A Reference Class for storing and manipulating the results and data from a four taxon test.

`P1`

Character The population which forms the P1 taxon in the four taxon test.

`P2`

Character The population which forms the P2 taxon in the four taxon test.

`P3`

Character The population which forms the P3 taxon in the four taxon test.

`A`

Character The population which forms the ancestral/outgroup taxon in the four taxon test.

`numBlocks`

integer The number of blocks the DNA sequence alignment was split into in order to perform the test.

`blockLength`

integer The number of base pairs to each block the DNA sequence alignment was split into to perform the test.

`ABBA`

numeric The global sum of ABBA sites. Given by

*(1 - Pr_1) * Pr_2 * Pr_3 * (1 - Pr_4)*. Where*Pr_i*is the frequency of the derived allele in the i'th population.`ABBA`

numeric The global sum of BABA sites. Given by

*Pr_1 * (1 - Pr_2) * Pr_3 * (1 - Pr_4)*. Where*Pr_i*is the frequency of the derived allele in the i'th population.`ABBAcount`

integer The number of sites for which ABBA was greater than BABA.

`BABAcount`

integer The number of sites for which BABA was greater than ABBA.

`globalX2`

numeric A chi squared value computed during the four taxon test. Used to assess whether ABBAcount and BABAcount are significantly different, based on the binomial distribution.

`X2_P`

numeric A p-value computer by the Fisher combined probability test based on globalX2. Indicates whether ABBAcount and BABAcount differ significantly.

`D_jEstimate`

numeric Patterson's D estimate based on jackknifeing the blocks of data.

`Fd_1DD4_jEstimate`

numeric A jackknifed estimate of Fd for complete introgression between populations 2 and 3.

`Fd_D2D4_jEstimate`

numeric A jackknifed estimate of Fd for complete introgression between populations 1 and 3.

`D_jVariance`

numeric Variance of Pattersons D estimates from jackknife.

`Fd_1DD4_jVariance`

numeric Variance of Fd estimates from jackknife. Where Fd is for total introgression between Populations 2 and 3.

`Fd_D2D4_jVariance`

numeric Variance of Fd estimates from jackknife. Where Fd is for total introgression between Populations 1 and 3.

`D_jSD`

numeric Standard deviation of Patterson's D estimates from jackknife.

`Fd_1DD4_jSD`

numeric Standard deviation of Fd estimates from jackknife. Where Fd is for total introgression between Populations 2 and 3.

`Fd_D2D4_jSD`

numeric Standard deviation of Fd estimates from jackknife. Where Fd is for total introgression between Populations 1 and 3.

`D_jZ`

numeric The Z score of Patterson's D, computed from the jackknife data.

`Fd_1DD4_jZ`

numeric The Z score of Fd, computed from the jackknife data. Where Fd is calculated for complete introgression between populations 2 and 3.

`Fd_D2D4_jZ`

numeric The Z score of Fd, computed from the jackknife data. Where Fd is calculated for complete introgression between populations 1 and 3.

`tableFile`

character A character string indicating the temporary file used to store the dataframe accessed with the table field.

`table`

function An accessor function used to access a table of results stored in a temporary file on disk. The location of this file is indicated by the tableFile field.

`blankTable()`

Method clears the table.

`getPops()`

Gets the population names from the result.

`getTable(includeGlobal, neat)`

Gets the results table for the blocks used to analyze the data.

`globallySignificant()`

Returns true if the test is significant according to the binomial.

`initialize(p1, p2, p3, a, HCDir)`

Initialize the result object.

`noTestPerformed()`

Returns true if a test has not been performed yet.

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