R/readBeadSummaryData.R
In markdunning/beadarray-devel: Quality assessment and low-level analysis for Illumina BeadArray data
readBeadSummaryData = function(dataFile, qcFile=NULL, sampleSheet=NULL, sep="\t", skip=8, ProbeID="ProbeID", columns = list(exprs = "AVG_Signal", se.exprs="BEAD_STDERR", nObservations = "Avg_NBEADS", Detection="Detection Pval"), qc.sep="\t", qc.skip=8, controlID="ProbeID", qc.columns = list(exprs="AVG_Signal", se.exprs="BEAD_STDERR", nObservations="Avg_NBEADS", Detection="Detection Pval"), illuminaAnnotation=NULL, dec=".", quote="", annoCols = c("TargetID", "PROBE_ID","SYMBOL"))
{
if(!(is.null(sampleSheet))){
samples = read.table(sampleSheet, sep=",", header=TRUE, skip=7, as.is=TRUE)
}
r = read.table(as.character(dataFile), sep=sep, header=TRUE, skip=skip, dec=dec, quote=quote, as.is=TRUE, row.names=NULL, check.names=FALSE, strip.white=TRUE, comment.char="", fill=TRUE)
#foundColumns = NULL
index = grep(ProbeID, colnames(r))
##Try to match the annotation columns
annoCols = match(annoCols, colnames(r))
annoCols = annoCols[!is.na(annoCols)]
annoMat = r[,annoCols,drop=FALSE]
if(length(index)!=0){
ProbeID = r[,index]
}
else {
stop("Could not find a column called ", ProbeID, " to use as bead identifiers. Check your file and try changing the \'ProbeID\' and/or \'skip\' arguments.")
}
#check for non-unique probe names
if(length(ProbeID) != length(unique(ProbeID))){
notdup = !duplicated(ProbeID)
warning("ProbeIDs non-unique: consider setting 'ProbeID' to another column containing unique identifiers. ", sum(!notdup), " repeated entries have been removed.\n")
ProbeID = ProbeID[notdup]
r = r[notdup,]
if(!is.na(annoCols)) annoMat = r[notdup,annoCols,drop=FALSE]
# warning("ProbeIDs non-unique: consider setting 'ProbeID' to another column containing unique values. Adding extension '.repX' to Xth replicate ID to enforce uniqueness.\n")
# dups = unique(ProbeID[duplicated(ProbeID)])
# for(j in 1:length(dups)) {
# sel = ProbeID==dups[j]
# ProbeID[sel] = paste(ProbeID[sel], ".rep", seq(1:sum(sel)), sep="")
# }
}
data = index = list()
ncols = NULL
nrows = nrow(r)
for(i in 1:length(columns)){
index[[i]] = grep(columns[[i]], colnames(r))
ncols[i] = length(index[[i]])
if(ncols[i] == 0){
cat("Could not find a column called: ", columns[[i]], "\n")
}
}
if(sum(ncols)==0) {
stop("No data found, check your file or try changing the \'skip\' argument")
}
i = seq(1:length(ncols))[ncols==max(ncols)][1]
defColNames = sub(paste("(.|)", columns[[i]], "(.|)", sep=""), "", colnames(r)[index[[i]]])
for(i in 1:length(columns)){
if(ncols[i]==max(ncols)) {
data[[i]] = r[,index[[i]]]
colNames = sub(paste("(.|)", columns[[i]], "(.|)", sep=""), "", colnames(r)[index[[i]]])
dupColNames = unique(colNames[duplicated(colNames)])
if(length(dupColNames)!=0) {
for(j in 1:length(dupColNames)) {
sel = colNames==dupColNames[j]
colNames[sel] = paste(colNames[sel], ".rep", seq(1:sum(sel)), sep="")
}
}
colnames(data[[i]]) = colNames
}
else { # data missing
data[[i]] = matrix(NA, nrows, max(ncols))
colnames(data[[i]]) = defColNames
}
rownames(data[[i]]) = ProbeID
# if(!(is.null(sampleSheet))){
# colnames(data[[i]]) = as.character(samples[,4])
# }
}
names(data) = names(columns) #foundColumns
BSData = new("ExpressionSetIllumina")
if(!is.null(illuminaAnnotation) && is.character(illuminaAnnotation))
BSData@annotation = illuminaAnnotation
for(i in 1:length(data)){
index = which(names(assayData(BSData))== names(data)[i])
if(ncols[i]==0) {
cat("Missing data - NAs stored in slot", names(data)[i], "\n")
}
assayData(BSData)[[index]] = as.matrix(data[[i]])
}
if(!(is.null(qcFile))){
QC = readQC(file=qcFile, sep=qc.sep, skip=qc.skip, columns=qc.columns, controlID=controlID, dec=dec, quote=quote)
if(ncol(QC$exprs)!=ncol(exprs(BSData))) {
warning("Number of arrays doesn't agree: ", ncol(exprs(BSData)), " in dataFile, versus ", ncol(QC$exprs), " in qcFile. qcFile ignored.")
