PWAS: proteome-wide association study—linking genes and phenotypes by functional variation in proteins

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作者
Nadav Brandes
Nathan Linial
Michal Linial
机构
[1] The Hebrew University of Jerusalem,School of Computer Science and Engineering
[2] The Hebrew University of Jerusalem,Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences
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GWAS; Machine learning; Protein function; Protein annotations; UK Biobank; Recessive heritability;
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摘要
We introduce Proteome-Wide Association Study (PWAS), a new method for detecting gene-phenotype associations mediated by protein function alterations. PWAS aggregates the signal of all variants jointly affecting a protein-coding gene and assesses their overall impact on the protein’s function using machine learning and probabilistic models. Subsequently, it tests whether the gene exhibits functional variability between individuals that correlates with the phenotype of interest. PWAS can capture complex modes of heritability, including recessive inheritance. A comparison with GWAS and other existing methods proves its capacity to recover causal protein-coding genes and highlight new associations. PWAS is available as a command-line tool.
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