phylocomr

phylocomr gives you access to the Phylocom C library, licensed under BSD 2-clause

Package API

ecovolve/ph_ecovolve - interface to ecovolve executable, and a higher level interface
phylomatic/ph_phylomatic - interface to phylomatic executable, and a higher level interface
phylocom - interface to phylocom executable
ph_aot - higher level interface to aot
ph_bladj - higher level interface to bladj
ph_comdist/ph_comdistnt - higher level interface to comdist
ph_comstruct - higher level interface to comstruct
ph_comtrait - higher level interface to comtrait
ph_pd - higher level interface to Faith’s phylogenetic diversity

A note about files

As a convienence you can pass ages, sample and trait data.frame’s, and phylogenies as strings, to phylocomr functions. However, phylocomr has to write these data.frame’s/strings to disk (your computer’s file system) to be able to run the Phylocom code on them. Internally, phylocomr is writing to a temporary file to run Phylocom code, and then the file is removed.

In addition, you can pass in files instead of data.frame’s/strings. These are not themselves used. Instead, we read and write those files to temporary files. We do this for two reasons. First, Phylocom expects the files its using to be in the same directory, so if we control the file paths that becomes easier. Second, Phylocom is case sensitive, so we simply standardize all taxon names by lower casing all of them. We do this case manipulation on the temporary files so that your original data files are not modified.

Installation

Stable version:

install.packages("phylocomr")

Development version:

remotes::install_github("ropensci/phylocomr")

library("phylocomr")
library("ape")

ecovolve

ph_ecovolve(speciation = 0.05, extinction = 0.005, time_units = 50)

phylomatic

taxa_file <- system.file("examples/taxa", package = "phylocomr")
phylo_file <- system.file("examples/phylo", package = "phylocomr")
(taxa_str <- readLines(taxa_file))

#> [1] "campanulaceae/lobelia/lobelia_conferta"          
#> [2] "cyperaceae/mapania/mapania_africana"             
#> [3] "amaryllidaceae/narcissus/narcissus_cuatrecasasii"

(phylo_str <- readLines(phylo_file))

#> [1] "(((((eliea_articulata,homalanthus_populneus)malpighiales,rosa_willmottiae),((macrocentrum_neblinae,qualea_clavata),hibiscus_pohlii)malvids),(((lobelia_conferta,((millotia_depauperata,(layia_chrysanthemoides,layia_pentachaeta)layia),senecio_flanaganii)asteraceae)asterales,schwenkia_americana),tapinanthus_buntingii)),(narcissus_cuatrecasasii,mapania_africana))poales_to_asterales;"

ph_phylomatic(taxa = taxa_str, phylo = phylo_str)

#> [1] "(lobelia_conferta:5.000000,(mapania_africana:1.000000,narcissus_cuatrecasasii:1.000000):1.000000)poales_to_asterales:1.000000;\n"
#> attr(,"taxa_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/taxa_c8d610d7337b"
#> attr(,"phylo_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/phylo_c8d62074d8e0"

use various different references trees

library(brranching)
library(ape)

r2 <- ape::read.tree(text=brranching::phylomatic_trees[['R20120829']])
smith2011 <- ape::read.tree(text=brranching::phylomatic_trees[['smith2011']])
zanne2014 <- ape::read.tree(text=brranching::phylomatic_trees[['zanne2014']])

# R20120829 tree
taxa_str <- c(
  "asteraceae/bidens/bidens_alba",
  "asteraceae/cirsium/cirsium_arvense",
  "fabaceae/lupinus/lupinus_albus"
)
ph_phylomatic(taxa = taxa_str, phylo = r2)

#> [1] "(((bidens_alba:13.000000,cirsium_arvense:13.000000):19.000000,lupinus_albus:27.000000):12.000000)euphyllophyte:1.000000;\n"
#> attr(,"taxa_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/taxa_c8d656a7d848"
#> attr(,"phylo_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/phylo_c8d625688b6a"