}
else {
reorder = match(colnames(QC[[i]]), colnames(exprs(BSData)))
notagree = colnames(QC$exprs)!=colnames(exprs(BSData))
if(sum(notagree)==0) {
for(i in 1:length(QC)){
slotMatch = match(names(QC)[i], names(assayData(BSData)))
##Only bind the QC column to the existing assayData if it contains data
if(!is.na(slotMatch)){
if(ncol(QC[[i]]) == ncol(assayData(BSData)[[slotMatch]])){
assayData(BSData)[[slotMatch]] = rbind(assayData(BSData)[[slotMatch]], QC[[i]])
dupIDs = which(duplicated(rownames(assayData(BSData)[[slotMatch]])))
if(length(dupIDs) > 0){
rownames(assayData(BSData)[[slotMatch]])[dupIDs] = paste(rownames(assayData(BSData)[[slotMatch]])[dupIDs], ".2", sep="")
}
}
}
}
}
else {
if(length(reorder)!=0) {
for(i in 1:length(BSData@QC)) {
reorder = sapply(colnames(QC[[i]]), FUN="grep", colnames(exprs(BSData)), fixed=TRUE)
if(length(reorder)>0) {
QC[[i]] = QC[[i]][, reorder]
##Only bind the QC column to the existing assayData if it contains data
slotMatch = match(names(QC)[i], names(assayData(BSData))[i])
if(!is.na(slotMatch)){
if(ncol(QC[[i]]) == ncol(assayData(BSData)[[slotMatch]])){
assayData(BSData)[[slotMatch]] = rbind(assayData(BSData)[[slotMatch]], QC[[i]])
dupIDs = which(duplicated(rownames(assayData(BSData)[[slotMatch]])))
if(length(dupIDs) > 0){
rownames(assayData(BSData)[[slotMatch]])[dupIDs] = paste(rownames(assayData(BSData)[[slotMatch]])[dupIDs], ".2", sep="")
}
}
}
}
}
}
else {
warning("Could not match array names used in dataFile with those in qcFile. qcFile ignored.")
}
}
}
}
else QC = NULL
if(!(is.null(sampleSheet))){
colmatch = grep(colnames(exprs(BSData)), samples, fixed=TRUE)
ord = match(colnames(exprs(BSData)), samples[,colmatch])
if(length(colmatch)==1 && sum(is.na(ord))==0) {
samples = samples[ord,]
rownames(samples) = colnames(exprs(BSData))
p = new("AnnotatedDataFrame", samples, data.frame(labelDescription=colnames(samples), row.names=colnames(samples)))
}
else {
warning("Could not reconcile dataFile with sampleSheet information. sampleSheet ignored.")
