maVolPlot {qPLEXanalyzer} | R Documentation |
MA or Volcano plot of differential statistics results
maVolPlot(diffstats, contrast, title="", controlGroup = NULL, selectedGenes=NULL, fdrCutOff=0.05, lfcCutOff=1, controlLfcCutOff=1, plotType="MA")
diffstats |
list; output of computeDiffStats function |
contrast |
character; contrast of interest to plot differential statistics results |
title |
character: title for the plot |
controlGroup |
character; control group such as IgG |
selectedGenes |
character: a vector defining genes to plot |
fdrCutOff |
numeric: False Discovery Rate (adj.P.Val) cut off |
lfcCutOff |
numeric: Log Fold Change (log2FC) cutoff for |
controlLfcCutOff |
numeric: only plot genes above controlLogFoldChange cutoff |
plotType |
character: which type of plot to generate: "MA" or "Volcano" |
Genes determined as significant according to the Log Fold Change and False Discovery Rate cutoffs are highlighted in red.
A user specified selection of genes can be highlighted by passing a character vector of Accessions to the selectedGenes argument. The contents of this vector will be matched with the Accessions column of the diffstats object to identify rows to highlight. These will be plotted in blue and labelled with the contents of the GeneSymbol column. Note that if the GeneSymbol for a selected gene is missing, no label will be apparent.
A "MA" or "Volcano" plot to visualize differential statistics results.
data(human_anno) data(exp3_OHT_ESR1) MSnSet_data <- convertToMSnset(exp3_OHT_ESR1$intensities_qPLEX1, metadata=exp3_OHT_ESR1$metadata_qPLEX1, indExpData=c(7:16), Sequences=2, Accessions=6) MSnset_norm <- groupScaling(MSnSet_data, scalingFunction=median) MSnset_Pnorm <- summarizeIntensities(MSnset_norm, sum, human_anno) contrasts <- c(tam.24h_vs_vehicle = "tam.24h - vehicle") diffstats <- computeDiffStats(MSnset_Pnorm, contrasts=contrasts) maVolPlot(diffstats, contrast = contrasts, plotType="MA") maVolPlot(diffstats, contrast = contrasts, plotType="Volcano")