#' Get gene names in each clusters and the expression profiling.
#'
#' Get gene names in each clusters and the expression profiling. This output
#' is helpful if user want to analyse the data for other application.
#'
#' @inheritParams enrichment
#' @return a list containing a matrix of cluster_id with expression profiling
#' and label a vector of the sample labels.
#' @rdname geneExpInCluster
#' @export
#' @seealso \code{\link{clEnrich}}
#' @examples
#' data(Psoriasis)
#' annofile <- system.file("extdata", "c2.cp.kegg.v7.01.symbols.gmt.xz",
#' package="cogena")
#'
#' \dontrun{
#' genecl_result <- coExp(DEexprs, nClust=2:3, clMethods=c("hierarchical","kmeans"),
#' metric="correlation", method="complete", ncore=2, verbose=TRUE)
#'
#' clen_res <- clEnrich(genecl_result, annofile=annofile, sampleLabel=sampleLabel)
#'
#' #geneExpInCluster
#' geneExp <- geneExpInCluster(clen_res, "kmeans", "3")
#' }
#'
setGeneric("geneExpInCluster", function(object, method, nCluster)
standardGeneric("geneExpInCluster"))
#' @rdname geneExpInCluster
#' @aliases geneExpInCluster,cogena_methods
setMethod("geneExpInCluster", signature(object="cogena"),
function (object, method=clusterMethods(object),
nCluster=nClusters(object)){
method <- match.arg(method, clusterMethods(object))
nCluster <- match.arg(nCluster, as.character(nClusters(object)))
cluster_id <- geneclusters(object, method,nCluster)
clusterGeneExp <- cbind(cluster_id, object@mat)
clusterGeneExp <- clusterGeneExp[order(clusterGeneExp[,"cluster_id"]),]
label <- object@sampleLabel
list(clusterGeneExp=clusterGeneExp, label=label)
}
)
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