2023
DOI: 10.1101/2023.10.05.561120
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Large-scale imputation models for multi-ancestry proteome-wide association analysis

Chong Wu,
Zichen Zhang,
Xiaochen Yang
et al.

Abstract: Proteome-wide association studies (PWAS) decode the intricate proteomic landscape of biological mechanisms for complex diseases. Traditional PWAS model training relies heavily on individual-level reference proteomes, thereby restricting its capacity to harness the emerging summary-level protein quantitative trait loci (pQTL) data in the public domain. Here we introduced a novel framework to train PWAS models directly from pQTL summary statistics. By leveraging extensive pQTL data from the UK Biobank, deCODE, a… Show more

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Cited by 4 publications
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