iCAMP (version 1.8.6)

mpd.big: Mean pairwise distance (MPD) from big data.

Description

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

Usage

mpd.big(comm, pd.desc, pd.spname = NULL, pd.wd,
        sp.limit = 10000, spname.check = FALSE,
        abundance.weighted = TRUE)

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.

sp.limit

numeric, the limitation of species number in each round of the looping inside this funciton, default is 10000, generally fine for most computer, if returns error, set lower value.

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.

Author

Daliang Ning ([e-mail])

Details

mean pairwise distance (MPD) in each community, which is the same index as 'mpd' in package 'picante', but calculated by matrix multiplication and using bigmemory to handle big dataset.

References

Webb C, Ackerly D, McPeek M, and Donoghue M. (2002). Phylogenies and community ecology. Annual Review of Ecology and Systematics 33:475-505.

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

mpdn, NRI.p, NRI.cm

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.mpd.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)
mpd.wt=mpd.big(comm=comm, pd.desc = pd.big$pd.file,
               pd.spname = pd.big$tip.label, pd.wd = pd.big$pd.wd,
               sp.limit = 10000, spname.check = FALSE,
               abundance.weighted = TRUE)
setwd(wd0)
# }