[BioC] Detection calls and LIMMA in GENE ST1.0
cstrato
cstrato at aon.at
Mon Mar 7 20:42:35 CET 2011
Dear Richard,
For Gene ST arrays Affymetrix has developed DABG as algorithm for P/M/A
calls. Using DABG you can filter RMA-normalized genes. As far as I know
DABG is currently only supported by APT and by xps. (In addition xps
allows you in principle to use the original detection call algorithm
for Gene ST arrays, too.)
Best regards
Christian
_._._._._._._._._._._._._._._._._._
C.h.r.i.s.t.i.a.n S.t.r.a.t.o.w.a
V.i.e.n.n.a A.u.s.t.r.i.a
e.m.a.i.l: cstrato at aon.at
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On 3/7/11 7:30 PM, Richard Friedman wrote:
> Jenny and list,
>
> Am I correct that P/M/A calls depend upon the presence of mismatched genes?
> If so, is there a way to filter RMA normalized ST1.0 genes by present
> absent?
>
> Thanks and best wishes,
> Rich
>
>
> On Mar 2, 2011, at 4:04 PM, Jenny Drnevich wrote:
>
>> Hi Rich,
>>
>> You can use the P/M/A calls to filter regardless of what
>> pre-processing algorithm you use. It is a completely separate
>> algorithm from MAS5, and I routinely use the P/M/A calls from the
>> mas5calls() function in the affy package in conjunction with gcrma
>> values.
>>
>> Cheers,
>> Jenny
>>
>> At 01:14 PM 3/2/2011, Richard Friedman wrote:
>>> 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
>>>>
>>>> ______________________________________________________________________
>>>> The information in this email is confidential and
>>>> intend...{{dropped: 4}}
>>>>
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