barPlotModelComparison,ClinicalModel,PCOSP_or_RLS_or_RGA-method {PDATK} | R Documentation

## Make a Bar Plot Comparison Model Performance Between a ClinicalModel and a PCOSP, RLSModel or RGAModel object.

### Description

Make a Bar Plot Comparison Model Performance Between a ClinicalModel and a PCOSP, RLSModel or RGAModel object.

### Usage

    ## S4 method for signature 'ClinicalModel,PCOSP_or_RLS_or_RGA'
    barPlotModelComparison(model1, model2, stat, ...)

### Arguments

`model1` | A `ClinicalModel` object.
`model2` | A `PCOSP` or `RLSModel` or `RGAModel` object.
`stat` | A `character` vector specifying which statistic to compare the models using. Options are 'AUC', 'log_D_index' or 'concordance_index'.
`...` | Not used.

### Value

A `ggplot2` object showing a barplot coloured by the model and comparing the stat between all cohorts that both models were validated with.

### Examples

    data(sampleValPCOSPmodel)
    data(sampleCohortList)
    data(sampleICGCmicro)

    # Set parallelization settings
    BiocParallel::register(BiocParallel::SerialParam())

    # Setup the models
    clinicalModel <- ClinicalModel(sampleICGCmicro,
      formula='prognosis ~ sex + age + T + N + M + grade',
      randomSeed=1987)

    # Train the models
    trainedClinicalModel <- trainModel(clinicalModel)

    # Make predctions
    clinicalPredCohortList <- predictClasses(sampleCohortList[c('PCSI', 'TCGA')],
      model=trainedClinicalModel)

    # Validate the models
    validatedClinicalModel <- validateModel(trainedClinicalModel,
      valData=clinicalPredCohortList)

    # Plot the comparison
    modelCompBarPlot <- barPlotModelComparison(validatedClinicalModel,
     sampleValPCOSPmodel, stat='AUC')

[Package PDATK version 1.2.0 Index]