#' A quality control function
#'
#' This function will allow you to see the boxplots of raw and normal data as well as
#' a cluster analysis of the normalized data.
#'
#' @param rawData The raw data. normData The normalized data.
#' @keywords hugene, microarrays
#' @export
#' @examples
#' qc()
qc <- function(rawData, normData){
#checking boxplot of raw data
par(mar=c(10,4.5,2,1))
boxplot(rawData, target = "core", las=3)
#checking boxplot of normalized data
boxplot(normData, target = "core",las=3)
#hierarchical clustering
eset <- exprs(normData)
distance <- dist(t(eset),method="maximum")
clusters <- hclust(distance)
plot(clusters)
}
#making negative images
#Pset = fitProbeLevelModel(rawData)
#pdf(file='plot.pdf')
#for (i in 1:69){image(Pset,which=i,main=ph@data$sample[i])}
#dev.off()
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