p = new("AnnotatedDataFrame", data.frame(sampleID=colnames(exprs(BSData)),row.names=colnames(exprs(BSData))))
}
}
else {
p = new("AnnotatedDataFrame", data.frame(sampleID=colnames(exprs(BSData)),row.names=colnames(exprs(BSData))))
}
##Have we added any more IDs to BSData
Status = rep("regular", length(ProbeID))
if(!is.null(QC)){
Type = QC$Type
newIDs = rownames(QC[[1]])
##Some IDs might already be in the QC and the Gene data
ProbeID = c(ProbeID, newIDs)
dupIDs = which(duplicated(ProbeID))
newAnno = matrix(nrow = length(newIDs), ncol=ncol(annoMat), NA)
colnames(newAnno) = colnames(annoMat)
annoMat = rbind(annoMat, newAnno)
Status = c(Status, Type)
##Some
if(length(dupIDs) > 0){
ProbeID[dupIDs] = paste(ProbeID[dupIDs], ".2", sep="")
}
}
featureData <- new("AnnotatedDataFrame", data=data.frame(ProbeID,annoMat, row.names=ProbeID, Status=Status))
phenoData(BSData) <- p
featureData(BSData) <- featureData
###We've read single-channel data, so set the channelData slot appropriately
BSData@channelData[[1]] <- rep("G", length(sampleNames(BSData)))
BSData
}
readQC=function(file, sep="\t", skip=8, controlID = "ProbeID", columns=list(exprs="AVG_Signal", se.exprs="BEAD_STDERR", nObservations="Avg_NBEADS", Detection="Detection Pval"), dec=".", quote=""){
##
r=read.table(as.character(file), sep=sep, header=TRUE, skip=skip, quote=quote, as.is=TRUE, check.names=FALSE, strip.white=TRUE, comment.char="", fill=TRUE)
##If there is an ArrayID column, the QC file is BeadStudio version 1 and each row in the file is an array
# read.table(file = fileName, header = TRUE, sep = sep,
# skip = nMetaDataLines, row.names = NULL, quote = "",
# as.is = TRUE, check.names = FALSE, strip.white = TRUE,
# comment.char = "", fill = TRUE)
ArrayID = grep("ArrayID", colnames(r))
type = NULL
typeCol = grep("TargetID", colnames(r))
if (!is.na(typeCol)){
type = r[,typeCol]
}
if(length(ArrayID) != 0){
BeadStudioVersion=1
index = grep(columns$exprs, colnames(r))
if(length(index)!=0){
ProbeID = sub(paste("(.|)", columns$exprs, "(.|)", sep=""), "", colnames(r))[index]
nrows = length(ProbeID)
}
else { # can't find controlIDs - report warning
stop("Could not find a column called ", controlID, " to use as control identifiers. Check your file and try changing the \'controlID\' and/or \'skip\' arguments.")
}
}
else {
BeadStudioVersion=2
nrows = nrow(r)
index = grep(controlID, colnames(r))
if(length(index)!=0){
ProbeID = r[,index]
}
else { # can't find controlIDs - report warning
stop("Could not find a column called ", controlID, " to use as control identifiers. Check your file and try changing the \'controlID\' and/or \'skip\' arguments.")
}
}
# check for non-unique probe names
if(length(ProbeID) != length(unique(ProbeID))){
notdup = !duplicated(ProbeID)
warning("controlIDs non-unique: ", sum(!notdup), " repeated entries have been removed.\n")
ProbeID = ProbeID[notdup]
r = r[notdup,]
type = type[notdup]
}
data = index = list()
ncols = NULL
for(i in 1:length(columns)){
index[[i]] = grep(columns[[i]], colnames(r))
ncols[i] = length(index[[i]])
if(ncols[i] == 0){
cat("[readQC] Could not find a column called: ", columns[[i]], "\n")
}
}
if(sum(ncols)==0) {
stop("No data found, check your file or try changing the \'skip\' argument")
}
i = seq(1:length(ncols))[ncols==max(ncols)][1]
defColNames = sub(paste("(.|)", columns[[i]], "(.|)", sep=""), "", colnames(r)[index[[i]]])
for(i in 1:length(columns)){
if(ncols[i]==max(ncols)) {
if(BeadStudioVersion == 2) {
data[[i]] = as.matrix(r[,index[[i]]])
colnames(data[[i]]) = sub(paste("(.|)", columns[[i]], "(.|)", sep=""), "", colnames(r)[index[[i]]])
}
else {
data[[i]] = as.matrix(t(r[,index[[i]]]))
colnames(data[[i]]) = r[,ArrayID]
}
}
else { # data missing
if(BeadStudioVersion == 2) {
data[[i]] = matrix(NA, nrows, max(ncols))
colnames(data[[i]]) = defColNames
}
else {
data[[i]] = matrix(NA, nrows, nrow(r))
colnames(data[[i]]) = r[,ArrayID]
}
}
rownames(data[[i]]) = ProbeID
}
names(data) = names(columns) # foundColumns
QC = list(exprs=new("matrix"), se.exprs=new("matrix"), Detection=new("matrix"), nObservations=new("matrix"),Type = new("character"))
