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epimutationNormalize.R
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epimutationNormalize.R
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epimut_normalize_champ <- function(sampleFolder, resultFolder, methodNormalization, useMvalue = FALSE)
{
# if(endsWith(sampleFolder, suffix ="/"))
# {
# message("Sample folder must not end with slash!")
# return()
# }
if (.Platform$OS.type == "windows") withAutoprint({
memory.size()
memory.size(TRUE)
memory.limit(16000)
})
start.time <- Sys.time()
#IMPORTAZIONE DATI
library(parallel)
library(foreach)
library(doParallel)
library(gtools)
# library(parallel)
library(ChAMP)
message("Normalizationwarm up ", Sys.time())
loadMethod <- if ( methodNormalization=="SWAN") {"minfi"} else {"ChAMP"}
dataToNormalize <- champ.load(directory = sampleFolder, method = loadMethod)
normalizationDataFolder <- resultFolder
if (normalizationDataFolder != "" && !dir.exists(normalizationDataFolder)) {
dir.create(normalizationDataFolder)
}
# browser()
#NORMALIZZAZIONE
message("Starting normalization ", Sys.time())
normalizedData <- champ.norm(
beta = dataToNormalize$beta,
rgSet = dataToNormalize$rgSet,
mset = dataToNormalize$mset,
resultsDir = paste(normalizationDataFolder, "/CHAMP_Normalization_by_", methodNormalization , "/", sep = ""),
method = methodNormalization,
plotBMIQ = FALSE,
#arraytype = "450K",
cores = min(detectCores(all.tests = FALSE, logical = TRUE) - 1,8)
# set.seed(seed = 200)
#detectCores(all.tests = FALSE, logical = TRUE) -1
)
if (any(is.na(normalizedData)))
stop("Normalized data Produced with NaN values ", Sys.time())
message( "Data normalized ",Sys.time())
probesNameNormalizedData <- row.names(normalizedData)
probeFeaturesValue <- data.frame(probe.features)
probeFeaturesName <- row.names(probeFeaturesValue)
probeToDiscard <- setdiff(probeFeaturesName, probesNameNormalizedData)
probeFeaturesValue <- probeFeaturesValue[!row.names(probeFeaturesValue) %in% probeToDiscard,]
probeFeaturesValue <- data.frame("Probe" = row.names(probeFeaturesValue), probeFeaturesValue)
probeFeaturesValue$CHR <- droplevels(probeFeaturesValue$CHR)
probeFeaturesValue <- probeFeaturesValue[
order(probeFeaturesValue[, "Probe"], decreasing = FALSE),
]
names(probeFeaturesValue)[names(probeFeaturesValue) == "MAPINFO"] <- "START"
normalizedData <- normalizedData[
order(row.names(normalizedData), decreasing = FALSE),
]
if(!test_match_order(row.names(normalizedData), row.names(probeFeaturesValue)))
stop("Wrong order matching Probes and Mutation!", Sys.time())
if(!test_match_order(row.names(normalizedData), probeFeaturesValue$Probe))
stop("Wrong order matching Probes and Mutation!", Sys.time())
if (useMvalue)
{
normalizedData <- log2(normalizedData/(1-normalizedData))
}
#browser()
normalizedData <- data.frame(row.names = row.names(probeFeaturesValue), normalizedData)
write.table(normalizedData, paste(normalizationDataFolder, "/CHAMP_Normalization_by_", methodNormalization , "/", "Normalized_Data.txt", sep = ""), sep = "\t", row.names = TRUE)
#browser()
sampleSheet <- if (methodNormalization=="SWAN") {data.frame(dataToNormalize$pd@listData)} else { dataToNormalize$pd }
result <- list(probeFeatures = probeFeaturesValue, sampleSheet = sampleSheet, normalizedData = normalizedData)
end.time <- Sys.time()
time.taken <- end.time - start.time
message("Time to normalize ", time.taken)
return(result)
}
epimut_normalize_rnbeads <- function(sampleFolder, resultFolder, methodNormalization)
