Join Multiple Species Delimitation Methods Outputs

delim_join() returns a tbl_df of species delimitation outputs whose partitions are consistent across different methods.

Usage

delim_join(delim, return = c("both", "df", "removed"))

Arguments

delim

A list or data.frame of multiple species delimitation methods outputs.

return

Which type of output to be returned if there are missing values within any of the species partitions used as input for analysis. Default to "df".

Value

an object of class tbl_df.

Details

delim_join() is a helper function to join multiple lists or columns of species delimitation outputs into a single tbl_df while keeping consistent identifications across multiple methods. Species delimitation outputs are in general a list or data frame of sample labels and its species partitions (Species 1, Species 2, etc.). These partition names may be or not the same across two or more methods. delim_join() standardizes partition names across two or more species delimitation outputs while keeping its underlying structure intact.

Author

Pedro S. Bittencourt, Rupert A. Collins.

Examples

# \donttest{
## run GMYC
gmyc_res <- try( gmyc(ape::as.phylo(geophagus_beast), method = "single") )

# create a tibble
gmyc_df <- try( gmyc_tbl(gmyc_res) )

## run bGMYC
bgmyc_res <- try( bgmyc(ape::as.phylo(geophagus_beast),
  mcmc = 11000,
  burnin = 1000,
  thinning = 100,
  t1 = 2,
  t2 = ape::Ntip(ape::as.phylo(geophagus_beast)),
  start = c(1, 0.5, 50)
)
)
#> bGMYC (C engine): 137 tips, 11000 MCMC steps, 100 post-burnin samples
#> 10%
#> 20%
#> 30%
#> 40%
#> 50%
#> 60%
#> 70%
#> 80%
#> 90%
#> 100%
#> Acceptance rates (py / pc / t):
#> 0.5487  0.8376  0.3420
# create a tibble
bgmyc_df <- try( bgmyc_tbl(bgmyc_res, ppcutoff = 0.05) )

## LocMin

# create a distance matrix
mat <- try( ape::dist.dna(geophagus, model = "raw", pairwise.deletion = TRUE) )

# estimate local minima from `mat`
locmin_res <- try( spider::localMinima(mat) )
#> [1] 0.006828358 0.018994392 0.040791871 0.055999413 0.067151612 0.082105695

# create a tibble
locmin_df <- try( locmin_tbl(mat,
  threshold = locmin_res$localMinima[1],
  haps = ape::as.phylo(geophagus_beast)$tip.label
)
)
# join delimitations
all_delims <- try( delim_join(list(gmyc_df, bgmyc_df, locmin_df)) )
#> Checking species delimitation tables...
#> Checking table 1 against table 2...
#> ✔ Labels are the same across tables but they likely are unordered.
#> Checking table 1 against table 2...

#> Checking table 1 against table 3...
#> Checking table 1 against table 3...
#> ✔ Labels are the same across tables but they likely are unordered.
#> Checking table 1 against table 3...

#> ✔ Checking complete! All tables are consistent.
#> Checking table 1 against table 3...

#> Checking table 1 against table 3...

# check
try(all_delims)
#> # A tibble: 137 × 4
#>    labels     gmyc  bgmyc locmin
#>    <chr>      <chr> <chr> <chr> 
#>  1 GU701784.1 sp1   sp1   sp1   
#>  2 GU701785.1 sp1   sp1   sp1   
#>  3 MH780911.1 sp1   sp1   sp1   
#>  4 OR732927.1 sp1   sp1   sp1   
#>  5 JN988869.1 sp1   sp1   sp1   
#>  6 OR732928.1 sp1   sp1   sp1   
#>  7 MZ504448.1 sp2   sp2   sp2   
#>  8 MZ504450.1 sp2   sp2   sp2   
#>  9 MZ504454.1 sp2   sp2   sp2   
#> 10 MZ504457.1 sp3   sp3   sp3   
#> # ℹ 127 more rows

# }