plotDistributionModel: Distribution of modelling output

In pulsedSilac: Analysis of pulsed-SILAC quantitative proteomics data

Description

Plot the distribution of the different model parameters and metrics for each condition.

Usage

plotDistributionModel(
  modelList,
  value = "param_values",
  plotType = "density",
  returnDataFrame = FALSE
)

Arguments

modelList	A list containing all the model objects, this should be the output of modelTurnover.
value	A character indicating which metric to plot. Check names(modelList) for available options. (Default = 'param_values')
plotType	A character indicating which geometry to plot: 'boxplot' or 'density'. (default = 'density')
returnDataFrame	A logical indicating if the data.frame used for the plot should be returned instead.

Value

A ggplot density or boxplot object, or the data.frame used to make the plot.

Examples

data('wormsPE')
wormsPE <- calculateIsotopeFraction(wormsPE, ratioAssay = 'ratio')

modelList <- modelTurnover(x = wormsPE[1:10],
                           assayName = 'fraction',
                           formula = 'fraction ~ 1 - exp(-k*t)',
                           start = list(k = 0.02),
                           mode = 'protein',
                           robust = FALSE,
                           returnModel = TRUE)

plotDistributionModel(modelList = modelList,
                      value = 'param_values',
                      plotType = 'density')

pulsedSilac documentation built on Nov. 8, 2020, 5:13 p.m.