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| 교육 연구에서의 베이지안 후성유전체 전장 연관성 분석× | 멘델 무작위 배정× | |
|---|---|---|
| 분야≠ | 생물정보학 | 인과추론 |
| 계열≠ | Process / pipeline | Regression model |
| 기원 연도≠ | EWAS framework ~2010–2011; Bayesian EWAS variants ~2013–2017; educational applications ~2015–present | 1997 |
| 창시자≠ | Rakyan, Down, Balding, and Beck (conceptual EWAS framework); Bayesian extensions by multiple groups including Teschendorff and colleagues | George Davey Smith |
| 유형≠ | Genomic association study with Bayesian inference | Genetic instrumental variable framework |
| 원전≠ | Rakyan, V. K., Down, T. A., Balding, D. J., & Beck, S. (2011). Epigenome-wide association studies for common human diseases. Nature Reviews Genetics, 12(8), 529–541. link ↗ | Davey Smith, G., & Hemani, G. (2014). Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Human Molecular Genetics, 23(R1), R89-R98. DOI ↗ |
| 별칭≠ | Bayesian EWAS, Bayesian epigenome-wide scan, Bayesian methylation-wide association study, B-EWAS | MR |
| 관련≠ | 3 | 2 |
| 요약≠ | A Bayesian epigenome-wide association study (Bayesian EWAS) scans hundreds of thousands of DNA methylation sites across the genome to identify those statistically associated with an educational outcome — such as cognitive ability, attainment, or socioeconomic exposure during schooling. Unlike classical frequentist EWAS, the Bayesian framework incorporates prior biological knowledge to compute posterior probabilities of association, improving power and reducing false discoveries when applied to complex educational phenotypes. | Mendelian randomization is a method for estimating causal effects of exposures on outcomes using genetic variants as instrumental variables. Introduced by George Davey Smith in the 1990s, it exploits Mendel's law of segregation to remove confounding bias. It has become a cornerstone technique in epidemiological causal inference. |
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