for(i in 1:length(data)){
index = which(names(QC)== names(data)[i])
if(ncols[i]==0) {
cat("[readQC] Missing data - NAs stored in slot", names(data)[i], "\n")
}
QC[[index]] = data[[i]]
}
if(!is.null(type)){
QC$Type = type
}
QC
}
markdunning/beadarray-devel documentation built on May 21, 2019, noon
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readBeadSummaryData = function(dataFile, qcFile=NULL, sampleSheet=NULL, sep="\t", skip=8, ProbeID="ProbeID", columns = list(exprs = "AVG_Signal", se.exprs="BEAD_STDERR", nObservations = "Avg_NBEADS", Detection="Detection Pval"), qc.sep="\t", qc.skip=8, controlID="ProbeID", qc.columns = list(exprs="AVG_Signal", se.exprs="BEAD_STDERR", nObservations="Avg_NBEADS", Detection="Detection Pval"), illuminaAnnotation=NULL, dec=".", quote="", annoCols = c("TargetID", "PROBE_ID","SYMBOL"))
{
if(!(is.null(sampleSheet))){
samples = read.table(sampleSheet, sep=",", header=TRUE, skip=7, as.is=TRUE)
}
r = read.table(as.character(dataFile), sep=sep, header=TRUE, skip=skip, dec=dec, quote=quote, as.is=TRUE, row.names=NULL, check.names=FALSE, strip.white=TRUE, comment.char="", fill=TRUE)
#foundColumns = NULL
index = grep(ProbeID, colnames(r))
##Try to match the annotation columns
annoCols = match(annoCols, colnames(r))
annoCols = annoCols[!is.na(annoCols)]
annoMat = r[,annoCols,drop=FALSE]
if(length(index)!=0){
ProbeID = r[,index]
}
else {
stop("Could not find a column called ", ProbeID, " to use as bead identifiers. Check your file and try changing the \'ProbeID\' and/or \'skip\' arguments.")
}
#check for non-unique probe names
if(length(ProbeID) != length(unique(ProbeID))){
notdup = !duplicated(ProbeID)
warning("ProbeIDs non-unique: consider setting 'ProbeID' to another column containing unique identifiers. ", sum(!notdup), " repeated entries have been removed.\n")
ProbeID = ProbeID[notdup]
r = r[notdup,]
if(!is.na(annoCols)) annoMat = r[notdup,annoCols,drop=FALSE]
# warning("ProbeIDs non-unique: consider setting 'ProbeID' to another column containing unique values. Adding extension '.repX' to Xth replicate ID to enforce uniqueness.\n")
# dups = unique(ProbeID[duplicated(ProbeID)])
# for(j in 1:length(dups)) {
# sel = ProbeID==dups[j]
# ProbeID[sel] = paste(ProbeID[sel], ".rep", seq(1:sum(sel)), sep="")
# }
}
data = index = list()
ncols = NULL
nrows = nrow(r)
for(i in 1:length(columns)){
index[[i]] = grep(columns[[i]], colnames(r))
ncols[i] = length(index[[i]])
if(ncols[i] == 0){
cat("Could not find a column called: ", columns[[i]], "\n")
}
}
if(sum(ncols)==0) {
stop("No data found, check your file or try changing the \'skip\' argument")
}
i = seq(1:length(ncols))[ncols==max(ncols)][1]
defColNames = sub(paste("(.|)", columns[[i]], "(.|)", sep=""), "", colnames(r)[index[[i]]])
for(i in 1:length(columns)){
if(ncols[i]==max(ncols)) {
data[[i]] = r[,index[[i]]]
colNames = sub(paste("(.|)", columns[[i]], "(.|)", sep=""), "", colnames(r)[index[[i]]])
dupColNames = unique(colNames[duplicated(colNames)])
if(length(dupColNames)!=0) {
for(j in 1:length(dupColNames)) {
sel = colNames==dupColNames[j]
colNames[sel] = paste(colNames[sel], ".rep", seq(1:sum(sel)), sep="")
}
}
colnames(data[[i]]) = colNames
}
else { # data missing
data[[i]] = matrix(NA, nrows, max(ncols))
colnames(data[[i]]) = defColNames
}
rownames(data[[i]]) = ProbeID
# if(!(is.null(sampleSheet))){
# colnames(data[[i]]) = as.character(samples[,4])
# }
}
names(data) = names(columns) #foundColumns
BSData = new("ExpressionSetIllumina")
if(!is.null(illuminaAnnotation) && is.character(illuminaAnnotation))
BSData@annotation = illuminaAnnotation
for(i in 1:length(data)){
index = which(names(assayData(BSData))== names(data)[i])
if(ncols[i]==0) {
cat("Missing data - NAs stored in slot", names(data)[i], "\n")
}
assayData(BSData)[[index]] = as.matrix(data[[i]])
}
if(!(is.null(qcFile))){
QC = readQC(file=qcFile, sep=qc.sep, skip=qc.skip, columns=qc.columns, controlID=controlID, dec=dec, quote=quote)
if(ncol(QC$exprs)!=ncol(exprs(BSData))) {
warning("Number of arrays doesn't agree: ", ncol(exprs(BSData)), " in dataFile, versus ", ncol(QC$exprs), " in qcFile. qcFile ignored.")
