R/IGSAinput-getDEGenes.R

In MIGSA: Massive and Integrative Gene Set Analysis

#' Calculate differentialy expressed genes of an IGSAinput object
#'
#' \code{getDEGenes} calculates the differentialy expressed genes of an
#' IGSAinput object using the expression matrix, the FitOtions and the
#' SEAparams..
#'
#' @param igsaInput a valid IGSAinput object.
#'
#' @return A IGSAinput object with the updated slots and DE genes calculated.
#'
#' @docType methods
#' @name getDEGenes
#' @rdname IGSAinput-getDEGenes
#' @seealso \code{\link{IGSAinput-class}}
#'
#' @include IGSAinput-class.R
#' @include IGSAinput.R
#' @include SEAparams.R
#' @exportMethod getDEGenes
#'
setGeneric(name = "getDEGenes", def = function(igsaInput) {
  standardGeneric("getDEGenes")
})

#' @rdname IGSAinput-getDEGenes
#' @aliases getDEGenes,IGSAinput
#' @examples
#' ## Lets create a basic IGSAinput object.
#' ## First create a expression matrix.
#' maData <- matrix(rnorm(10000), ncol = 4)
#' rownames(maData) <- 1:nrow(maData)
#' # It must have rownames (gene names).
#' maExprData <- new("MAList", list(M = maData))
#' ## Now lets create the FitOptions object.
#' myFOpts <- FitOptions(c("Cond1", "Cond1", "Cond2", "Cond2"))
#' ## Lets create our IGSAinput object.
#' myIgsaInput <- IGSAinput(
#'   name = "myIgsaInput", expr_data = maExprData,
#'   fit_options = myFOpts
#' )
#' ## And check how many differentialy expressed genes does it get with actual
#' ## parameters.
#' aux <- getDEGenes(myIgsaInput)
setMethod(
  f = "getDEGenes",
  signature = c("IGSAinput"),
  definition = function(igsaInput) {
    validObject(igsaInput)
    sea_par <- igsaInput@sea_params

    if (is.null(sea_par)) {
      return(sea_par)
    }

    # get differentialy expressed genes
    dif <- igsaGetDEGenes(
      sea_par, igsaInput@expr_data,
      igsaInput@fit_options
    )

    # update sea_par with this dif genes, so we dont need to recalculate
    de_genes(sea_par) <- dif
    igsaInput@sea_params <- sea_par

    return(igsaInput)
  }
)