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#' Subset Pathway-Specific Data
#'
#' @description Given an \code{Omics} object and the name of a pathway, return
#' the -omes in the assay and the response as a (tibble) data frame.
#'
#' @param object An object of class \code{OmicsPathway}, or an object extending
#' this class.
#' @param pathName The name of a pathway contained in the pathway collection in
#' the object.
#' @param ... Dots for additional internal arguments (currently unused).
#'
#' @return A data frame of the columns of the assay in the \code{Omics} object
#' which are listed in the specified pathway, with a leading column for
#' sample IDs. If the \code{Omics} object has response information, these
#' are also included as the first column(s) of the data frame, after the
#' sample IDs. If you have the suggested \code{tidyverse} package suite
#' loaded, then this data frame will print as a \code{\link[tibble]{tibble}}.
#' Otherwise, it will print as a data frame.
#'
#'
#' @details This function subsets the assay by the matching gene symbols or IDs
#' in the specified pathway.
#'
#' @include createClass_validOmics.R
#' @include createClass_OmicsPath.R
#' @include createClass_OmicsSurv.R
#' @include createClass_OmicsReg.R
#' @include createClass_OmicsCateg.R
#' @include accessClass_OmicsPath.R
#' @include accessClass_OmicsRegCateg.R
#' @include accessClass_OmicsSurv.R
#'
#' @importFrom methods setGeneric
#'
#' @export
#'
#' @examples
#' data("colonSurv_df")
#' data("colon_pathwayCollection")
#'
#' colon_Omics <- CreateOmics(
#' assayData_df = colonSurv_df[, -(2:3)],
#' pathwayCollection_ls = colon_pathwayCollection,
#' response = colonSurv_df[, 1:3],
#' respType = "survival"
#' )
#'
#' SubsetPathwayData(
#' colon_Omics,
#' "KEGG_RETINOL_METABOLISM"
#' )
#'
#'
#' @rdname SubsetPathwayData
setGeneric("SubsetPathwayData",
function(object, pathName, ...){
standardGeneric("SubsetPathwayData")
})
#' @rdname SubsetPathwayData
setMethod(f = "SubsetPathwayData", signature = "OmicsPathway",
definition = function(object, pathName, ...){
### The Design Matrix ###
path_ls <- getTrimPathwayCollection(object)[[pathName]]
genes_char <- path_ls$IDs
design_df <- getAssay(object)[, genes_char]
sampleIDs <- getSampleIDs(object)
### The Response Vectors ###
obj_class <- class(object)
switch(obj_class,
OmicsPathway = {
out_df <- data.frame(
sampleID = sampleIDs,
design_df,
stringsAsFactors = FALSE
)
},
OmicsSurv = {
out_df <- data.frame(
sampleID = sampleIDs,
EventTime = getEventTime(object),
EventObs = getEvent(object),
design_df,
stringsAsFactors = FALSE
)
},
OmicsReg = {
out_df <- data.frame(
sampleID = sampleIDs,
Response = getResponse(object),
design_df,
stringsAsFactors = FALSE
)
},
OmicsCateg = {
out_df <- data.frame(
sampleID = sampleIDs,
Response = getResponse(object),
design_df,
stringsAsFactors = FALSE
)
}
)
### Return ###
class(out_df) <- c("tbl_df", "tbl", "data.frame")
out_df
})
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