--- a
+++ b/R/cleanMetadata.GSE31312.R
@@ -0,0 +1,68 @@
+#' @rdname cleanMetadata
+#' @details
+#'    GSE31312:\cr
+#'    This function makes the samples GSM776068, GSM776149, and GSM776462 to be
+#'    left out of the downstream preprocessing due to bad array quality.
+#' @export
+cleanMetadata.GSE31312 <- function(meta_data) {
+  message("Cleaning GSE31312 (IDRC)!")
+
+  # Generic clean
+  suppressMessages(meta_data <- cleanMetadata.data.frame(meta_data))
+
+  # Added factor describing the batches and CEL files
+  exclude <- c("GSM776068", "GSM776149", "GSM776462")
+  meta_data$Batch <-
+    factor(ifelse(rownames(meta_data) %in% exclude, NA, "Batch1"))
+  meta_data$CEL <- rownames(meta_data)
+  meta_data$GSM <- as.character(meta_data$geo_accession)
+
+  return(meta_data)
+}
+
+
+# meta_data$Array.Data.File <-
+#   as.character(
+#     meta_data_old[as.character(meta_data$GEO.Depository..31312),
+#                      "Array.Data.File" ])
+#
+# meta_data <- meta_data[!is.na(meta_data$Array.Data.File),]
+#
+# meta_data$WrightClass2 <-
+#   meta_data$GEP.Classification
+# meta_data$WrightClass <- as.character(meta_data$WrightClass2)
+# meta_data$WrightClass <-
+#   as.factor(gsub("UC", "Unclassified", meta_data$WrightClass))
+#
+#   # Creating survival objects
+#
+#   meta_data$OS  <- meta_data$OS  / 12
+#   meta_data$PFS <- meta_data$PFS / 12
+#
+# meta_data$OScensor <- ifelse(meta_data$OScensor == 1, 0, 1)
+# meta_data$PFScensor <- ifelse(meta_data$PFScensor == 1, 0, 1)
+#
+# meta_data$OS<- Surv(as.numeric(meta_data$OS), meta_data$OScensor)
+#
+# os5  <- ifelse(meta_data$OS[,1] > 5, 5, meta_data$OS[,1])
+# ios5 <- pmin(ifelse(meta_data$OS[,1] > 5, 0, 1), meta_data$OS[,2])
+#
+# meta_data$OS5 <- Surv(as.numeric(os5), ios5)
+#
+# meta_data$PFS<- Surv(as.numeric(meta_data$PFS), meta_data$PFScensor)
+#
+# PFS5  <- ifelse(meta_data$PFS[,1] > 5, 5, meta_data$PFS[,1])
+# iPFS5 <- pmin(ifelse(meta_data$PFS[,1] > 5, 0, 1), meta_data$PFS[,2])
+#
+# meta_data$PFS5 <- Surv(as.numeric(PFS5), iPFS5)
+# @
+#
+#   <<>>=
+#   meta_data$ipi.hl <- NA
+# meta_data$ipi.hl[meta_data$IPI.score %in% c(0,1)] <- "0-1"
+# meta_data$ipi.hl[meta_data$IPI.score %in% c(2,3)] <- "2-3"
+# meta_data$ipi.hl[meta_data$IPI.score %in% c(4,5)] <- "4-5"
+# meta_data$ipi.hl <- as.factor(meta_data$ipi.hl)
+# table(meta_data$ipi.hl, meta_data$IPI.score)
+#
+# meta_data$age <- meta_data$Age