### This is the analysis of NIEHS2 dataset in R

### Starts with the data from Lee with spot coordinates

# read in the maanova raw data
raw <- read.madata("F:/cui/Research/MicroarrayAnalyses/NIEHS2/data_edit/dataEdit_anovaInput_noname.txt", header=FALSE, designfile="F:/cui/Research/MicroarrayAnalyses/NIEHS2/data_edit/design2.txt",spotflag=FALSE,metarow=4, metacol=4,row=5, col=6,cloneid=2, pmt=7)

# reload the modified (2 slides regridded) data
raw <- read.madata("F:/cui/Research/MicroarrayAnalyses/NIEHS2/data_edit/anovaInput_nonameEdit.txt", header=FALSE, designfile="F:/cui/Research/MicroarrayAnalyses/NIEHS2/data_edit/design2.txt",spotflag=FALSE,metarow=4, metacol=4,row=5, col=6,cloneid=2, pmt=7)

# load the vector of row index with missing data
rowvec <- scan(file="F:/cui/Research/MicroarrayAnalyses/NIEHS2/data_edit/rowvec.txt", sep="\t")

# remove the rows with missing data
raw$data <-raw$data[setdiff(1:2085,rowvec),];
raw$cloneid <-raw$cloneid[setdiff(1:2085,rowvec)];
raw$metarow <-raw$metarow[setdiff(1:2085,rowvec)];
raw$metacol <-raw$metacol[setdiff(1:2085,rowvec)];
raw$row <-raw$row[setdiff(1:2085,rowvec)];
raw$col <-raw$col[setdiff(1:2085,rowvec)];

# convert data into raw from log2 transformed

raw$data <- 2^(raw$data)

# modify metarow and metacol because they only contain block number
raw$metarow[which(raw$metarow==2)] <- 1
raw$metarow[which(raw$metarow==3)] <- 2
raw$metarow[which(raw$metarow==4)] <- 2

raw$metacol[which(raw$metacol==3)] <- 1
raw$metacol[which(raw$metacol==4)] <- 2

save(raw, file="F:/cui/Research/MicroarrayAnalyses/NIEHS2/analysis2/raw.RData")

# riplot
riplot(raw)
graphics.off()

data <- createData(raw, 1)

ratio <- make.ratio(data, norm.std=FALSE)

arrayview(data, ratio=ratio, zlim=c(-1,1))
    # there is some heterogeneity in some of the arrays, mainly in array number
    # 22 and higher.  The most obvious one is block 1 and 2 read and 3,4 green.

gridcheck(raw, 1,2)
   # array 3  block 2 is completely off. (corrected in the regridded data)
   # array 10 block 1 and 2 are not great.(not corrected in the regridded data)

datas <- smooth(data, method="rlowess")
graphics.off()
ratio <- make.ratio(datas)
arrayview(datas,ratio=ratio, zlim=c(-1,1))
   # array 14 still has bright bottum band.