plotDistributionModel {pulsedSilac} | R Documentation

## Distribution of modelling output

### 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')

[Package pulsedSilac version 1.0.1 Index]