R/AllClasses.R

In palenic/genePrioritization: Find Potential Disease-Related Genes

#' Class RankedGeneList
#'
#' A S4 class to store results of a genePrioritization analysis.
#' @name RankedGeneList-class
#' @slot results A named vactor of candidate scores sorted according to
#' increasing score
#' @slot seed The seed genes
#' @slot candidates The candidate genes sorted according to
#' increasing score
#' @slot coexpr A named matrix of shape (nCandidates, nSeed) with
#' coexpression values between each seed and each candidate.
#' Rows are sorted according to increasing candidate score.
#' @slot ranks A named matrix of shape (nCandidates, nSeed) with ranks of
#' each candidate in each seed gene coexpression list. Candidates are ranked
#' according to their decreasing coexpression. Rows are sorted according to
#' increasing candidate score
#' @importFrom methods setClass
#' @importFrom methods new
#' @exportClass RankedGeneList
#' @export RankedGeneList
#' @seealso \code{\link{prioritizeCandidates}}\cr
#' @examples
#' a <- matrix(c(1,2,3,2,4,6,8,6,4,5,2,8,7,1,5),
#' nrow=5, ncol=3,byrow=TRUE)
#' colnames(a) <- c('sample1','sample2','sample3')
#' rownames(a) <- c('gene1','gene2','gene3','gene4','gene5')
#' seed <- c('gene1')
#' candidates <- c('gene2','gene4')
#' x <- findCoexpression(counts=a, seedGenes=seed)
#' y <- rankGenes(x)
#' z <- candidateScoring(y, candidates)
#' result <- RankedGeneList(seed=seed, candidates=candidates,
#'                         results=z,
#'                         coexpr=x[candidates,,drop=FALSE],
#'                         ranks=y[candidates,,drop=FALSE])
#'
RankedGeneList<-setClass("RankedGeneList",
                        slots=list(
                        results="numeric",
                        seed="character",
                        candidates="character",
                        coexpr="matrix",
                        ranks="matrix"))