# zanne2014 tree
taxa_str <- c(
  "zamiaceae/dioon/dioon_edule",
  "zamiaceae/encephalartos/encephalartos_dyerianus",
  "piperaceae/piper/piper_arboricola"
)
ph_phylomatic(taxa = taxa_str, phylo = zanne2014)

#> [1] "(((dioon_edule:121.744843,encephalartos_dyerianus:121.744850)zamiaceae:230.489838,piper_arboricola:352.234711)spermatophyta:88.058670):0.000000;\n"
#> attr(,"taxa_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/taxa_c8d67298ef55"
#> attr(,"phylo_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/phylo_c8d61688f03a"

# zanne2014 subtree
zanne2014_subtr <- ape::extract.clade(zanne2014, node='Loganiaceae')
zanne_subtree_file <- tempfile(fileext = ".txt")
ape::write.tree(zanne2014_subtr, file = zanne_subtree_file)
taxa_str <- c(
  "loganiaceae/neuburgia/neuburgia_corynocarpum",
  "loganiaceae/geniostoma/geniostoma_borbonicum",
  "loganiaceae/strychnos/strychnos_darienensis"
)
ph_phylomatic(taxa = taxa_str, phylo = zanne2014_subtr)

#> [1] "((neuburgia_corynocarpum:32.807743,(geniostoma_borbonicum:32.036335,strychnos_darienensis:32.036335):0.771406):1.635496)loganiaceae:0.000000;\n"
#> attr(,"taxa_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/taxa_c8d630ca1ff3"
#> attr(,"phylo_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/phylo_c8d625f7a38b"

ph_phylomatic(taxa = taxa_str, phylo = zanne_subtree_file)

#> [1] "((neuburgia_corynocarpum:32.807743,(geniostoma_borbonicum:32.036335,strychnos_darienensis:32.036335):0.771406):1.635496)loganiaceae:0.000000;\n"
#> attr(,"taxa_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/taxa_c8d625120e26"
#> attr(,"phylo_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/phylo_c8d6445ef3cd"

aot

traits_file <- system.file("examples/traits_aot", package = "phylocomr")
phylo_file <- system.file("examples/phylo_aot", package = "phylocomr")
traitsdf_file <- system.file("examples/traits_aot_df", package = "phylocomr")
traits <- read.table(text = readLines(traitsdf_file), header = TRUE,
  stringsAsFactors = FALSE)
phylo_str <- readLines(phylo_file)
ph_aot(traits = traits, phylo = phylo_str)

