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| Полигенен рисков резултат× | Картографиране на количествени локуси (QTL)× | |
|---|---|---|
| Област | Генетика | Генетика |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2007 | 1989 |
| Създател≠ | Shaun Purcell & Nicholas Wray | Eric Lander & David Botstein |
| Тип≠ | Predictive genomic method | Genetic linkage method |
| Основополагащ източник≠ | 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 ↗ | Lander, E. S., & Botstein, D. (1989). Mapping Mendelian traits using RFLP linkage maps. Genetics, 121(1), 185–199. link ↗ |
| Други названия | PRS, Polygenic score, Genomic risk score | QTL analysis, Linkage mapping, Trait locus mapping |
| Свързани | 4 | 4 |
| Резюме≠ | 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. | Quantitative trait loci (QTL) mapping is a genetic method that localizes chromosomal regions influencing quantitative traits—continuous phenotypes controlled by multiple genes and environmental factors. Developed by Lander and Botstein in 1989, QTL mapping uses linkage analysis and trait variation in segregating populations (such as F2 crosses or recombinant inbred lines) to identify genomic intervals containing loci that substantially affect trait values. This foundational approach has been extended to genome-wide association and is essential for understanding the genetic architecture of complex traits. |
| ScholarGateНабор от данни ↗ |
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