CompareVolcanoPlots: Compare Volcano plots

In NormalizeMets: Analysis of Metabolomics Data

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

Author(s)

Alysha M De Livera, Gavriel Olshansky

See Also

VolcanoPlot

Examples

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)

NormalizeMets documentation built on May 1, 2019, 10:26 p.m.