Сравнение на методи

	Тестът на McDonald-Kreitman (MK)	Тест на ХКА	Селективен суип (D на Таджима)
Област	Генетика	Генетика	Генетика
Семейство	Process / pipeline	Process / pipeline	Process / pipeline
Година на възникване	1991	1987	1989
Създател	James McDonald & Martin Kreitman	Richard Hudson, Martin Kreitman & Montserrat Aguade	Fumio Tajima
Тип	Hypothesis test	Statistical test	Neutrality test
Основополагащ източник	McDonald, J. H., & Kreitman, M. (1991). Adaptive protein evolution at the Adh locus in Drosophila. Nature, 351(6328), 652–654.	Hudson, R. R., Kreitman, M., & Aguadé, M. (1987). A test of neutral molecular evolution based on nucleotide data. Genetics, 116(1), 153–159.	Tajima, F. (1989). Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics, 123(3), 585–595.
Други названия	MK test, Positive selection test	HKA test, Polymorphism divergence test	Tajima's D test, Selective sweep analysis, Neutrality test
Свързани	4	4	4
Резюме	The McDonald-Kreitman (MK) test is a statistical method for detecting adaptive evolution by comparing ratios of synonymous and nonsynonymous substitutions within and between species. Developed by James McDonald and Martin Kreitman in 1991, this test exploits the key insight that neutral mutations accumulate at similar rates within and between species, while adaptive (nonsynonymous) substitutions should be enriched between species if they have been fixed by positive selection. The MK test has become a standard tool in molecular evolutionary biology for identifying genes under natural selection.	The Hudson-Kreitman-Aguade (HKA) test is a statistical method that tests for neutral evolution by comparing levels of within-population polymorphism and between-population divergence at multiple loci. Developed by Hudson, Kreitman, and Aguade in 1987, this test uses the principle that neutral loci should show expected relationships between polymorphism and divergence. Loci deviating from these relationships are candidates for selection. The HKA test is particularly useful for detecting selection in genome-wide surveys because it uses relative comparisons across loci rather than requiring external calibration.	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.