iCAMP (version 1.8.6)

mntd.big: Mean nearest taxon distance (MNTD) for big data

Description

Calculate mean nearest taxon distance (MNTD) in each community in a given community matrix, using 'bigmemory' to deal with too large dataset.

Usage

mntd.big(comm, pd.desc = "pd.desc", pd.spname = NULL,
         pd.wd = getwd(), spname.check = FALSE,
         abundance.weighted = TRUE, silent = TRUE,
         memory.G = 50)

Value

result is a numeric vector with sample names

Arguments

comm

matrix or data.frame, community data matrix, rownames are sample names, colnames are OTU ids.

pd.desc

character, the name to describe bigmemory file of phylogenetic distance matrix, default is "pd.desc".

pd.spname

vector, the OTU ids (species names) in exactly the same order as the phylogenetic matrix rows or columns

pd.wd

the path of the folder saving the phylogenetic distance matrix.

spname.check

logic, whether to check the OTU ids (species names) in community matrix and phylogenetic distance matrix are the same.

abundance.weighted

logic, whether weighted by species abundance, default is TRUE, means weighted.

silent

Logic, if FALSE, some messages will be showed during calculation. Default is FALSE.

memory.G

numeric, to set the memory size as you need, so that calculation of large tree will not be limited by physical memory. unit is Gb. default is 50Gb.

Author

Daliang Ning

Details

mean nearest taxon distance (MNTD) in each community, using the same algrithm as the function 'mntd' in package 'picante'.

References

Webb CO, Ackerly DD, and Kembel SW. (2008). Phylocom: software for the analysis of phylogenetic community structure and trait evolution. Bioinformatics 18:2098-2100

Kembel, S.W., Cowan, P.D., Helmus, M.R., Cornwell, W.K., Morlon, H., Ackerly, D.D. et al. (2010). Picante: R tools for integrating phylogenies and ecology. Bioinformatics, 26, 1463-1464.

See Also

NTI.cm.big

Examples

data("example.data")
comm=example.data$comm
tree=example.data$tree

# since it needs to save some file to a certain folder,
# the following code is set as 'not test'.
# but you may test the code on your computer
# after change the folder path for 'save.wd'.
# \donttest{
wd0=getwd()
save.wd=paste0(tempdir(),"/pdbig.mntd.big")
# you may change save.wd to the folder you want to save the pd.big output.
nworker=2 # parallel computing thread number
pd.big=pdist.big(tree = tree, wd=save.wd, nworker = nworker)
mntd.wt=mntd.big(comm=comm, pd.desc = pd.big$pd.file,
               pd.spname = pd.big$tip.label, pd.wd = pd.big$pd.wd,
               spname.check = FALSE, abundance.weighted = TRUE)
setwd(wd0)
# }