maVolPlot {qPLEXanalyzer} | R Documentation

## MA or Volcano Plot

### Description

MA or Volcano plot of differential statistics results

### Usage

    maVolPlot(
      diffstats,
      contrast,
      title = "",
      controlGroup = NULL,
      selectedGenes = NULL,
      fdrCutOff = 0.05,
      lfcCutOff = 1,
      controlLfcCutOff = 1,
      plotType = "MA"
    )

### Arguments

`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"

### Details

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 labeled with the contents of the `GeneSymbol` column. Note that if the `GeneSymbol` for a selected gene is missing, no label will be apparent.

### Value

An object created by `ggplot`

### Examples

    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")

[Package qPLEXanalyzer version 1.10.0 Index]