Extract all descendants of a given tree-sequence node
Arguments
- ts
Tree sequence object of the class
slendr_ts- x
An integer node ID of the ancestral node
- verbose
Report on the progress of ancestry path generation?
- complete
Does every individual in the tree sequence need to have complete metadata recorded? If
TRUE, only individuals/nodes with complete metadata will be included in the reconstruction of ancestral relationships. For instance, nodes added during the coalescent recapitation phase will not be included because they don't have spatial information associated with them.
Value
A table of descendant nodes of a given tree-sequence node all the way down to the leaves of the tree sequence
Examples
init_env()
#> Python virtual environment for slendr 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)
# find the complete descendancy information for a given individual
ts_descendants(ts, x = 62, verbose = TRUE)
#>
#> Generating data about spatial relationships of nodes...
#> # A tibble: 18 × 12
#> name pop node_id level child_id parent_id child_time parent_time child_pop
#> <chr> <fct> <dbl> <fct> <int> <int> <dbl> <dbl> <fct>
#> 1 EUR_4 NEA 62 1 22 62 0 51800 EUR
#> 2 NA NEA 62 1 35 62 11000 51800 EUR
#> 3 NA NEA 62 1 36 62 12110 51800 EUR
#> 4 NA NEA 62 1 38 62 14060 51800 EUR
#> 5 NA NEA 62 1 48 62 24530 51800 EUR
#> 6 NA NEA 62 1 50 62 30560 51800 EUR
#> 7 NA NEA 62 1 56 62 40580 51800 NEA
#> 8 EUR_2 NEA 62 2 18 35 0 11000 EUR
#> 9 EUR_4 NEA 62 2 22 35 0 11000 EUR
#> 10 EUR_3 NEA 62 2 21 36 0 12110 EUR
#> 11 NA NEA 62 2 36 38 12110 14060 EUR
#> 12 EUR_5 NEA 62 2 25 48 0 24530 EUR
#> 13 NA NEA 62 2 35 48 11000 24530 EUR
#> 14 NA NEA 62 2 39 48 14750 24530 EUR
#> 15 NEA_2 NEA 62 2 2 56 40000 40580 NEA
#> 16 NEA_2 NEA 62 2 3 56 40000 40580 NEA
#> 17 NA NEA 62 3 34 39 10040 14750 EUR
#> 18 EUR_2 NEA 62 4 19 34 0 10040 EUR
#> # ℹ 3 more variables: parent_pop <fct>, left_pos <dbl>, right_pos <dbl>