مقایسهٔ روش‌ها

	آماره‌های F (FST)	تحلیل آمیختگی	نظریه همگرایی	تحلیل بلوک‌های LD	جاروب انتخابی (D تاجیما)
حوزه	ژنتیک	ژنتیک	ژنتیک	ژنتیک	ژنتیک
خانواده	Process / pipeline	Process / pipeline	Process / pipeline	Process / pipeline	Process / pipeline
سال پیدایش	1951	2009	1982	2002	1989
پدیدآور	Sewall Wright	David Alexander & Jonathan Novembre	John Kingman	Shaun Gabriel & Eric Lander	Fumio Tajima
نوع	Population differentiation measure	Clustering and inference method	Stochastic process model	Haplotype analysis method	Neutrality test
منبع بنیادین	Wright, S. (1951). The genetical structure of populations. Annals of Eugenics, 15(4), 323–354.	Alexander, D. H., Novembre, J., & Lange, K. (2009). Fast model-based estimation of ancestry in unrelated individuals. Genome Research, 19(9), 1655–1664.	Kingman, J. F. C. (1982). The coalescent. Stochastic Processes and their Applications, 13(3), 235–248.	Gabriel, S. B., Schaffner, S. F., Nguyen, H., Moore, J. M., Roy, J., Blumenstiel, B., & Lander, E. S. (2002). The structure of haplotype blocks in the human genome. Science, 296(5576), 2225–2229.	Tajima, F. (1989). Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics, 123(3), 585–595.
نام‌های دیگر	FST, Wright's F-statistics, Population differentiation index	Population structure inference, Ancestry analysis, ADMIXTURE	Kingman Coalescent, n-coalescent	Haplotype block analysis, LD mapping, Block structure analysis	Tajima's D test, Selective sweep analysis, Neutrality test
مرتبط	4	4	4	5	4
خلاصه	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.	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.	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.	Linkage disequilibrium (LD) block analysis is a genomic method that partitions the human genome into distinct haplotype blocks—regions of limited recombination where variants are in strong statistical association. First systematically described by Gabriel and colleagues in 2002, this approach reveals the underlying structure of genetic variation and enables efficient genomic studies by reducing the number of variants needed to capture common diversity. LD block analysis forms the foundation of genome-wide association study (GWAS) design and modern population genetics.	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.