# HG changeset patch
# User proteomisc
# Date 1706520853 0
# Node ID 31f89047724fbdc70613899c63950a2aa6c9c2b6
# Parent  a738f5824d0be4c6c937ef76765f4c3851e7a511
Uploaded

diff -r a738f5824d0b -r 31f89047724f preprocess_datasets/GenePix_Two_Colors_Preprocessing_Functions.R
--- a/preprocess_datasets/GenePix_Two_Colors_Preprocessing_Functions.R	Sat Dec 16 15:58:09 2023 +0000
+++ b/preprocess_datasets/GenePix_Two_Colors_Preprocessing_Functions.R	Mon Jan 29 09:34:13 2024 +0000
@@ -6,11 +6,14 @@
  MA<-MA[rm.na(rownames(MA$M)),]
  RG.pq <<- RG.MA(MA)
  MAb <<-suppressWarnings(suppressMessages(normalizeBetweenArrays(MA, method=methodNBA))) 
- data_mt<-NaRV.omit(as.data.frame(MAb$M))
- MAb$M=(data_mt)
- MAb$A=NaRV.omit(as.data.frame(MAb$A))
- MAb$genes=(MAb$genes[(MAb$genes$ID %in% c(rownames(MAb$A),rownames(MAb$M))),])
- MA.avg <-suppressWarnings(suppressMessages(avereps(MAb)))
+ data_mt <-NaRV.omit(as.data.frame(MAb$M))
+ MAb$M <- data_mt
+ MAb$A <- NaRV.omit(as.data.frame(MAb$A))
+ genesids <- Reduce(intersect, list(rownames(MAb$M),rownames(MAb$A),MAb$genes$ID))
+ MAb$genes <- MAb$genes[MAb$genes$ID %in% genesids,]
+ MAb$M <- MAb$M[rownames(MAb$M) %in% genesids,]
+ MAb$A <- MAb$A[rownames(MAb$A) %in% genesids,]
+ MA.avg <-suppressWarnings(suppressMessages(avereps(MAb, ID=genesids)))
  data_matrix=NaRV.omit(MA.avg$M)
  colnames(data_matrix)<-designo$sample
  write.table(format(data_matrix, justify="right"),sep="\t", quote=FALSE,