R/MIGSAres-setEnrCutoff.R

In jcrodriguez1989/MIGSA: Massive and Integrative Gene Set Analysis

#' Set enrichment cutoff for a MIGSAres object
#'
#' \code{setEnrCutoff} sets the enrichment cutoff value for a MIGSAres object in
#' order to get detailed enrichment results.
#'
#' @param object a MIGSAres object.
#' @param newEnrCutoff numeric value in range [0,1] or NA to set the new
#' enrichment cutoff. If NA then enrichment cutoff is unset for object.
#'
#' @return A MIGSAres object with the updated slots.
#'
#' @docType methods
#' @name setEnrCutoff
#' @rdname MIGSAres-setEnrCutoff
#'
#' @include MIGSAres-class.R
#' @exportMethod setEnrCutoff
#'
setGeneric(name = "setEnrCutoff", def = function(object, newEnrCutoff) {
  standardGeneric("setEnrCutoff")
})

#' @rdname MIGSAres-setEnrCutoff
#' @aliases setEnrCutoff,MIGSAres,numeric-method
#' @examples
#' data(migsaRes)
#' ## After executing MIGSA, the MIGSAres object does not have an enrichment
#' ## cutoff set, so it will be shown as follows:
#' head(migsaRes)
#' ## Now lets set an enrichment cutoff, and then show again the object.
#' migsaResWCoff <- setEnrCutoff(migsaRes, 0.01)
#' head(migsaResWCoff)
#' ## So now we can do stuff like check how many gene sets are enriched in both
#' ## experiments, in each one, etc. Moreover now we can do different MIGSAres
#' ## plots available in MIGSA package.
#' table(migsaResWCoff[, c("igsaInput1", "igsaInput2")])
#' ## And with different cutoffs.
#' migsaResWCoff <- setEnrCutoff(migsaRes, 0.1)
#' table(migsaResWCoff[, c("igsaInput1", "igsaInput2")])
setMethod("setEnrCutoff",
  signature = c("MIGSAres", "numeric"),
  definition = function(object, newEnrCutoff) {
    stopifnot(validObject(object))

    res <- object
    enrCutoff(res) <- newEnrCutoff

    return(res)
  }
)