Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, South Korea.
Interdisciplinary Program for Bioinformatics, College of Natural Science, Seoul National University, Seoul, South Korea.
Genet Epidemiol. 2019 Dec;43(8):1046-1055. doi: 10.1002/gepi.22250. Epub 2019 Aug 20.
Proportions of false-positive rates in genome-wide association analysis are affected by population stratification, and if it is not correctly adjusted, the statistical analysis can produce the large false-negative finding. Therefore various approaches have been proposed to adjust such problems in genome-wide association studies. However, in spite of its importance, a few studies have been conducted in genome-wide single nucleotide polymorphism (SNP)-by-environment interaction studies. In this report, we illustrate in which scenarios can lead to the false-positive rates in association mapping and approach to maintaining the overall type-1 error rate.
全基因组关联分析中的假阳性率受到群体分层的影响，如果不进行正确调整，统计分析可能会产生大量的假阴性结果。因此，已经提出了各种方法来调整全基因组关联研究中的这些问题。然而，尽管其重要性，在全基因组单核苷酸多态性（SNP）与环境相互作用研究中，很少有研究进行。在本报告中，我们说明了哪些情况下会导致关联映射中的假阳性率，并提出了保持总体Ⅰ型错误率的方法。
