CompareRlaPlots: CompareRlaPlots
In NormalizeMets: Analysis of Metabolomics Data

Produces within group and across group relative log abundance plots to visually compare between different normalization methods

CompareRlaPlots(lfeaturedata, groupdata, normmeth = NULL, type = c("ag",
  "wg"), yrange = NULL, plottitle = "RLA plots Comparison",
  saveinteractiveplot = FALSE, savenoninteractive = FALSE,
  interactivesavename = "RlaPlotsComp", ...)

`lfeaturedata`	A list containing data frames in the featuredata format.
`groupdata`	A vector containing group information.
`normmeth`	A vector with the normalization method used corresponding in order to the data supplied to be displayed on the plot.
`type`	A character string indicating whether within group ("`wg`") or across group ("`ag`") RLA plots need to be plotted.
`yrange`	A vector with the first entry corresponding to the minimum y-axis value and the second to the maximum y-axis value to show as default on all the plots. This can be zoomed out as the plot is interactive.
`plottitle`	The title to be displayed on the plot.
`saveinteractiveplot`	A boolean indicating whether the interactive plto should be save as a `.html` file.
`savenoninteractive`	A boolean indicating whether a `.png` version of the plto should be save as a.
`interactivesavename`	A character string to be used as the filename for saving the interactive plot.
`...`	Other arguments to `RlaPlots` function.

data(UVdata)
# Not RUN due to user input; we set k=1 each and saved normalized data as uv_ruvrandclust
# uv_ruvrand_norm<-NormQcmets(featuredata=UVdata$featuredata,
#                            method="ruvrandclust",
#                            qcmets=which(UVdata$metabolitedata$neg_control==1),
#                            k=1)
data("uv_ruvrandclust")
lfeaturedata<-list(unadj=UVdata$featuredata,ruv=uv_ruvrandclust$featuredata,
   ruvuv=uv_ruvrandclust$uvdata)
#CompareRlaPlots(lfeaturedata,
#                groupdata=interaction(UVdata$sampledata$temperature,UVdata$sampledata$instrument),
#                normmeth=c("Unadjusted:", "RUVrandclust normalized:", 
#                           "RUVrandclust: removed uv:"),
#               yrange=c(-3,3))