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| Широкогеномно асоциативно проучване в образователните изследвания× | Менделеева рандомизация× | |
|---|---|---|
| Област≠ | Биоинформатика | Причинно-следствено заключение |
| Семейство≠ | Process / pipeline | Regression model |
| Година на възникване≠ | 2013 (first large-scale educational attainment GWAS); refined through major studies in 2016, 2018, 2022 | 1997 |
| Създател≠ | Social Science Genetic Association Consortium (SSGAC); Rietveld et al. 2013 pioneered educational attainment GWAS | George Davey Smith |
| Тип≠ | Quantitative genomic association analysis | Genetic instrumental variable framework |
| Основополагащ източник≠ | Okbay, A., Turley, P., Georgios, K., et al. (2022). Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. Nature Genetics, 54(4), 437–449. 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 ↗ |
| Други названия≠ | GWAS in education, educational GWAS, GWAS for cognitive traits, genomic study of educational attainment | MR |
| Свързани≠ | 1 | 2 |
| Резюме≠ | A genome-wide association study (GWAS) applied to educational research scans millions of single-nucleotide polymorphisms (SNPs) across the human genome to identify genetic variants statistically associated with educational outcomes such as years of schooling, degree attainment, or cognitive test scores. Large consortia — most prominently the Social Science Genetic Association Consortium — have conducted landmark studies in hundreds of thousands to millions of individuals, establishing GWAS as the principal genomic tool for understanding the heritable architecture of 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. |
| ScholarGateНабор от данни ↗ |
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