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| GCTA× | F統計量 (FST)× | |
|---|---|---|
| 分野 | 遺伝学 | 遺伝学 |
| 系統 | Process / pipeline | Process / pipeline |
| 提唱年≠ | 2011 | 1951 |
| 提唱者≠ | Jian Yang & Peter Visscher | Sewall Wright |
| 種類≠ | Computational analysis tool | Population differentiation measure |
| 原典≠ | 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 ↗ | Wright, S. (1951). The genetical structure of populations. Annals of Eugenics, 15(4), 323–354. DOI ↗ |
| 別名 | GREML, Genome-wide complex trait analysis, Heritability estimation | FST, Wright's F-statistics, Population differentiation index |
| 関連 | 4 | 4 |
| 概要≠ | 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. | F-statistics are a family of measures developed by Sewall Wright to quantify population genetic structure and the degree of genetic differentiation between populations. FST, the most widely used F-statistic, measures the proportion of total genetic variation attributable to differences between populations versus within populations. FST ranges from zero (no differentiation) to one (complete differentiation). These statistics have become fundamental tools for understanding population structure, detecting population admixture, and analyzing the evolutionary forces shaping genetic variation. |
| ScholarGateデータセット ↗ |
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