#' Download and process all curated DLBCL datasets
#'
#' Automatically download and process all support curated DLBCL datasets.
#' Simply loops over all datasets in \code{data(dlbcl_overview)}.
#'
#' @param \dots Arguments passed to \code{\link{downloadAndProcessGEO}}.
#' @return Saves a \code{list} of the processed datasets in the working
#' directory named "dlbcl_data.Rds".
#' Invisibly returns a \code{list} of the output of
#' \code{\link{downloadAndProcessGEO}}.
#' @author
#' Anders Ellern Bilgrau\cr
#' Steffen Falgreen Larsen
#' @examples
#' listTargets("brainarray")
#' \dontrun{
#' # Warning, very long processing times if data is not downloaded.
#'
#' # Preprocess with brainarray "Entrez" gene ids
#' res <- downloadAndProcessDLBCL(cdf = "brainarray", target = "ENTREZG",
#' clean = FALSE)
#'
#' # Preprocess with brainarray "Ensembl" gene ids
#' res2 <- downloadAndProcessDLBCL(cdf = "brainarray", target = "ENSG",
#' clean = TRUE)
#'
#' # Preprocess with affy's probesets
#' res3 <- downloadAndProcessDLBCL() #= downloadAndProcessDLBCL(cdf = "affy")
#' }
#' @export
downloadAndProcessDLBCL <- function(...) {
st <- proc.time()
message("\nDownloading and processing all DLBCL datasets\n")
res <- list()
for (i in 1:nrow(DLBCLdata::DLBCL_overview)) {
geo_nbr <- as.character(DLBCLdata::DLBCL_overview$GSE[i])
stdy <- as.character(DLBCLdata::DLBCL_overview$Study[i])
message(sprintf("\n\n\n\n #### %s (%s) ####\n\n\n", geo_nbr, stdy))
t <- system.time({
res[[i]] <- downloadAndProcessGEO(geo_nbr = geo_nbr, ...)
})
message(sprintf("\n %s finished successfully in %s minutes.\n",
geo_nbr, t[3] %/% 60))
}
names(res) <- as.character(DLBCLdata::DLBCL_overview$GSE)
message("Saving all processed DLBCL data")
saveRDS(res, file = file.path(getwd(), "dlbcl_data.Rds"))
message("\nFinished in ", (proc.time()-st)[3] %/% 60, " minutes.\n")
return(invisible(res))
}
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