Hi Atul,

Not sure if there is a function in affy or limma for what you are trying to do but this might help:http://www.inside-r.org/packages/cran/WGCNA/docs/collapseRows

Mete



On Apr 3, 2013, at 9:17 PM, Atul Kakrana <atulkakrana@gmail.com<mailto:atulkakrana@gmail.com>> wrote:

Hello Martin and All,

I think I was not clear with my question and therefore would like to
rephrase it. I am analyzing Affymetrix data and one thing I need to do
is that select one probe-set if there are multiple probe-set for same
gene and the criteria I need to use it to select the probe set with
highest median expression across all the samples.

So, if there are 5 probe-sets corresponding to same gene than I need to
select the one with highest median expression across all samples to
represent the expression of that gene. As I am trying to change from
probe-set level to gene level analysis I was hoping that there must be
some function already to do this in 'affy' or 'limma'.

@Martin: I think you suggested me the right solution even when I was not
clear with my question. Could you please confirm that? Also, wouldn't it
be better to perform this step after bg correction, normalization? I am
very confused at this moment.

mydata <- ReadAffy()
pData(mydata)<- read.table("phenodata",head = T,row.names=1,sep = '\t')
esetRMA <- rma(mydata)

Perform probe set reduction here>>>

I would really appreciate your suggestions on how and where I can select
the probe-set  with higest median expression across all the samples.

Thanks

AK






On 03-Apr-13 11:34 PM, Martin Morgan wrote:
On 04/03/2013 03:17 PM, Atul Kakrana wrote:
Hello All,

I need your help. I am analysing affymetrix data and have to select the
probe-set that has median expression among all the probe-sets for same
gene. This way I want to remove the redundancy by keeping the analysis
to single gene entry level. I am fully aware that it is not a nice thing
to do but I just have to do it.

To do so, I came across 'findLargest' function of 'genefilter' package
but it's not well documented; and I do not know how to implement the
'findLargest' function. At this point I have:
esetRMA <- rma(mydata)

Could anybody guide me on how can I select single probeset with median
expression from multiple probe-sets corresponding to single gene and
discard others? Is there any other way to achieve so i.e. other than
using 'genefilter'?

Genefilter package:
http://www.bioconductor.org/packages/2.11/bioc/html/genefilter.html

Hi Atul --It's a Bioconductor package, so might as well ask instead on
the Bioconductor mailing list

 http://bioconductor.org/help/mailing-list/

As a reproducible example, load the "ALL" sample ExpressionSet,
Biobase and genefilter packates

 library(Biobase)
 library(ALL)
 library(genefilter)

The three arguments to findLargest are the names of the probe sets

 featureNames(ALL)

the test statistic

 rowMedians(ALL)

and the chip from which the ExpressionSet is based

 annotation(ALL)

So the variable

 idx = findLargest(featureNames(ALL), rowMedians(ALL), annotation(ALL)

identifies the probes and

 ALL1 = ALL[idx,]

gets you the data you're interested in.

Again, follow-up questions should go to the Bioconductor mailing list.

Martin



Thanks

AK





--
Atul Kakrana
DBI, Delaware Technology Park

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