手法を比較

	Coalescent Theory	集団混合解析	F統計量 (FST)
分野	遺伝学	遺伝学	遺伝学
系統	Process / pipeline	Process / pipeline	Process / pipeline
提唱年	1982	2009	1951
提唱者	John Kingman	David Alexander & Jonathan Novembre	Sewall Wright
種類	Stochastic process model	Clustering and inference method	Population differentiation measure
原典	Kingman, J. F. C. (1982). The coalescent. Stochastic Processes and their Applications, 13(3), 235–248.	Alexander, D. H., Novembre, J., & Lange, K. (2009). Fast model-based estimation of ancestry in unrelated individuals. Genome Research, 19(9), 1655–1664.	Wright, S. (1951). The genetical structure of populations. Annals of Eugenics, 15(4), 323–354.
別名	Kingman Coalescent, n-coalescent	Population structure inference, Ancestry analysis, ADMIXTURE	FST, Wright's F-statistics, Population differentiation index
関連	4	4	4
概要	Coalescent theory is a probabilistic framework that traces the genealogical history of DNA sequences backward in time to their most recent common ancestor. Developed by John Kingman in 1982, this method forms the foundation of modern population genetics, enabling researchers to understand demographic events, estimate genetic parameters, and reconstruct evolutionary histories from modern genetic data.	Admixture analysis is a population genetics method that infers population structure and individual ancestry from multilocus genotype data. Originally developed by Pritchard, Stephens, and Donnelly (2000) and refined by Alexander, Novembre, and Lange (2009), admixture analysis reveals how genetic variation is distributed among populations and estimates the ancestry fractions of admixed individuals. This technique is essential for understanding human evolutionary history, detecting population stratification in genetic studies, and inferring individual ancestry.	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.