Nothing
library("aroma.affymetrix")
verbose <- Arguments$getVerbose(-4, timestamp=TRUE)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Setup
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
dataSet <- "GSE8605"
chipType <- "Mapping10K_Xba142"
csR <- AffymetrixCelSet$byName(dataSet, chipType=chipType, verbose=verbose)
print(csR)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# AS-CRMAv2
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
res <- doASCRMAv2(csR, drop=FALSE, verbose=verbose)
print(res)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Extraction test
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
ces <- res$cesN
# (a) Single array
ce <- ces[[1]]
Y <- extractMatrix(ce, verbose=verbose)
print(head(Y))
theta <- extractTheta(ce, verbose=verbose)
print(head(theta))
data <- extractDataFrame(ce, addNames=TRUE, verbose=verbose)
print(head(data))
# (b) Multiple arrays
Y <- extractMatrix(ces, verbose=verbose)
print(head(Y))
theta <- extractTheta(ces, verbose=verbose)
print(theta[1:6,,])
data <- extractDataFrame(ces, addNames=TRUE, verbose=verbose)
print(head(data))
# Extract unit and group name and indices together with chip effects
dataT <- extractDataFrame(ces, units=1:50, addNames=TRUE)
print(head(dataT))
# Sanity check
stopifnot(all.equal(dataT[1:50,], data[1:50,]))
# SNPs only
unf <- getUnitNamesFile(ces)
print(unf)
units <- indexOf(unf, pattern="^SNP")
str(units)
theta <- extractTheta(ces, units=units[1:10])
print(theta)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Plot theta:s
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
theta <- extractTheta(ces, units=units)
dimnames(theta)[[2]] <- c("A", "B")
ltheta <- log2(theta)
a <- (ltheta[,"A",]+ltheta[,"B",])/2
m <- ltheta[,"A",]-ltheta[,"B",]
toPNG(getFullName(ces), tags=c("LogDiffvsLogSum"), aspectRatio=0.7, {
Alim <- c(5,14)
Mlim <- diff(Alim)*c(-1,1)
Alab <- expression(1/2%*%log[2](theta[A]*theta[B]))
Mlab <- expression(log[2](theta[A]/theta[B]))
I <- dim(theta)[3]
layout(matrix(1:I, ncol=3, byrow=TRUE))
par(mar=c(3.8,4,3,1)+0.1)
for (ii in 1:I) {
name <- dimnames(theta)[[3]][ii]
plot(a[,ii], m[,ii], pch=".", xlim=Alim, ylim=Mlim, xlab=Alab, ylab=Mlab, main=name)
}
})
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