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| GCTA× | 多基因风险评分× | |
|---|---|---|
| 领域 | 遗传学 | 遗传学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2011 | 2007 |
| 提出者≠ | Jian Yang & Peter Visscher | Shaun Purcell & Nicholas Wray |
| 类型≠ | Computational analysis tool | Predictive genomic method |
| 开创性文献≠ | Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011). GCTA: A tool for genome-wide complex trait analysis. American Journal of Human Genetics, 88(1), 76–82. DOI ↗ | Purcell, S. M., Wray, N. R., Stone, J. L., Visscher, P. M., O'Donovan, M. C., Sullivan, P. F., & Sklar, P. (2007). Common polygenic variation contributes to risk of schizophrenia. Nature, 460(7256), 748–752. link ↗ |
| 别名 | GREML, Genome-wide complex trait analysis, Heritability estimation | PRS, Polygenic score, Genomic risk score |
| 相关 | 4 | 4 |
| 摘要≠ | GCTA (Genome-wide Complex Trait Analysis) is a computational toolkit for estimating heritability and genetic correlations from genome-wide genotype and phenotype data. Developed by Yang and Visscher in 2011, GCTA uses genome-wide restricted maximum likelihood (GREML) to partition phenotypic variance into components explained by common SNPs, environmental factors, and residual variation. GCTA has become a standard tool for understanding the proportion of trait variation attributable to genetics across complex diseases and quantitative traits. | A polygenic risk score (PRS) is a summary measure that aggregates the effects of many genetic variants across the genome to predict an individual's genetic predisposition to disease or other complex traits. Developed initially by Purcell and colleagues in 2007, PRS methods combine genome-wide association study (GWAS) results with an individual's genotype to generate a personalized risk estimate. PRS approaches have transformed precision medicine by enabling risk stratification and early intervention in populations at high genetic risk. |
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