For a discussion on the difference between "site" and "branch" options of the
mode argument, please see the tskit documentation at
https://tskit.dev/tskit/docs/stable/stats.html#sec-stats-mode
Usage
ts_tajima(ts, sample_sets, mode = c("site", "branch", "node"), windows = NULL)Arguments
- ts
Tree sequence object of the class
slendr_ts- sample_sets
A list (optionally a named list) of character vectors with individual names (one vector per set). If a simple vector is provided, it will be interpreted as
as.list(sample_sets), meaning that a given statistic will be calculated for each individual separately.- mode
The mode for the calculation ("sites" or "branch")
- windows
Coordinates of breakpoints between windows. The first coordinate (0) and the last coordinate (equal to
ts$sequence_length) are added automatically)
Value
For each set of individuals either a single Tajima's D value or a vector of Tajima's D values (one for each window)
Examples
check_dependencies(python = TRUE, quit = TRUE) # dependencies must be present
init_env()
#> The interface to all required Python modules has been activated.
# load an example model with an already simulated tree sequence
slendr_ts <- system.file("extdata/models/introgression_slim.trees", package = "slendr")
model <- read_model(path = system.file("extdata/models/introgression", package = "slendr"))
# load the tree-sequence object from disk
ts <- ts_read(slendr_ts, model) %>% ts_mutate(mutation_rate = 1e-8, random_seed = 42)
# calculate Tajima's D for given sets of individuals in a tree sequence ts
ts_tajima(ts, list(eur = c("EUR_1", "EUR_2", "EUR_3", "EUR_4", "EUR_5"),
nea = c("NEA_1", "NEA_2")))
#> # A tibble: 2 × 2
#> set D
#> <chr> <dbl>
#> 1 eur -1.00
#> 2 nea 2.16