plotIndividualModel: Fitted model(s) for a feature

In marcpaga/pulsedSilac: Analysis of pulsed-SILAC quantitative proteomics data

Description

Plot the model fit for a specific protein/peptide in different conditions.

Usage

plotIndividualModel(x, ...)

## S4 method for signature 'SilacProteinExperiment'
plotIndividualModel(x, modelList, num, returnDataFrame = FALSE)

## S4 method for signature 'SilacPeptideExperiment'
plotIndividualModel(x, modelList, num, returnDataFrame = FALSE)

## S4 method for signature 'SilacProteomicsExperiment'
plotIndividualModel(x, modelList, num, returnDataFrame = FALSE)

Arguments

x	A SilacProteinExperiment, SilacPeptideExperiment or SilacProteomicsExperiment object.
...	Unused.
modelList	A list containing all the model objects, this should be the output of modelTurnover with returnModel as TRUE.
num	The feature number to be plotted.
returnDataFrame	A logical indicating if the data.frame used for the plot should be returned instead.

Value

A scatter plot with a fitted line or a data.frame.

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)

plotIndividualModel(x = wormsPE,
                    modelList = modelList,
                    num = 2)

marcpaga/pulsedSilac documentation built on March 11, 2020, 8:49 p.m.