simDecay: Plot community similarity decay against selected taxa or...

In hallucigenia-sparsa/seqtime: Time Series Analysis of Sequencing Data

Plot community similarity decay against selected taxa or metadata

Description

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

Usage

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)
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])

hallucigenia-sparsa/seqtime documentation built on Jan. 9, 2023, 11:53 p.m.