Colocalization analyses assess whether two traits are affected by the same or distinct causal genetic variants in a single gene region. A class of Bayesian colocalization tests are now routinely used in practice; for example, for genetic analyses in drug development pipelines. In this work, we consider an alternative frequentist approach to colocalization testing that examines the proportionality of genetic associations with each trait. The proportional colocalization approach uses markedly different assumptions to Bayesian colocalization tests, and therefore can provide valuable complementary evidence in cases where Bayesian colocalization results are inconclusive or sensitive to priors. We propose a novel conditional test of proportional colocalization, prop-coloc-cond, that aims to account for the uncertainty in variant selection, in order to recover accurate type I error control. The test can be implemented straightforwardly, requiring only summary data on genetic associations. Simulation evidence and an empirical investigation into GLP1R gene expression demonstrates how tests of proportional colocalization can offer important insights in conjunction with Bayesian colocalization tests.

翻译：共定位分析评估两个性状是否受同一基因区域内的相同或不同因果遗传变异影响。一类贝叶斯共定位检验现已在实践中常规使用，例如在药物研发管线的遗传分析中。本研究考虑了一种替代性的频率学派共定位检验方法，该方法考察遗传关联与每个性状的比例性。比例共定位方法使用的假设与贝叶斯共定位检验显著不同，因此在贝叶斯共定位结果不确定或对先验敏感的情况下，可提供有价值的补充证据。我们提出了一种新颖的比例共定位条件检验（prop-coloc-cond），旨在考虑变异选择中的不确定性，以恢复准确的I类错误控制。该检验可简便实施，仅需遗传关联的汇总数据。模拟证据及对GLP1R基因表达的经验调查表明，比例共定位检验可与贝叶斯共定位检验相结合提供重要见解。