Thus, approaches that automate both PheWASs and MR can enhance biobank-scale analyses, circumventing the need for multiple tools by providing a comprehensive, end -to -end tool to drive scientific discovery. To this end, we present PYPE, a Python pipeline for running, visualizing, and interpreting PheWASs. PYPE utilizes input genotype or phenotype files to automatically estimate associations between the chosen independent variables and phenotypes. PYPE can also produce a variety of visualizations and can be used to identify nearby genes and functional consequences of significant associations. Finally, PYPE can identify possible causal relationships between phenotypes using MR under a variety of causal effect modeling scenarios.
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页数:7
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