手法を比較

	Selection Sweep (Tajima's D)	Coalescent Theory	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	1989	1982	1951
提唱者	Fumio Tajima	John Kingman	Sewall Wright
種類	Neutrality test	Stochastic process model	Population differentiation measure
原典	Tajima, F. (1989). Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics, 123(3), 585–595.	Kingman, J. F. C. (1982). The coalescent. Stochastic Processes and their Applications, 13(3), 235–248.	Wright, S. (1951). The genetical structure of populations. Annals of Eugenics, 15(4), 323–354.
別名	Tajima's D test, Selective sweep analysis, Neutrality test	Kingman Coalescent, n-coalescent	FST, Wright's F-statistics, Population differentiation index
関連	4	4	4
概要	Tajima's D is a statistical test designed to detect selective sweeps—recent, rapid fixation of advantageous mutations—from patterns of genetic variation in DNA sequences. Developed by Fumio Tajima in 1989, this test measures deviations from neutrality by comparing different measures of DNA sequence diversity. A significant Tajima's D value indicates departure from neutral evolution, suggesting positive selection, population structure, or demographic events.	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.	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.