School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
Genome Biol. 2020 Jul 14;21(1):173. doi: 10.1186/s13059-020-02089-x.
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.
我们介绍了蛋白质组关联研究（PWAS），这是一种用于检测由蛋白质功能改变介导的基因-表型关联的新方法。PWAS 聚合了所有共同影响一个蛋白质编码基因的变异的信号，并使用机器学习和概率模型来评估它们对蛋白质功能的整体影响。随后，它测试该基因在个体之间是否表现出与感兴趣的表型相关的功能变异性。PWAS 可以捕捉复杂的遗传模式，包括隐性遗传。与 GWAS 和其他现有方法的比较证明了它能够恢复因果蛋白质编码基因，并突出新的关联。PWAS 可作为命令行工具使用。