}
else {
reorder = match(colnames(QC[[i]]), colnames(exprs(BSData)))
notagree = colnames(QC$exprs)!=colnames(exprs(BSData))
if(sum(notagree)==0) {
for(i in 1:length(QC)){
slotMatch = match(names(QC)[i], names(assayData(BSData)))
##Only bind the QC column to the existing assayData if it contains data
if(!is.na(slotMatch)){
if(ncol(QC[[i]]) == ncol(assayData(BSData)[[slotMatch]])){
assayData(BSData)[[slotMatch]] = rbind(assayData(BSData)[[slotMatch]], QC[[i]])
dupIDs = which(duplicated(rownames(assayData(BSData)[[slotMatch]])))
if(length(dupIDs) > 0){
rownames(assayData(BSData)[[slotMatch]])[dupIDs] = paste(rownames(assayData(BSData)[[slotMatch]])[dupIDs], ".2", sep="")
}
}
}
}
}
else {
if(length(reorder)!=0) {
for(i in 1:length(BSData@QC)) {
reorder = sapply(colnames(QC[[i]]), FUN="grep", colnames(exprs(BSData)), fixed=TRUE)
if(length(reorder)>0) {
QC[[i]] = QC[[i]][, reorder]
##Only bind the QC column to the existing assayData if it contains data
slotMatch = match(names(QC)[i], names(assayData(BSData))[i])
if(!is.na(slotMatch)){
if(ncol(QC[[i]]) == ncol(assayData(BSData)[[slotMatch]])){
assayData(BSData)[[slotMatch]] = rbind(assayData(BSData)[[slotMatch]], QC[[i]])
dupIDs = which(duplicated(rownames(assayData(BSData)[[slotMatch]])))
if(length(dupIDs) > 0){
rownames(assayData(BSData)[[slotMatch]])[dupIDs] = paste(rownames(assayData(BSData)[[slotMatch]])[dupIDs], ".2", sep="")
}
}
}
}
}
}
else {
warning("Could not match array names used in dataFile with those in qcFile. qcFile ignored.")
}
}
}
}
else QC = NULL
if(!(is.null(sampleSheet))){
colmatch = grep(colnames(exprs(BSData)), samples, fixed=TRUE)
ord = match(colnames(exprs(BSData)), samples[,colmatch])
if(length(colmatch)==1 && sum(is.na(ord))==0) {
samples = samples[ord,]
rownames(samples) = colnames(exprs(BSData))
p = new("AnnotatedDataFrame", samples, data.frame(labelDescription=colnames(samples), row.names=colnames(samples)))
}
else {
warning("Could not reconcile dataFile with sampleSheet information. sampleSheet ignored.")
