View source: R/samplingProbs.R
samplingProbs | R Documentation |
If the user would like to specify species sampling on a
clade-by-clade basis, a sampling probability table can be provided to
BAMM
.
samplingProbs(
tree,
cladeTable,
cladeRichness = NULL,
globalSampling,
output,
writeToDisk = TRUE
)
tree |
An object of class |
cladeTable |
A dataframe with one column of species names and a second column of group assignment. |
cladeRichness |
Either |
globalSampling |
percent sampling for the backbone of the phylogeny. |
output |
Path + output file name. |
writeToDisk |
A logical, should the table be written to disk,
defaults to |
This function handles two types of input: The cladeTable can
either contain the species found in the phylogeny, along with clade
assignment of those species, or it can contain more species than found
in the phylogeny. If the table only contains those species in the
phylogeny, then a vector cladeRichness
must be provided that
contains known clade richness. If the cladeTable contains more than
the species in the phylogeny, then cladeRichness should be set to
NULL
. The globalSampling
value should represent the
overall completeness of species sampling in terms of major clades. See
http://bamm-project.org/ for additional details.
If writeToDisk = TRUE
, then no object is returned. If
writeToDisk = FALSE
, then a dataframe is returned. The
resultant table must contain one row for each species in the
phylogeny, along with clade assignment, and sampling fraction. The
first line must contain the overall sampling fraction for the
phylogeny and must be written as tab-delimited, with no headers.
Pascal Title
# Generate dummy data
tree <- read.tree(text="(((t1:2,(t2:1,t3:1):1):1,((t4:1,t5:1):1,t6:2):1)
:1,(t7:3,(t8:2,t9:2):1):1);")
tree$tip.label <- paste(rep('Species',9),1:9,sep='')
spTable <- as.data.frame(matrix(nrow=9,ncol=2))
spTable[,1] <- tree$tip.label
spTable[1:3,2] <- 'cladeA'
spTable[4:6,2] <- 'cladeB'
spTable[7:9,2] <- 'cladeC'
richnessVec <- c(cladeA=5, cladeB=4, cladeC=12)
# Option 1: We have a table of clade assignment for the species in the
# tree, along with a vector of known clade richness
spTable
richnessVec
samplingProbs(tree, cladeTable = spTable, cladeRichness = richnessVec,
globalSampling = 1, writeToDisk = FALSE)
# Option 2: We have a table of known species, beyond the sampling in the
# phylogeny
spTable <- rbind(spTable, c('Species10','cladeA'),c('Species11','cladeA'),
c('Species12','cladeC'), c('Species13','cladeC'),
c('Species14','cladeC'))
spTable
samplingProbs(tree, cladeTable = spTable, cladeRichness = NULL,
globalSampling = 0.9, writeToDisk = FALSE)
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