tpptrFTest {TPP} | R Documentation

## Analyze spline fits to detect differential behavior over time

### Description

Analyze fitted natural spline models and look for differential behaviour between conditions by a moderated F-test.

### Usage

    tpptrFTest(fittedModels, doPlot = FALSE, resultPath = NULL)

### Arguments

`fittedModels` | a table of fitted spline models (produced by `tpptrFitSplines`).
`doPlot` | boolean value indicating whether QC plots should be produced. Currently, QC plots comprise distributions of the F statistics, and the p-values before/ after Benjamini Hochberg adjustment.
`resultPath` | location where to store QC plots, if `doPlot` = TRUE.

### Details

If `doPlot` is `TRUE`, but no `resultPath` is specified, the plots will be prompted to the active device.

The moderated F-statistic is calculated by the following equation: ...

### Value

A long table containing the hypothesis test results per protein.

### See Also

`ns, squeezeVar`

### Examples

    data(hdacTR_smallExample)
    tpptrData <- tpptrImport(configTable = hdacTR_config, data = hdacTR_data)
    normResults <- tpptrNormalize(data = tpptrData, normReqs = tpptrDefaultNormReqs())
    normData_eSets <- normResults$normData
    fitData <- tpptrTidyUpESets(normData_eSets)
    fits <- tpptrFitSplines(data = fitData, factorsH1 = "condition", nCores = 1, splineDF = 4:5)
    testResults <- tpptrFTest(fittedModels = fits)

[Package TPP version 3.20.1 Index]