{
# if(endsWith(sampleFolder, suffix ="/"))
# {
# message("Sample folder must not end with slash!")
# return()
# }
if (.Platform$OS.type == "windows") withAutoprint({
memory.size()
memory.size(TRUE)
memory.limit(16000)
})
start.time <- Sys.time()
#IMPORTAZIONE DATI
library(parallel)
library(foreach)
library(doParallel)
library(gtools)
# library(parallel)
library(ChAMP)
message("Normalizationwarm up ", Sys.time())
loadMethod <- if ( methodNormalization=="SWAN") {"minfi"} else {"ChAMP"}
dataToNormalize <- champ.load(directory = sampleFolder, method = loadMethod)
normalizationDataFolder <- sampleFolder
if (normalizationDataFolder != "" && !dir.exists(normalizationDataFolder)) {
dir.create(normalizationDataFolder)
}
# browser()
#NORMALIZZAZIONE
message("Starting normalization ", Sys.time())
normalizedData <- champ.norm(
beta = dataToNormalize$beta,
rgSet = dataToNormalize$rgSet,
mset = dataToNormalize$mset,
resultsDir = paste(normalizationDataFolder, "/CHAMP_Normalization_by_", methodNormalization , "/", sep = ""),
method = methodNormalization,
plotBMIQ = FALSE,
#arraytype = "450K",
cores = min(detectCores(all.tests = FALSE, logical = TRUE) - 1,8)
# set.seed(seed = 200)
#detectCores(all.tests = FALSE, logical = TRUE) -1
)
if (any(is.na(normalizedData)))
stop("Normalized data Produced with NaN values ", Sys.time())
message( "Data normalized ",Sys.time())
probesNameNormalizedData <- row.names(normalizedData)
probeFeaturesValue <- data.frame(probe.features)
probeFeaturesName <- row.names(probeFeaturesValue)
probeToDiscard <- setdiff(probeFeaturesName, probesNameNormalizedData)
probeFeaturesValue <- probeFeaturesValue[!row.names(probeFeaturesValue) %in% probeToDiscard,]
probeFeaturesValue <- data.frame("Probe" = row.names(probeFeaturesValue), probeFeaturesValue)
probeFeaturesValue$CHR <- droplevels(probeFeaturesValue$CHR)
probeFeaturesValue <- probeFeaturesValue[
order(probeFeaturesValue[, "Probe"], decreasing = FALSE),
]
names(probeFeaturesValue)[names(probeFeaturesValue) == "MAPINFO"] <- "START"
normalizedData <- normalizedData[
order(row.names(normalizedData), decreasing = FALSE),
]
if(!test_match_order(row.names(normalizedData), row.names(probeFeaturesValue)))
stop("Wrong order matching Probes and Mutation!", Sys.time())
if(!test_match_order(row.names(normalizedData), probeFeaturesValue$Probe))
stop("Wrong order matching Probes and Mutation!", Sys.time())
#browser()
normalizedData <- data.frame(row.names = row.names(probeFeaturesValue), normalizedData)
write.table(normalizedData, paste(normalizationDataFolder, "/CHAMP_Normalization_by_", methodNormalization , "/", "Normalized_Data.txt", sep = ""), sep = "\t", row.names = TRUE)
###################
# browser()
#NORMALIZZAZIONE
message("Starting normalization ", Sys.time())
normalizedData2 <- champ.norm(
beta = dataToNormalize$beta,
rgSet = dataToNormalize$rgSet,
mset = dataToNormalize$mset,
resultsDir = paste(normalizationDataFolder, "/CHAMP_Normalization_by_", methodNormalization , "/", sep = ""),
method = methodNormalization,
plotBMIQ = FALSE,
#arraytype = "450K",
cores = min(detectCores(all.tests = FALSE, logical = TRUE) - 1,8)
# set.seed(seed = 200)
#detectCores(all.tests = FALSE, logical = TRUE) -1
)
if (any(is.na(normalizedData2)))
stop("Normalized data Produced with NaN values ", Sys.time())
message( "Data normalized ",Sys.time())
probesNamenormalizedData2 <- row.names(normalizedData2)
probeFeaturesValue <- data.frame(probe.features)
probeFeaturesName <- row.names(probeFeaturesValue)
probeToDiscard <- setdiff(probeFeaturesName, probesNamenormalizedData2)
probeFeaturesValue <- probeFeaturesValue[!row.names(probeFeaturesValue) %in% probeToDiscard,]
probeFeaturesValue <- data.frame("Probe" = row.names(probeFeaturesValue), probeFeaturesValue)
probeFeaturesValue$CHR <- droplevels(probeFeaturesValue$CHR)
probeFeaturesValue <- probeFeaturesValue[
order(probeFeaturesValue[, "Probe"], decreasing = FALSE),
]
names(probeFeaturesValue)[names(probeFeaturesValue) == "MAPINFO"] <- "START"
normalizedData2 <- normalizedData2[
order(row.names(normalizedData2), decreasing = FALSE),
]
if(!test_match_order(row.names(normalizedData2), row.names(probeFeaturesValue)))
stop("Wrong order matching Probes and Mutation!", Sys.time())
if(!test_match_order(row.names(normalizedData2), probeFeaturesValue$Probe))
stop("Wrong order matching Probes and Mutation!", Sys.time())
#browser()
normalizedData2 <- data.frame(row.names = row.names(probeFeaturesValue), normalizedData2)
write.table(normalizedData2, paste(normalizationDataFolder, "/CHAMP_Normalization_by_", methodNormalization , "/", "Normalized_Data_2.txt", sep = ""), sep = "\t", row.names = TRUE)
check <- normalizedData != normalizedData2
print (table(check))
##################
browser()
sampleSheet <- if (methodNormalization=="SWAN") {data.frame(dataToNormalize$pd@listData)} else { dataToNormalize$pd }
result <- list(probeFeatures = probeFeaturesValue, sampleSheet = sampleSheet, normalizedData = normalizedData)
end.time <- Sys.time()
time.taken <- end.time - start.time
message("Time to normalize ", time.taken)
return(result)
}