####################################
#                                  #
#     Read in probe level          #  
#     192 samples from             #
#     Data Citation 1              #
#     (n = 192, p = 56044)         #
#                                  #
####################################
## File names
# Refer to GEO submission of Data Citation 1 for the raw .txt file file name:
# e.g. US83903565_253118111471_S01_miRNA_107_Sep09_1_1.txt
file.name.list <- c("US83903565_253118111471_S01_miRNA_107_Sep09_1_1.txt", 
                    ...)

## Read the data in ----
# set up the frame
data.array.192 <- vector("list",3)
temp <- read.table(file = file.name.list[1], sep = "\t", header = TRUE, skip = 9)
probe.name.agi <- as.character(temp$ProbeName)
gene.name.agi <- as.character(temp$GeneName)
probe.type.agi <- temp$ControlType
data.array.192[[1]] <- cbind(data.array.192[[1]],temp$gMeanSignal)
data.array.192[[2]] <- cbind(data.array.192[[2]],temp$gBGMeanSignal)
data.array.192[[3]] <- cbind(data.array.192[[3]],temp$gProcessedSignal)

# loop through 192 samples (except the first one)
for (i in 2:192){print(i)
  temp <- read.table(file = file.name.list[i], sep = "\t", header = TRUE, skip = 9)
  data.array.192[[1]] <- cbind(data.array.192[[1]],temp$gMeanSignal)
  data.array.192[[2]] <- cbind(data.array.192[[2]],temp$gBGMeanSignal)
  data.array.192[[3]] <- cbind(data.array.192[[3]],temp$gProcessedSignal)
}
rownames(data.array.192[[1]]) <- 
  rownames(data.array.192[[2]]) <- 
  rownames(data.array.192[[3]]) <- probe.name.agi
colnames(data.array.192[[1]]) <- 
  colnames(data.array.192[[2]]) <- 
  colnames(data.array.192[[3]]) <- sub(" ", ".", list.array$SampleName)
names(data.array.192) <- c("MeanSignal","BGMeanSignal","ProcessedSignal")

# to matrix
array.192.pro <- as.matrix(data.array.192$ProcessedSignal)
array.192.fgd <- as.matrix(data.array.192$MeanSignal)
array.192.bgd <- as.matrix(data.array.192$BGMeanSignal)

## get the original no background adjusted (noba) and background adjusted (ba) 192-sample randomized data ----
temp <- array.192.fgd
temp[temp < 1] <- 1
noba.log2.data.a <- log2(temp)

temp <- array.192.fgd - array.192.bgd
temp[temp < 1] <- 1
ba.log2.data.a <- log2(temp)  

rownames(noba.log2.data.a) <- rownames(ba.log2.data.a) <- probe.name.agi
colnames(noba.log2.data.a) <- colnames(ba.log2.data.a) <- list.array$SampleName

## save noba.log2.data.a (n = 192) ----

# enter path to directory you would like to save the data matrix
path3 <- "path_to_save_data_matrix/"
save(noba.log2.data.a, file = paste0(path3, "/noba.log2.data.a.Rdata"))