Hi

I am using your script to filter out the genes that are Absent in ALL the arrays. In the discussion you mention that normalize the data and then calculate detection calls(red font) but in the script, you do normalize first but for detection call you use the raw data(Blue font) is this the right step? See Below.

Thanks.
Mala

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Claire Wilson ClaireWilson at PICR.man.ac.uk
Tue Jul 19 17:28:50 CEST 2005

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Hi Josh,

Not sure whether anyone has responded to your mail yet, but I think an
easier way to do this would be to load your data in, normalise it then
calculate detection calls (present/absent calls) and then use these to
filter only out those probesets called present..

library(simpleaffy)
library(gcrma)

# read in all the cel files in the current directory
raw.data <- ReadAffy()

# normalise using gcrma
gcrma.eset <- call.exprs(raw.data, "gcrma")

# calculate detection calls
# present/absent calls are stored in the $call slot
calls.eset <- detection.p.val(raw.data)

# show the complete present/absent calls table for the expression set,
# columns are different chips, rows are the probesets
calls.eset$call

# summarise the calls for filtering
# effectively counts how many times a particular probeset is called
present
calls.sum <- rowSums(calls.eset$call == "P")

# to get all probesets that are present on all chips
present.all.chips <-
names(calls.sum[calls.sum==length(colnames(gcrma.eset at exprs))])

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