Question

huex10stv2cdf annotation file needed

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arisarkar88 ▴ 40

@arisarkar88-11464

Last seen 9 months ago

Los Angeles

Where can i find huex10stv2cdf annotation file? Unable to download it from the link: https://stat.ethz.ch/pipermail/bioc-devel/2007-October/001411.html

cdf microarray affy • 1.5k views

ADD COMMENT • link updated 7.2 years ago by James W. MacDonald 65k • written 7.2 years ago by arisarkar88 ▴ 40

score 0 · Answer 1 · 2017-02-22

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James W. MacDonald 65k

@james-w-macdonald-5106

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That's not an annotation file (which would map the probeset IDs to various gene annotations, etc). Instead that is a cdf package intended to be used with the affy package, in order to process the raw data into expression values.

But do note that won't work either, as the affy package will not let you process the Exon arrays. For that you should use the oligo package, and that should be straightforward:

library(oligo)

dat <- read.celfiles(list.celfiles())

eset <- rma(dat)

ADD COMMENT • link 7.2 years ago James W. MacDonald 65k

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Thank you for the reply. I was bit confused regarding this. Is it possible to analyze/normalize Affymetrix Human Exon 1.0 ST Array and Affymetrix Human Gene 1.0 ST Array together? How should I deal with two datasets having these the above platforms respectively?

ADD REPLY • link 7.2 years ago arisarkar88 ▴ 40

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No, unfortunately you can't normalize them together. In fact you almost surely won't be able to analyze them together either - the two arrays are just too different. If you have the same experiment that was repeated on the two platforms, then you might be able to normalize and summarize the data separately and then use something like the GeneMeta package to do a meta analysis. But that assumes that you pretty much repeated the same experiment on each array platform.

But if the different groups that you want to compare are only assayed on one array or the other, then any biological difference is likely to be orders of magnitude smaller than the technical differences between the array platforms. While you could hypothetically still analyze the data, it is most likely a lost cause, because you can't say if any differences are due to biology or technical differences between the arrays.