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.
Understanding the genetics of systemic lupus erythematosus using Bayesian statistics and gene network analysis.
利用贝叶斯统计和基因网络分析了解系统性红斑狼疮的遗传学。
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| 期刊: | Clinical and Experimental Pediatrics | 影响因子: | 3.600 |
| 时间: | 2021 | 起止号: | 2021 May;64(5):208-222 |
| doi: | 10.3345/cep.2020.00633 | ||
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