[BioC] Advise on setting up a non-specific filter for differential expression

[Tobias Straub]

Hi Lucia!

did you already have a look at the nsFilter function in the genefilter package? 

nsFilter(eset, require.entrez = F, require.symbol = F,
require.GOBP = FALSE, require.GOCC = FALSE, require.GOMF = FALSE,
remove.dupEntrez = TRUE, var.func = IQR, var.cutoff = 0.5, var.filter = TRUE)

would simply remove half of the genes based on low IQR across the arrays. assuming that a) non-expressed genes have a low IQR and b) that frequently not more than 50% of genes are expressed in any given tissue.

this is far from a "present" filter but I have no other suggestion in case you don't trust MAS calls. out of curiosity: did you quality check your arrays, could there be batch effects, what's your pre-processing?

best regards
T.

On Aug 16, 2010, at 4:50 PM, Lucia Peixoto wrote:

> Thanks Tobias for your response
> 
> I am processing data obtained with Affymetrix mouse chips (430_2, previous
> version)
> The first filterning was done based on presence/absence calls, so only genes
> present in 2/17 samples were used. It is a 2 condition set up, with 8 and 9
> replicates for each condition. My definition of FDR in my previous question
> was strictly limited to validation in 8+ independent qPCRs of 40+ randomly
> selected genes obtained using a SAM cutoff of 5% FDR. So I am talking about
> independently re-testing the reproducibility of gene expression, which is
> the only way to really know your FDR. Using the Mas5 presence absence calls
> filter leads to about 50% of the tested genes not being reproducible.
> 
> If I remove the filtering and redo the analysis at 5% FDR, I get all the the
> previous "false positives" to become true positives. Which was not a
> surprise to me since about 1/3 of MM probes are known to hybridize better
> than PM probes, so I don't know what Mas5 presence/absence really means, but
> definitely cannot reflect accurately the presence of a transcript if the MM
> probe hybridizes better.
> 
> The problem is that I have a great loss of sensitivity (I have a lot of
> positive controls so I know that), and I would like to increase that using a
> filter that can come closer to really defining "present", because MM/PM does
> not.
> any ideas?
> thanks
> 
> Lucia
> 
> 
> On Mon, Aug 16, 2010 at 8:34 AM, Tobias Straub
> <tstraub at med.uni-muenchen.de>wrote:
> 
>> Hi Lucia
>> 
>> I am not sure if I completely understand your problem, just want to mention
>> that I routinely apply non-specific filtering based on MAS5 calls with a
>> very good outcome (based on a prior-knowledge training set). I do not like
>> so much the alternative approach - filtering based on variance or IQR -  as
>> it jeopardizes my preferred way of defining responders by applying a
>> threshold on the local false discovery rate.
>> 
>> Could you extend a bit on how you exactly filter based on MAS5 calls, how
>> you define responders and non-responders in qPCR, how your "FDR disaster"
>> exactly looks like.
>> 
>> What is your model system by the way, which arrays you use?
>> 
>> best regards
>> T.
>> 
>> 
>> On Aug 13, 2010, at 7:11 PM, Lucia Peixoto wrote:
>> 
>>> Dear All,
>>> I want to set up a non-specific filter to eliminate genes that are juts
>> not
>>> expressed from further statistical analysis. I've previously tried a
>> filter
>>> based on Mas5 presence/absence calls which turned out to be a disaster
>> for
>>> the FDR (as measured by lots of qPCRs), probably because 1/3 of the MM
>>> probes actually hybridize better than PM, who knows.
>>> 
>>> In any case, my plan is to set up a filter based both on raw fluorescent
>>> intensity and IQR. I am trying to get as much sensitivity as possible
>>> without increasing my FDR too much.
>>> I was thinking that using the intensity distributions and box plots of
>> the
>>> raw data may be useful to determine what the best cutoffs to obtain the
>> best
>>> sensitivity will be.
>>> Any advise on how to select appropriate cutoffs?
>>> 
>>> Thank you very much in advance
>>> Lucia
>>> 
>>>      [[alternative HTML version deleted]]
>>> 
>>> _______________________________________________
>>> Bioconductor mailing list
>>> Bioconductor at stat.math.ethz.ch
>>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>>> Search the archives:
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>> 
>> ----------------------------------------------------------------------
>> Dr. Tobias Straub ++4989218075439 Adolf-Butenandt-Institute, München D
>> 
>> 
> 
> 	[[alternative HTML version deleted]]
> 
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

----------------------------------------------------------------------
Dr. Tobias Straub ++4989218075439 Adolf-Butenandt-Institute, München D