rliPlot {qPLEXanalyzer} | R Documentation

## RLI plot

### Description

Relative log intensity (RLI) plots of the samples within MSnset

### Usage

    rliPlot(MSnSetObj, title="", sampleColours=NULL, colourBy="SampleGroup", omitIgG=TRUE)

### Arguments

`MSnSetObj` | MSnSet; an object of class MSnSet
`title` | character: title for the plot
`sampleColours` | character: a named vector of colours for samples
`colourBy` | character: column name to use for colouring samples from pData(MSnSetObj)
`omitIgG` | logical: whether to remove IgG from the RLI plot

### Details

An RLI-plot is a boxplot that can be used to visualise unwanted variation in a data set. It is similar to the relative log expression plot developed for microarray analysis - see Gandolfo and Speed (2018). Rather than examining gene expression, the RLI plot uses the MS intensities for each peptide or the summarised protein intensities.

The column provided to the "colourBy" argument will be used to colour the samples. The colours will be determined using the function assignColours, alternatively the user may specify a named vector of colours using the "sampleColours" argument. The names of the "sampleColours" vector should match the unique values in the colourBy column.

### Value

An instance of class "MSnSet".

### References

Gandolfo LC, Speed TP (2018) RLE plots: Visualizing unwanted variation in high dimensional data. PLoS ONE 13(2): e0191629. https://doi.org/10.1371/journal.pone.0191629

### 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)
    rliPlot(MSnSet_data, title = "qPLEX_RIME_ER")

    # custom colours
    customCols <- rainbow(length(unique(pData(MSnSet_data)$SampleGroup)))
    names(customCols) <- unique(pData(MSnSet_data)$SampleGroup)
    rliPlot(MSnSet_data, title = "qPLEX_RIME_ER", sampleColours = customCols)

[Package qPLEXanalyzer version 1.4.0 Index]