p = new("AnnotatedDataFrame", data.frame(sampleID=colnames(exprs(BSData)),row.names=colnames(exprs(BSData))))
}
}
else {
p = new("AnnotatedDataFrame", data.frame(sampleID=colnames(exprs(BSData)),row.names=colnames(exprs(BSData))))
}
##Have we added any more IDs to BSData
Status = rep("regular", length(ProbeID))
if(!is.null(QC)){
Type = QC$Type
newIDs = rownames(QC[[1]])
##Some IDs might already be in the QC and the Gene data
ProbeID = c(ProbeID, newIDs)
dupIDs = which(duplicated(ProbeID))
newAnno = matrix(nrow = length(newIDs), ncol=ncol(annoMat), NA)
colnames(newAnno) = colnames(annoMat)
annoMat = rbind(annoMat, newAnno)
Status = c(Status, Type)
##Some
if(length(dupIDs) > 0){
ProbeID[dupIDs] = paste(ProbeID[dupIDs], ".2", sep="")
}
}
featureData <- new("AnnotatedDataFrame", data=data.frame(ProbeID,annoMat, row.names=ProbeID, Status=Status))
phenoData(BSData) <- p
featureData(BSData) <- featureData
###We've read single-channel data, so set the channelData slot appropriately
BSData@channelData[[1]] <- rep("G", length(sampleNames(BSData)))
BSData
}
readQC=function(file, sep="\t", skip=8, controlID = "ProbeID", columns=list(exprs="AVG_Signal", se.exprs="BEAD_STDERR", nObservations="Avg_NBEADS", Detection="Detection Pval"), dec=".", quote=""){
##
r=read.table(as.character(file), sep=sep, header=TRUE, skip=skip, quote=quote, as.is=TRUE, check.names=FALSE, strip.white=TRUE, comment.char="", fill=TRUE)
##If there is an ArrayID column, the QC file is BeadStudio version 1 and each row in the file is an array
# read.table(file = fileName, header = TRUE, sep = sep,
# skip = nMetaDataLines, row.names = NULL, quote = "",
# as.is = TRUE, check.names = FALSE, strip.white = TRUE,
# comment.char = "", fill = TRUE)
ArrayID = grep("ArrayID", colnames(r))
type = NULL
typeCol = grep("TargetID", colnames(r))
if (!is.na(typeCol)){
type = r[,typeCol]
}
if(length(ArrayID) != 0){
BeadStudioVersion=1
index = grep(columns$exprs, colnames(r))
if(length(index)!=0){
ProbeID = sub(paste("(.|)", columns$exprs, "(.|)", sep=""), "", colnames(r))[index]
nrows = length(ProbeID)
}
else { # can't find controlIDs - report warning
stop("Could not find a column called ", controlID, " to use as control identifiers. Check your file and try changing the \'controlID\' and/or \'skip\' arguments.")
}
}
else {
BeadStudioVersion=2
nrows = nrow(r)
index = grep(controlID, colnames(r))
if(length(index)!=0){
ProbeID = r[,index]
}
else { # can't find controlIDs - report warning
stop("Could not find a column called ", controlID, " to use as control identifiers. Check your file and try changing the \'controlID\' and/or \'skip\' arguments.")
}
}
# check for non-unique probe names
if(length(ProbeID) != length(unique(ProbeID))){
notdup = !duplicated(ProbeID)
warning("controlIDs non-unique: ", sum(!notdup), " repeated entries have been removed.\n")
ProbeID = ProbeID[notdup]
r = r[notdup,]
type = type[notdup]
}
data = index = list()
ncols = NULL
for(i in 1:length(columns)){
index[[i]] = grep(columns[[i]], colnames(r))
ncols[i] = length(index[[i]])
if(ncols[i] == 0){
cat("[readQC] Could not find a column called: ", columns[[i]], "\n")
}
}
if(sum(ncols)==0) {
stop("No data found, check your file or try changing the \'skip\' argument")
}
i = seq(1:length(ncols))[ncols==max(ncols)][1]
defColNames = sub(paste("(.|)", columns[[i]], "(.|)", sep=""), "", colnames(r)[index[[i]]])
for(i in 1:length(columns)){
if(ncols[i]==max(ncols)) {
if(BeadStudioVersion == 2) {
data[[i]] = as.matrix(r[,index[[i]]])
colnames(data[[i]]) = sub(paste("(.|)", columns[[i]], "(.|)", sep=""), "", colnames(r)[index[[i]]])
}
else {
data[[i]] = as.matrix(t(r[,index[[i]]]))
colnames(data[[i]]) = r[,ArrayID]
}
}
else { # data missing
if(BeadStudioVersion == 2) {
data[[i]] = matrix(NA, nrows, max(ncols))
colnames(data[[i]]) = defColNames
}
else {
data[[i]] = matrix(NA, nrows, nrow(r))
colnames(data[[i]]) = r[,ArrayID]
}
}
rownames(data[[i]]) = ProbeID
}
names(data) = names(columns) # foundColumns
QC = list(exprs=new("matrix"), se.exprs=new("matrix"), Detection=new("matrix"), nObservations=new("matrix"),Type = new("character"))
for(i in 1:length(data)){
index = which(names(QC)== names(data)[i])
if(ncols[i]==0) {
cat("[readQC] Missing data - NAs stored in slot", names(data)[i], "\n")
}
QC[[index]] = data[[i]]
}
if(!is.null(type)){
QC$Type = type
}
QC
}
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