Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| GCTA (Genome-wide Complex Trait Analysis)× | Картирование количественных признаков (QTL Mapping)× | |
|---|---|---|
| Область | Генетика | Генетика |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2011 | 1989 |
| Автор метода≠ | Jian Yang & Peter Visscher | Eric Lander & David Botstein |
| Тип≠ | Computational analysis tool | Genetic linkage method |
| Основополагающий источник≠ | 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 ↗ | Lander, E. S., & Botstein, D. (1989). Mapping Mendelian traits using RFLP linkage maps. Genetics, 121(1), 185–199. link ↗ |
| Другие названия | GREML, Genome-wide complex trait analysis, Heritability estimation | QTL analysis, Linkage mapping, Trait locus mapping |
| Связанные | 4 | 4 |
| Сводка≠ | 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. | 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 данных ↗ |
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