plotGenus: Basic plot function of the raw or normalized data.

In metagenomeSeq: Statistical analysis for sparse high-throughput sequencing

Description

This function plots the abundance of a particular OTU by class. The function uses the estimated posterior probabilities to make technical zeros transparent.

Usage

plotGenus(
  obj,
  otuIndex,
  classIndex,
  norm = TRUE,
  log = TRUE,
  no = 1:length(otuIndex),
  labs = TRUE,
  xlab = NULL,
  ylab = NULL,
  jitter = TRUE,
  jitter.factor = 1,
  pch = 21,
  ...
)

Arguments

obj	An MRexperiment object with count data.
otuIndex	A list of the otus with the same annotation.
classIndex	A list of the samples in their respective groups.
norm	Whether or not to normalize the counts - if MRexperiment object.
log	Whether or not to log2 transform the counts - if MRexperiment object.
no	Which of the otuIndex to plot.
labs	Whether to include group labels or not. (TRUE/FALSE)
xlab	xlabel for the plot.
ylab	ylabel for the plot.
jitter	Boolean to jitter the count data or not.
jitter.factor	Factor value for jitter
pch	Standard pch value for the plot command.
...	Additional plot arguments.

Value

plotted data

See Also

cumNorm

Examples

data(mouseData)
classIndex=list(controls=which(pData(mouseData)$diet=="BK"))
classIndex$cases=which(pData(mouseData)$diet=="Western")
otuIndex = grep("Strep",fData(mouseData)$family)
otuIndex=otuIndex[order(rowSums(MRcounts(mouseData)[otuIndex,]),decreasing=TRUE)]
plotGenus(mouseData,otuIndex,classIndex,no=1:2,xaxt="n",norm=FALSE,ylab="Strep normalized log(cpt)")

metagenomeSeq documentation built on Nov. 8, 2020, 5:34 p.m.