functions

# Check the assumed conditions
# by means of your data

load("constants.rdata")
load("logdif.rdata")

## cell QQ plot
for (i in 1:NumOfExp) {
fname<- paste("cell_qq_", samnam[i],".png")
sampledata<-sample(logdif[,i], 10000)

png(filename = fname, width = 400, height = 430, pointsize = 14, bg="white", res = 96)
qqnorm(sampledata, ylab=samnam[i], main=paste("Cells in", samnam[i]))
curve(1*x, col="red", add=T)
dev.off()
}
rm(logdif)

## window QQ plot
load("window_median.rdata")
for (i in 1:NumOfExp) {
fname<- paste("window_median_qq",samnam[i],".png")
png(filename = fname, width = 400, height = 430, pointsize = 14, bg="white", res = 96)
samp<-sample(window_median[,i]/0.31, 10000)
qqnorm(samp, ylab=samnam[i], main=paste("Windows' Medians in", samnam[i]))
curve(1*x, col="red", add=T)
dev.off() }

med_25_sd <- array(NA, dim=c(NumOfExp, 1))

for (i in 1:NumOfExp) {
uq <- quantile(window_median[,i], 0.7, na.rm=T)
md <- quantile(window_median[,i], 0.5, na.rm=T)
dq <- quantile(window_median[,i] , 0.3, na.rm=T)
stdev <- (uq-dq)*(1/(qnorm(0.7)-qnorm(0.3)))
med_25_sd[i,1]<-stdev }
rm(window_median)
save(med_25_sd, file="med_25_sd.rdata")
## histogram for the windows' sd
png(filename = "histogram_windows_median.png", width = 400, height = 430, pointsize = 14, bg="white", res = 96)
hist(med_25_sd, breaks = ((1:20)*0.01+0.205))
dev.off()

# 01 Sep. 2006
# Tomokazu Konishi

# Check the assumed conditions # by means of your data

# Check the assumed conditions
# by means of your data