R/old_crossomics.R

In isglobal-brge/omicRexposome: Exposome and omic data associatin and integration analysis

#' #' Function to perform a Transcriptome-Wide Association Study
#' #'
#' #' This function allows to perform a Transcriptome-Wide Association Study
#' #' by using an \code{ExposmeSet} and an \code{ExpressionSet}. It
#' #' allows to perform an adjustment using Surrogate Variable Analysis (from
#' #' R package \code{sva}).
#' #'
#' #' @param list A list containing at last two \code{eSet} based objects
#' #' like \code{ExposomeSet}, \code{ExpressionSet} or \code{MethylationSet}.
#' #' @param method (default \code{"mcca"}) It can takes values \code{"mcca"} for
#' #' Multiple Canonical Correlation Analysis or \code{"mcia"} for Multiple
#' #' Co-Inertia Analysis.
#' #' @param ncomponents (default \code{2}) Number of components to be estimated.
#' #' @param na.rm (default \code{FALSE}) If \code{method} was set to
#' #' \code{"mcca"} and \code{na.rm} was set to \code{TRUE}, features containing
#' #' missing values are removed.
#' #' @param permute (default \code{c(100, 3)}). If \code{method="mcca"} and this
#' #' agument is set to \code{NULL} no permutation test to tune-up the parameters
#' #' for \code{MultiCCA}. When filles, \code{permute[1]} corresponds to
#' #' the number permutations (default in \code{MultiCCa.permute} is \code{25})
#' #' and \code{permute[2]} the number of iterations
#' #' (default in \code{MultiCCA.permute} is 3).
#' #' @param ... Other arguments given to \code{mcia} (from \code{omicade4}) or
#' #' to \code{MultiCCA} (from \code{PMA}).
#' #' @param verbose (default \code{FALSE}) If set to \code{TRUE}, a series of
#' #' messages descriving the process are shown.
#' #' @param warnings (default \code{TRUE}) If set to \code{TRUE}, a series of
#' #' warnings are shown when required user atention.
#' #' @return An object of class \code{\link{ResultSet}}.
#' #' @examples
#' #' data(methy_r)
#' #' data(gexp_r)
#' #' rst <- crossomics(list(methy=methy_r, gexp=gexp_r), permute=NULL)
#' #' rst
#' # @export
#' crossomics2222 <- function(list, method="mcca", ncomponents=2, ..., na.rm=FALSE,
#'         permute = c(100, 3), verbose=FALSE, warnings=TRUE) {
#'     ## --------------------------------------------------------------------- ##
#'     ## GENERAL CHECKS
#'     method <- match.arg(method, choices = c("mcca", "mcia"))
#'     if(length(list) < 2) {
#'         stop("At last two different datasets are required for integration processes.")
#'     }
#'     if(is.null(names(list))) {
#'         names(list) <- paste("set", 1:length(list))
#'     }
#'     ## --------------------------------------------------------------------- ##
#'
#'     ## --------------------------------------------------------------------- ##
#'     ## REDUCE DATASETS TO COMMON SAMPLES
#'     if(warnings | verbose) {
#'         warning("Sets from 'MultiDataSet' will be reduced to common samples")
#'     }
#'
#'     l1 <- vapply(Biobase::sampleNames(object), length, FUN.VALUE = numeric(1))
#'     object <- MultiDataSet::commonSamples(object)
#'     l2 <- sapply(Biobase::sampleNames(object), length)
#'     l3 <- mapply('-', l1, l2, SIMPLIFY = FALSE)
#'
#'     if(verbose) {
#'         message(paste(unlist(l3), names(l3),
#'                       sep = " samples were reduced from ", collapse = ", "))
#'     }
#'     ## --------------------------------------------------------------------- ##
#'
#'
#'     if(method == "mcca") {
#'         .crossomics_mcca_list(list, ncomponents=ncomponents, na.rm=na.rm,
#'             permute=permute, verbose=verbose, warnings=warnings, ...)
#'     } else if(method == "mcia") {
#'         .crossomics_mcia_list(list, verbose=verbose, warnings=warnings, ...)
#'     } else {
#'         stop("Invalid method (", method, ") was given.")
#'     }
#' }