Identify ancestral recombination graphs under selection that correspond to models of divergence.

Usage

identify_argcandidates_divergence(
  dat,
  analysis = "all",
  background = NULL,
  tmrca.threshold = NULL,
  pop1.threshold = NULL,
  pop2.threshold = NULL,
  tmrca.iqr.low.threshold = NULL,
  tmrca.iqr.high.threshold = NULL
)

Arguments

dat: a dataframe of ancestral recombination graph statistics calculated using the argstats function.
analysis: a character vector indicating the types of args you want to identify. Options are "all" for all types, "RI", "WP", "RS", "RIWP".
background: a dataframe of ancestral recombination graph statistics calculated using the argstats function. If supplied this will be used to define thresholds and the dat argument will be treated as the test set.
tmrca.threshold: a numeric value to customize the tmrca threshold used to identify ARGs associated with reproductive isolation.
pop1.threshold: a numeric value to customize the pop1 tmrcaw threshold used to identify ARGs associated with within-population selection and recurrent selection.
pop2.threshold: a numeric value to customize the pop2 tmrcaw threshold used to identify ARGs associated with within-population selection and recurrent selection.
tmrca.iqr.low.threshold: a numeric value to customize the lower tmrca threshold used to identify ARGs associated with within-population selection and recurrent selection.
tmrca.iqr.high.threshold: a numeric value to customize the upper tmrca threshold used to identify ARGs associated with within-population selection and recurrent selection.

Value

a list containing ARGs that were identified as candidates

Examples

# \donttest{
data("rattlesnake_argstats")
#> Warning: data set ‘rattlesnake_argstats’ not found
data("rattlesnake_pops")

pop2 <- rattlesnake_pops[which(rattlesnake_pops$species == "pop2"),]
pop1 <- rattlesnake_pops[which(rattlesnake_pops$species == "pop1"),]

stat_res <- argstats(arg.dat = rattlesnake_args, pop1 = pop1$sample, pop2 = pop2$sample, pop1.name = "pop1", pop2.name = "pop2")

stat_df <- do.call("rbind", stat_res)

Test <- identify_argcandidates_divergence(dat = stat_df, analysis = "all")# }