#' Utility for using voom transformation with TMLE for biomarker discovery

#'

#' This function prepares next-generation sequencing data (counts) for use with

#' the biomarker TMLE procedure by invoking the voom transform of \code{limma}.

#'

#' @param biotmle A \code{bioTMLE} object containing next-generation sequencing

#'  count data in its "assays" slot.

#' @param weights A \code{logical} indicating whether to return quality weights

#'  of samples in the output object.

#' @param ... Other arguments to be passed to \code{\link[limma]{voom}} or

#'  \code{\link[limma]{voomWithQualityWeights}} as appropriate.

#'

#' @importFrom tibble as_tibble

#' @importFrom limma voom voomWithQualityWeights

#' @importFrom SummarizedExperiment assay

#' @importFrom assertthat assert_that

#' @importFrom methods is

#'

#' @export rnaseq_ic

#'

#' @return \code{EList} object containing voom-transformed expression measures

#'  of count data (actually, the mean-variance trend) in the "E" slot, to be

#'  passed into the biomarker TMLE procedure.

rnaseq_ic <- function(biotmle, weights = TRUE, ...) {

  # check arguments

  assertthat::assert_that(is(biotmle, "bioTMLE"))

  assertthat::assert_that(is.logical(weights))

  # extract count data from appropriate slot of SummarizedExperiment object

  ngs_data <- tibble::as_tibble(assay(biotmle))

  # invoke the "voom" transform from LIMMA

  if (weights) {

    voom_data <- limma::voomWithQualityWeights(ngs_data,

      normalize.method = "scale",

      ...

    )

  } else {

    voom_data <- limma::voom(ngs_data,

      normalize.method = "scale",

      ...

    )

  }

  return(voom_data)

}