Learn R Programming

metagenomeSeq (version 1.14.0)

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

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

plotOTU(obj, otu, classIndex, log = TRUE, norm = TRUE, jitter.factor = 1, pch = 21, labs = TRUE, xlab = NULL, ylab = NULL, jitter = TRUE, ...)

Arguments

obj
A MRexperiment object with count data.
otu
The row number/OTU to plot.
classIndex
A list of the samples in their respective groups.
log
Whether or not to log2 transform the counts - if MRexperiment object.
norm
Whether or not to normalize the counts - if MRexperiment object.
jitter.factor
Factor value for jitter.
pch
Standard pch value for the plot command.
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.
...
Additional plot arguments.

Value

Plotted values

See Also

cumNorm

Examples

Run this code

data(mouseData)
classIndex=list(controls=which(pData(mouseData)$diet=="BK"))
classIndex$cases=which(pData(mouseData)$diet=="Western")
# you can specify whether or not to normalize, and to what level
plotOTU(mouseData,otu=9083,classIndex,norm=FALSE,main="9083 feature abundances")

Run the code above in your browser using DataLab