Dear Henrik,
I wonder if aroma.affymetrix is suitable for pooled GWA studies and
if you have any experience with this subject. In principle this
consists in extracting the RAS scores, so should be doable. I have the
following specific questions and snippet:
1. by using :
plm <- AvgCnPlm(csN, mergeStrands=TRUE, combineAlleles=FALSE)
data <- extractTotalAndFreqB(ce, units=units);
- the freqB column should be the equivalent of RAS?
- how is it possible to get the SNPs names in the data.frame from
extractTotalAndFreqB
- can the freqB for all the arrays be extracted at once, or only array
by array?
2. Is there a way to eliminate CN probes from the analysis from the
very beginning (just SNPs are need for pooling)?
3. Will be the standard normalization steps of CRMA usefuls/
deleterious/neutral?
I eliminated the crosstalk step so far, since I am not sure how this
behaves on a DNA pool. It seems to me that the crosstalk requires 3
clusters for AA, AB BB to work properly. Is this correct?
4. Same question for the pcr and probe sequence normalization steps.
Seems to me that they should not disturb
5. Do you see any missing/unuseful/wrong step in the code below?
#############
cdf <- AffymetrixCdfFile$byChipType("GenomeWideSNP_6",
tags="Full")
gi <- getGenomeInformation(cdf)
si <- getSnpInformation(cdf)
acs <- AromaCellSequenceFile$byChipType(getChipType(cdf,
fullname=FALSE))
cdf <- AffymetrixCdfFile$byChipType("GenomeWideSNP_6",
tags="Full")
csR <- AffymetrixCelSet$byName("POOLS_SNP", cdf=cdf)
#acc <- AllelicCrosstalkCalibration(csR, model="CRMAv2")
#print(acc)
#csC <- process(acc, verbose=verbose)
#print(csC)
bpn <- BasePositionNormalization(csR, target="zero")
csN <- process(bpn, verbose=verbose)
plm <- AvgCnPlm(csN, mergeStrands=TRUE, combineAlleles=FALSE)
if (length(findUnitsTodo(plm)) > 0) {
units <- fitCnProbes(plm, verbose=verbose)
str(units)
units <- fit(plm, verbose=verbose)
str(units)
}
ces <- getChipEffectSet(plm)
fln <- FragmentLengthNormalization(ces, target="zero")
cesN <- process(fln, verbose=verbose)
ce <- getFile(cesN, 1)
data <- extractTotalAndFreqB(ce, units=units);
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