NormalizeMets (version 0.25)

CompareVolcanoPlots: Compare Volcano plots

Description

Produces a volcano plot that can be sued to compare between different normalisation methods.

Usage

CompareVolcanoPlots(lcoef, lpvals, normmeth = NULL, plimit = 0.05,
  coeflimit = 1, yrange = NULL, negcontrol = NULL, poscontrol = NULL,
  xlab = "Coefficients", ylab = "-log(p-value)", labelunderlim = FALSE,
  labelsig = FALSE, saveinteractiveplot = FALSE,
  interactiveplotname = "interactiveVolcanPlot", ...)

Arguments

lcoef

A list of vectors of coefficients with metabolite names, each vector corresponding to a different noramlization method.

lpvals

A list of vector of corresponding p-values.

normmeth

A vector with the normalization method used corresponding in order to the data supplied to be displayed on the plot.

plimit

A numeric indicating the p value cutoff. The default is set to 0.05.

coeflimit

A numeric indicating the lower fold cutoff. The default is set to 2.

yrange

A numeric for the maximum y value (scale of y-axis is -log(p-value)), can only be set to a value as big as the maximum y-value in the plots.

negcontrol

A vector with the names of the metabolites used as negative controls, to be coloured differently.

poscontrol

A vector with the names of the metabolites used as positive controls, to be coloured differently.

xlab

x-axis label.

ylab

y-axis label.

labelunderlim

A logical indicating whether to label points that are not significant.

labelsig

A logical indicating whether all significant points should be labeled.

saveinteractiveplot

A logical indication whether the interactive plot produced should be saved as a .html file.

interactiveplotname

A character string indicating the name to be used for saving the interactive plot.

...

Arguments to VolcanoPlot function

See Also

VolcanoPlot

Examples

# NOT RUN {
data("alldata_eg")
featuredata_eg<-alldata_eg$featuredata
dataview(featuredata_eg)
sampledata_eg<-alldata_eg$sampledata
dataview(sampledata_eg)
metabolitedata_eg<-alldata_eg$metabolitedata
dataview(metabolitedata_eg)

logdata <- LogTransform(featuredata_eg)
dataview(logdata$featuredata)
imp <-  MissingValues(logdata$featuredata,sampledata_eg,metabolitedata_eg,
                     feature.cutof=0.8, sample.cutoff=0.8, method="knn")
dataview(imp$featuredata)

#Linear model fit using unadjusted data
factormat<-model.matrix(~gender +Age +bmi, sampledata_eg)
unadjustedFit<-LinearModelFit(featuredata=imp$featuredata,
                             factormat=factormat,
                             ruv2=FALSE)
unadjustedFit

#Linear model fit using `is' normalized data 
Norm_is <-NormQcmets(imp$featuredata, method = "is", 
                    isvec = imp$featuredata[,which(metabolitedata_eg$IS ==1)[1]])
isFit<-LinearModelFit(featuredata=Norm_is$featuredata,
                     factormat=factormat,
                     ruv2=FALSE)
isFit

#Linear model fit with ruv-2 normalization
ruv2Fit<-LinearModelFit(featuredata=imp$featuredata,
                       factormat=factormat,
                       ruv2=TRUE,k=2,
                       qcmets = which(metabolitedata_eg$IS ==1))
ruv2Fit

#Exploring metabolites associated with age
lcoef_age<-list(unadjusted=unadjustedFit$coefficients[,"Age"],
               is_age=isFit$coefficients[,"Age"],
               ruv2_age=ruv2Fit$coefficients[,"Age"])
lpvals_age<-list(unadjusted=unadjustedFit$p.value[,"Age"],
                is=isFit$p.value[,"Age"],
                ruv2=ruv2Fit$p.value[,"Age"])

negcontrols<-metabolitedata_eg$names[which(metabolitedata_eg$IS==1)]                   

CompareVolcanoPlots(lcoef=lcoef_age, 
                   lpvals_age, 
                   xlab="Coef",
                   negcontrol=negcontrols)

# }