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#' CIMLR_Estimate_Number_of_Clusters
#'
#' @title This function has been removed and it is now provided
#' by the CIMLR package, please refer to https://github.com/danro9685/CIMLR
#'
#' @examples
#' \dontrun{
#' CIMLR_Estimate_Number_of_Clusters(GliomasReduced$in_X,
#' NUMC = 2:5,
#' cores.ratio = 0)
#' }
#' @param all_data is a list of multi-omic data each of which is an (m x n) data matrix of measurements of cancer patients
#' @param NUMC vector of number of clusters to be considered
#' @param cores.ratio ratio of the number of cores to be used when computing the multi-kernel
#'
#' @export CIMLR_Estimate_Number_of_Clusters
#' @return a list of 2 elements: K1 and K2 with an estimation of the best clusters (the lower
#' values the better) as discussed in the original paper of SIMLR
#'
"CIMLR_Estimate_Number_of_Clusters" = function(
all_data,
NUMC = 2:5,
cores.ratio = 1) {
.Defunct("CIMLR_Estimate_Number_of_Clusters", package = "CIMLR",
msg = "This function has been removed and it is now provided by the CIMLR package, please refer to https://github.com/danro9685/CIMLR")
}
#' perform the CIMLR clustering algorithm
#'
#' @title This function has been removed and it is now provided
#' by the CIMLR package, please refer to https://github.com/danro9685/CIMLR
#'
#' @examples
#' \dontrun{
#' CIMLR(X = GliomasReduced$in_X, c = 3, cores.ratio = 0)
#' }
#' @param X a list of multi-omic data each of which is an (m x n) data matrix of measurements of cancer patients
#' @param c number of clusters to be estimated over X
#' @param no.dim number of dimensions
#' @param k tuning parameter
#' @param cores.ratio ratio of the number of cores to be used when computing the multi-kernel
#'
#' @return clusters the patients based on CIMLR and their similarities
#' @export CIMLR
#'
"CIMLR" <- function( X, c, no.dim = NA, k = 10, cores.ratio = 1 ) {
.Defunct("CIMLR", package = "CIMLR",
msg = "This function has been removed and it is now provided by the CIMLR package, please refer to https://github.com/danro9685/CIMLR")
}
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