Plot community similarity decay against selected taxa or metadata

Source: R/simDecay.R

All pair-wise community dissimilarities are plotted against the corresponding abundance difference of selected taxa or metadata.

simDecay(x, taxa = c(), metadata = c(), metadataName = "",
  samplegroups = rep(1, ncol(x)), dissim = "bray", normtaxa = FALSE,
  logdissim = FALSE, intragroupsOnly = FALSE, header = "",
  groupName = "", inversePlot = FALSE)

Arguments

x

taxon-sample matrix with taxa as rows and samples as columns
taxa

vector of taxon row indices or row names present in x
metadata

vector with values in the same order as samples in the taxon matrix
metadataName

name of the metadata vector (e.g. age)
samplegroups

supposed to assign an integer to each sample, with integers ranging from 1 to group number. If provided, intra-group dissimilarity dots are colored by sample group
dissim

dissimilarity measure to use, a measure supported by vegan's vegdist function
normtaxa

divide each taxon vector in x by its sum
logdissim

take the logarithm of the dissimilarity before fitting a line
intragroupsOnly

only take sample pairs within the same group into account for dissimilarity computation (groups are labeled in the plot by their identifier)
header

a string to be appended to the plot title (Dissimilarity change)
groupName

the name for the groups displayed in the legend (defaults to group)
inversePlot

plot community dissimilarity on the x-axis instead of on the y-axis

Examples

N=50
data("david_stoolA_otus")
rar=rarefyFilter(david_stoolA_otus,min=10000)
#> [1] "Number of columns 329"
#> [1] "Keeping  311  columns with column sums equal or above 10000"
data=rar[[1]]
# Faecalibacterium OTUs
taxa=c("OTU_72853","OTU_119271")
out1=simDecay(data[,1:N],taxa)
data("david_stoolA_metadata")
days=david_stoolA_metadata[1,rar[[2]]] # only keep samples that made it through rarefaction
out2=simDecay(data[,1:N],metadata=days[1:N],metadataName=rownames(david_stoolA_metadata)[1])