bootstrapAUC: Bootstrap the AUC and conduct T-Tests for a collection of...
In TBSignatureProfiler: Profile RA-Seq Data Using TB Pathway Signatures

Description Usage Arguments Value Examples

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

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

`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`.

A list of length 3 returning a vector of p-values for a 2-sample t-test, bootstrapped AUC values, and an AUC value for using all scored values for all signatures specified in signatureColNames.

 # 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