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Tajima's D is a population genetic test statistic created by and named after the Japanese researcher Fumio Tajima. [1] Tajima's D is computed as the difference between two measures of genetic diversity: the mean number of pairwise differences and the number of segregating sites, each scaled so that they are expected to be the same in a neutrally evolving population of constant size.
Fumio Tajima was born in Ōkawa, in Japan's Fukuoka prefecture, in 1951. [1] [2] He graduated from high school in 1970, completed his undergraduate degree at Kyushu University in 1976, and received a Master's degree from the same institution in 1978. [3]
The allele frequency spectrum can be written as the vector = (,,,,), where is the number of observed sites with derived allele frequency .In this example, the observed allele frequency spectrum is (,,,,), due to four instances of a single observed derived allele at a particular SNP loci, two instances of two derived alleles, and so on.
Tajima's D; Taleb distribution; Tampering (quality control) Taylor expansions for the moments of functions of random variables; Taylor's law – empirical variance-mean relations; Telegraph process; Test for structural change; Test–retest reliability; Test score; Test set; Test statistic; Testimator; Testing hypotheses suggested by the data ...
Population genomics is the large-scale comparison of DNA sequences of populations. Population genomics is a neologism that is associated with population genetics.Population genomics studies genome-wide effects to improve our understanding of microevolution so that we may learn the phylogenetic history and demography of a population.
Comparing the value of the Watterson's estimator, to nucleotide diversity is the basis of Tajima's D which allows inference of the evolutionary regime of a given locus. See also [ edit ]
Allele frequency, or gene frequency, is the relative frequency of an allele (variant of a gene) at a particular locus in a population, expressed as a fraction or percentage. [1]
Tajima's D is based on the expectation that S = theta * x where x is the sum of 1/i for i from 1 to N. Thus, we turn this into a method to estimate theta by noting that theta = E(S)/x. The current version suggests that S/x part is a "normalized" version of segregating sites, and this leads to a mistake in the calculation of D in the example.