R/mbqnNRI.R

In arianeschad/mbqn: Mean/Median-balanced quantile normalization

#' Selective mean/median-balanced quantile normalization
#'
#' @description Quantile normalization of a data matrix where rank
#' invariant (RI)/nearly rank invariant (NRI) rows/features or other
#' user-selected rows are normalized by the mean/median-balanced quantile
#' normalization.
#' @inheritParams mbqn
#' @inheritParams mbqnGetNRIfeatures
#' @param index an integer or a vector integers specifying the indices of
#' selected rows.
#' @details Selected rows and/or rows with rank invariance frequency
#' \code{>=threshold} are normalized with the mean/median-balanced quantile
#' normalization. Remaining rows are quantile normalized without mean balancing.
#' @return Normalized \code{matrix}.
#' @seealso [mbqn()], [mbqnGetNRIfeatures()].
#' @references Brombacher, E., Schad, A., Kreutz, C. (2020). Tail-Robust 
#' Quantile Normalization. BioRxiv.
#' @examples ## Quantile normalize a data matrix where
#' ## nearly rank invariant (NRI) features are balanced
#' X <- matrix(c(5,2,3,NA,4,1,4,2,3,4,6,NA,1,3,1),ncol=3)
#' mbqnNRI(X, median,low_thr = 0.5) # Balance NRI features selected by threshold
#' mbqnNRI(X, median, index = c(1,2)) # Balance selected features
#' @author Ariane Schad
#' @export mbqnNRI
# Created: Nov 2018

mbqnNRI <- function(
    x, FUN = "mean", na.rm = TRUE, method = NULL, low_thr = 0.5 ,
    index = NULL,  offsetmatrix = FALSE, verbose = TRUE){

    if(is.null(index)){
        if (!is.numeric(low_thr) || low_thr >1)
            { stop("Wrong data format, low_thr must be a value within [0 1]!")}

        res  <- mbqnGetNRIfeatures(x,
                                method = method,
                                low_thr = low_thr,
                                verbose = verbose)
        index <- as.numeric(names(res$nri))
    }
    x.mbqn <- mbqn(
        x = x, FUN = FUN,na.rm = na.rm, method = method, 
        verbose = verbose, offsetmatrix = offsetmatrix)
    x.qn <- mbqn(
        x = x, FUN = NULL ,na.rm = na.rm, method = method, 
        verbose = verbose, offsetmatrix = offsetmatrix)
    if(length(index)>0) x.qn[index,] <- x.mbqn[index,]
    return(x.qn)
}