tpp2dCreateDRplots: Create dose response curve plots for 2D-TPP data
In TPP: Analyze thermal proteome profiling (TPP) experiments

Description Usage Arguments Details Value See Also Examples

Generates a list of dose response curve plots per protein and temperature point.

tpp2dCreateDRplots(
  data = NULL,
  type = "all",
  verbose = FALSE,
  paletteName = "Spectral"
)

`data`	the data that should be plotted.
`type`	string defining which curves to display (see details).
`verbose`	boolean variable stating whether a print description of problems/success for plotting of each protein should be printed.
`paletteName`	color palette (see details).

data is a data frame in wide table format returned by function tpp2dCurveFit. Its attributes contain information about the experiment names, temperatures, isobaric labels, as well as instructions on how to find the relevant columns in the wide table.

type defines which curves to display per plot. Possible values are:

"all": Create one plot per protein. This plot simultaneously displays the curves for all available temperatures for this protein (the default).
"good": Create one plot per protein. This plot displays all dose response curves with a high goodness-of-fit. Choose this option to save runtime by focusing only on the reliable fits.
"single": Create one separate plot per protein and temperature. This plot displays all dose response curves with a high goodness-of-fit.

paletteName specifies the color palette to be used by the brewer.pal function from the RColorBrewer package to assign a separate color to each concentration.

A list of successfully generated plot objects of class 'ggplot'

tpp2dCurveFit brewer.pal

data(panobinostat_2DTPP_smallExample)

# Import data:
datIn <- tpp2dImport(configTable = panobinostat_2DTPP_config,
                      data = panobinostat_2DTPP_data,
                      idVar = "representative",
                      addCol = "clustername",
                      intensityStr = "sumionarea_protein_",
                      nonZeroCols = "qusm")

# Compute fold changes:
fcData2d <- tpp2dComputeFoldChanges(data = datIn)
normData2d <- tpp2dNormalize(data = fcData2d)
ccr2dResults <- tpp2dCurveFit(data = normData2d)
allCurves <- tpp2dCreateDRplots(data = ccr2dResults, type = "all")
allCurves[["HDAC1"]]