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Question: perform probe level RMA without summarization
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gravatar for jxd_84
8 months ago by
jxd_8410
jxd_8410 wrote:

I'm trying to perform normalization on a set of Affy U133A chips. I'm using the affy library on R and was able to do the regular probeset level normalization using ReadAffy() and rma() on the affybatch object.

But now I want to do the same thing but for the probe level data. The problem is, I cannot use expresso with summarization disabled (a summary argument has to be provided or it returns an error).  Nor can I use the function pm() because the probe to probeset id numbers are lost.  That is, with pm() the row identifiers turn into probe numbers. but with the function probes() i still get 1007_s_at1, 1007_s_at2, etc.   

Is there a way I can do all the steps that RMA does to the probe level data, without summarization, and with keeping the associated probeset id information to each probe?

I hope this was was clear. If not, I can elaborate. 

ADD COMMENTlink modified 8 months ago by James W. MacDonald44k • written 8 months ago by jxd_8410
1
gravatar for James W. MacDonald
8 months ago by
United States
James W. MacDonald44k wrote:

It's not clear exactly what you are after; I assume you just want to background correct and then normalize the probes? You can easily do that. As an example:

> dat <- ReadAffy()
> dat

AffyBatch object
size of arrays=712x712 features (18 kb)
cdf=HG-U133A (22283 affyids)
number of samples=6
number of genes=22283
annotation=hgu133a
notes=

> dat.bg <- bg.correct(dat, "rma")
> dat.bg.norm <- normalize(dat.bg, "quantiles")

Now we have background corrected and normalized data. It's probably easiest to now extract these data into a list:

> prbs <- probes(dat.bg.norm, LISTRUE = TRUE)

And now we have a list of background corrected, normalized probes, by probeset. These are not log transformed yet, so we could do that as well.

> prbs.log <- lapply(prbs, log2)

And just to check, let's compare the RMA results from just running RMA directly vs what we get from our data:

> eset <- rma(dat)
> head(exprs(eset), 1)
          GSM533844.CEL.gz GSM533845.CEL.gz GSM533846.CEL.gz GSM533847.CEL.gz
1007_s_at         8.764547         9.015684          8.93276         9.319638
          GSM533848.CEL.gz GSM533849.CEL.gz
1007_s_at         9.225833         9.157688
> z <- medpolish(prbs.log[["1007_s_at"]])
1: 26.33469
2: 25.76838
Final: 25.68395
> z$col + z$overall
GSM533844.CEL.gz GSM533845.CEL.gz GSM533846.CEL.gz GSM533847.CEL.gz
        8.764547         9.015684         8.932760         9.319638
GSM533848.CEL.gz GSM533849.CEL.gz
        9.225833         9.157688

Which looks pretty much exactly the same.

 

 

 


 

ADD COMMENTlink written 8 months ago by James W. MacDonald44k
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