[BioC] Detection calls and LIMMA

[Richard Friedman]

Dear Gordon,

	Can you  suggest how to define "some modest evidence of expression"  
in Affymetrix arrays filtered with RMA
or GCRMA which does not give a presence-or-absence call?

Thanks and best wishes,
Rich

On Mar 1, 2011, at 7:50 PM, Gordon K Smyth wrote:

> Deaer Avhena,
>
> I agree with Wolfgang that filtering is useful.  In my lab, the  
> standard practice is to filter probes that fail to show some modest  
> evidence for expression on at least n arrays, where n is the minimum  
> group size.  For example, if we compare wt (with 2 replicate arrays)  
> to a mutant (with 3 replicate arrays), we filter probes that are  
> Present on fewer than 2 arrays.
>
> This is because we want to keep any probe that is expressed in at  
> least one of the experimental conditions.  If a probe is expressed  
> in one of the conditions, then it should appear consistently across  
> the replicates for that condition.
>
> Best wishes
> Gordon
>
>> Date: Mon, 28 Feb 2011 11:35:42 -0500
>> From: avehna <avhena at gmail.com>
>> To: whuber at embl.de
>> Cc: bioconductor at r-project.org
>> Subject: Re: [BioC] Detection calls and LIMMA
>>
>> Dear Wolfgang,
>>
>> Thank you for your response, I agree with you. I will read the  
>> paper now...
>>
>> Best Regards,
>> Avhena
>>
>> On Mon, Feb 28, 2011 at 4:38 AM, Wolfgang Huber <whuber at embl.de>  
>> wrote:
>>
>>> Hi Avhena
>>>
>>> it is not required, but properly applied filtering can increase  
>>> detection
>>> power in your experiment while still controlling type-I error (false
>>> positives). The example you mention seems to be one that you want  
>>> to keep
>>> though, since it is a good candidate for being up-regulated in the  
>>> Treatment
>>> condition. One possibly reasonable criterion would be, e.g., to  
>>> filter out
>>> all probesets that are called 'Absent' on all arrays. Some further
>>> discussion on the topic is also here:
>>>
>>> [1] Bourgon, Gentleman and Huber. Independent filtering increases  
>>> detection
>>> power for high-throughput experiments. PNAS, 107(21):9546-9551,
>>>
>>>       Best wishes
>>>       Wolfgang
>>>
>>>
>>> Il Feb/28/11 6:51 AM, avehna ha scritto:
>>>
>>>> Hi All,
>>>>
>>>> I have a basic question. Is it required to filter the microarray  
>>>> data
>>>> based
>>>> on the detection calls (A/M/P) before analyzing it with LIMMA?
>>>>
>>>> What if I have the following scenario (for example):
>>>>
>>>>                           Control Control Control         Treatment
>>>> Treatment Treatment
>>>> 1367813_at           A            A             P
>>>> P                   P                 P
>>>>
>>>> Please note that this gene is just "present/detected"  once in the
>>>> Control,
>>>> but it is present in all the replicates of the treatment. In this  
>>>> case:
>>>> what
>>>> would be the right thing to do? To eliminate it from the analysis  
>>>> or keep
>>>> it
>>>> and consider it up or down depending on the signal of the  
>>>> treatment?
>>>>
>>>> Thank a lot!
>>>> Avhena
>
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