Сравнение методов

	GCTA (Genome-wide Complex Trait Analysis)	F-статистики (FST)
Область	Генетика	Генетика
Семейство	Process / pipeline	Process / pipeline
Год появления	2011	1951
Автор метода	Jian Yang & Peter Visscher	Sewall Wright
Тип	Computational analysis tool	Population differentiation measure
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.	Wright, S. (1951). The genetical structure of populations. Annals of Eugenics, 15(4), 323–354.
Другие названия	GREML, Genome-wide complex trait analysis, Heritability estimation	FST, Wright's F-statistics, Population differentiation index
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.	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.