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Leveraging <i>cis-</i> and <i>trans-</i> variants to improve protein expression level prediction for proteome-wide association studies

2026-05-28

Abstract excerpt

Since genetic effects are often mediated through proteins, the analysis of proteomic data can provide insights into disease etiology. However, most studies lack proteomic data. To address this problem, we developed TransCisPredict to perform proteome-wide association studies (PWAS) at a biobank scale. TransCisPredict reduces computational burden through linkage-disequilibrium block selection which facilitates inco...

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Literature Corpus work
99a7afd0-6d0f-5f6c-a003-c7c49360a331
DOI
10.64898/2026.05.28.728201
Open publication

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Leveraging <i>cis-</i> and <i>trans-</i> variants to improve protein expression level prediction for proteome-wide association studiesDOI 10.64898/2026.05.28.728201
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