bootstrapAUC {TBSignatureProfiler} | R Documentation

## Bootstrap the AUC and conduct T-Tests for a collection of signatures.

### Description

Run bootstrapping of the AUC and derive the p-value for a 2-sample t-test for all signatures tested on a given dataset.

### Usage

    bootstrapAUC(
      SE_scored,
      annotationColName,
      signatureColNames,
      num.boot = 100,
      pb.show = TRUE
    )

### Arguments

`SE_scored` | a `SummarizedExperiment` object with genes as the row features and signature scores in the `colData`. There should also be a column of annotation data. Required.
`annotationColName` | a character string giving the column name in `colData` that contains the annotation data. Required.
`signatureColNames` | a vector of column names in the `colData` that contain the signature score data. Required.
`num.boot` | integer. The number of times to bootstrap the data. The default is `100`.
`pb.show` | logical for whether to show a progress bar while running code. The default is `TRUE`.

### Value

A list of length 5 returning a vector of p-values for a 2-sample t-test, bootstrapped AUC values, an AUC value for using all scored values for all signatures specified in `signatureColNames`, and values for the lower and upper bounds of a bootstrapped AUC confidence interval using `pROC::roc()`.

### Examples

     # Run signature profiling
     choose_sigs <- TBsignatures[1]
     prof_indian <- runTBsigProfiler(TB_indian, useAssay = "logcounts",
                                     algorithm = "ssGSEA",
                                     combineSigAndAlgorithm = TRUE,
                                     signatures = choose_sigs,
                                     parallel.sz = 1)
     # Bootstrapping
     booted <- bootstrapAUC(SE_scored = prof_indian, annotationColName = "label",
                            signatureColNames = names(choose_sigs), num.boot = 5)
     booted

[Package TBSignatureProfiler version 1.4.11 Index]