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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.
In statistical hypothesis testing, a two-sample test is a test performed on the data of two random samples, each independently obtained from a different given population. The purpose of the test is to determine whether the difference between these two populations is statistically significant.
The McDonald–Kreitman test [1] is a statistical test often used by evolutionary and population biologists to detect and measure the amount of adaptive evolution within a species by determining whether adaptive evolution has occurred, and the proportion of substitutions that resulted from positive selection (also known as directional selection).
If the rate of neutral mutations in a sequence is assumed to be constant (clock-like), and if most differences between species are neutral rather than adaptive, then the number of differences between two different species can be used to estimate how long ago two species diverged (see molecular clock). In fact, the mutation rate of an organism ...
The set of these calculated differences is the exact distribution of possible differences (for this sample) under the null hypothesis that group labels are exchangeable (i.e., are randomly assigned). The one-sided p-value of the test is calculated as the proportion of sampled permutations where the difference in means was greater than T obs ...
Examples of gene flow within a species include the migration and then breeding of organisms, or the exchange of pollen. Gene transfer between species includes the formation of hybrid organisms and horizontal gene transfer. Population genetic models can be used to identify which populations show significant genetic isolation from one another ...
Kuiper's test is closely related to the better-known Kolmogorov–Smirnov test (or K-S test as it is often called). As with the K-S test, the discrepancy statistics D + and D − represent the absolute sizes of the most positive and most negative differences between the two cumulative distribution functions that are being compared
Through natural selection and random genetic drift, the traits with a negative effect on population fitness disappear from the gene pool. The balance between the influence of natural selection and genetic drift on the population mutation rate is mainly determined by the population size. [5]