Nam Seoung Wan, Lee Kwang Seob, Yang Jae Won, Ko Younhee, Eisenhut Michael, Lee Keum Hwa, Shin Jae Il, Kronbichler Andreas
Department of Rheumatology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea.
Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
Clin Exp Pediatr. 2021 May;64(5):208-222. doi: 10.3345/cep.2020.00633. Epub 2020 Jul 15.
The publication of genetic epidemiology meta-analyses has increased rapidly, but it has been suggested that many of the statistically significant results are false positive. In addition, most such meta-analyses have been redundant, duplicate, and erroneous, leading to research waste. In addition, since most claimed candidate gene associations were false-positives, correctly interpreting the published results is important. In this review, we emphasize the importance of interpreting the results of genetic epidemiology meta-analyses using Bayesian statistics and gene network analysis, which could be applied in other diseases.
遗传流行病学荟萃分析的发表数量迅速增加,但有人认为许多具有统计学意义的结果是假阳性。此外,大多数此类荟萃分析都存在冗余、重复和错误的情况,导致研究资源浪费。此外,由于大多数声称的候选基因关联都是假阳性,因此正确解读已发表的结果很重要。在本综述中,我们强调使用贝叶斯统计和基因网络分析来解读遗传流行病学荟萃分析结果的重要性,这些方法也可应用于其他疾病。