rliPlot | R Documentation |
Relative log intensity (RLI) plots of the samples within MSnset
rliPlot(
MSnSetObj,
title = "",
sampleColours = NULL,
colourBy = "SampleGroup",
omitIgG = TRUE
)
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 |
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.
An object created by ggplot
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
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)
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