#> $trait_conservatism
#> # A tibble: 124 x 28
#>    trait trait.name  node name    age ntaxa n.nodes tip.mn tmn.ranklow
#>    <int> <chr>      <int> <chr> <dbl> <int>   <int>  <dbl>       <int>
#>  1     1 traitA         0 a         5    32       2   1.75        1000
#>  2     1 traitA         1 b         4    16       2   1.75         638
#>  3     1 traitA         2 c         3     8       2   1.75         645
#>  4     1 traitA         3 d         2     4       2   1.5          238
#>  5     1 traitA         4 e         1     2       2   1             51
#>  6     1 traitA         7 f         1     2       2   2           1000
#>  7     1 traitA        10 g         2     4       2   2           1000
#>  8     1 traitA        11 h         1     2       2   2           1000
#>  9     1 traitA        14 i         1     2       2   2           1000
#> 10     1 traitA        17 j         3     8       2   1.75         663
#> # … with 114 more rows, and 19 more variables: tmn.rankhi <int>, tip.sd <dbl>,
#> #   tsd.ranklow <int>, tsd.rankhi <int>, node.mn <dbl>, nmn.ranklow <int>,
#> #   nmn.rankhi <int>, nod.sd <dbl>, nsd.ranklow <int>, nsd.rankhi <int>,
#> #   sstipsroot <dbl>, sstips <dbl>, percvaramongnodes <dbl>,
#> #   percvaratnode <dbl>, contributionindex <dbl>, sstipvnoderoot <dbl>,
#> #   sstipvnode <dbl>, ssamongnodes <dbl>, sswithinnodes <dbl>
#> 
#> $independent_contrasts
#> # A tibble: 31 x 17
#>     node name    age n.nodes contrast1 contrast2 contrast3 contrast4 contrastsd
#>    <int> <chr> <dbl>   <int>     <dbl>     <dbl>     <dbl>     <dbl>      <dbl>
#>  1     0 a         5       2     0         0         0         0.254       1.97
#>  2     1 b         4       2     0         1.03      0         0.516       1.94
#>  3     2 c         3       2     0.267     0.535     0         0           1.87
#>  4     3 d         2       2     0.577     0         1.15      0           1.73
#>  5     4 e         1       2     0         0         0.707     0           1.41
#>  6     7 f         1       2     0         0         0.707     0           1.41
#>  7    10 g         2       2     0         0         1.15      0           1.73
#>  8    11 h         1       2     0         0         0.707     0           1.41
#>  9    14 i         1       2     0         0         0.707     0           1.41
#> 10    17 j         3       2     0.267     0.535     0         0           1.87
#> # … with 21 more rows, and 8 more variables: lowval1 <dbl>, hival1 <dbl>,
#> #   lowval2 <dbl>, hival2 <dbl>, lowval3 <dbl>, hival3 <dbl>, lowval4 <dbl>,
#> #   hival4 <dbl>
#> 
#> $phylogenetic_signal
#> # A tibble: 4 x 5
#>   trait  ntaxa varcontr varcn.ranklow varcn.rankhi
#>   <chr>  <int>    <dbl>         <int>        <int>
#> 1 traitA    32    0.054             1         1000
#> 2 traitB    32    0.109             1         1000
#> 3 traitC    32    0.622            67          934
#> 4 traitD    32    0.011             1         1000
#> 
#> $ind_contrast_corr
#> # A tibble: 3 x 6
#>   xtrait ytrait ntaxa  picr  npos ncont
#>   <chr>  <chr>  <int> <dbl> <dbl> <int>
#> 1 traitA traitB    32 0.248  18.5    31
#> 2 traitA traitC    32 0.485  27.5    31
#> 3 traitA traitD    32 0      16.5    31

bladj

ages_file <- system.file("examples/ages", package = "phylocomr")
phylo_file <- system.file("examples/phylo_bladj", package = "phylocomr")
ages_df <- data.frame(
  a = c('malpighiales','salicaceae','fabaceae','rosales','oleaceae',
        'gentianales','apocynaceae','rubiaceae'),
  b = c(81,20,56,76,47,71,18,56)
)
phylo_str <- readLines(phylo_file)
(res <- ph_bladj(ages = ages_df, phylo = phylo_str))

#> [1] "((((((lomatium_concinnum:20.250000,campanula_vandesii:20.250000):20.250000,(((veronica_candidissima:10.125000,penstemon_paniculatus:10.125000)plantaginaceae:10.125000,justicia_oblonga:20.250000):10.125000,marsdenia_gilgiana:30.375000):10.125000):10.125000,epacris_alba-compacta:50.625000)ericales_to_asterales:10.125000,((daphne_anhuiensis:20.250000,syzygium_cumini:20.250000)malvids:20.250000,ditaxis_clariana:40.500000):20.250000):10.125000,thalictrum_setulosum:70.875000)eudicots:10.125000,((dendrocalamus_giganteus:27.000000,guzmania_densiflora:27.000000)poales:27.000000,warczewiczella_digitata:54.000000):27.000000)malpighiales:1.000000;\n"
#> attr(,"ages_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/ages"
#> attr(,"phylo_file")
#> [1] "/var/folders/fc/n7g_vrvn0sx_st0p8lxb3ts40000gn/T//RtmpLApP50/phylo_c8d65b2958fd"

plot(ape::read.tree(text = res))