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.
Bibliographical noteFunding Information:
Acknowledgments This study was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1A1B03032457) and Hankuk University of Foreign Studies Research Fund.
© 2021 by The Korean Pediatric Society.
All Science Journal Classification (ASJC) codes
- Pediatrics, Perinatology, and Child Health