[BioC] Patricia's simpleaffy question

alex lam (RI) alex.lam at bbsrc.ac.uk
Fri Jan 18 14:20:17 CET 2008


 Dear Patricia,
Please do not hijack a thread and ask a different question to the subject line.

How many genes depends on your arrays quality and the biology of your experiment. There will be some genes that are silent across all of the conditions. Why don't you plot the mean expression and variance of all probesets to see what those distributions look like?

RMA is generally regarded as better than MAS5.

Cheers,
Alex

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-----Original Message-----
From: bioconductor-bounces at stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Patrícia Luiza Nunes da Costa
Sent: 18 January 2008 12:50
To: bioconductor at stat.math.ethz.ch
Subject: Re: [BioC] Disorderly duplicate spots

Friends,

We used an Affymetrix microarray with about 45 000 genes. We have 4 groups with 3 arrays.
How many genes should I except after par wise filtering (simpleaffy)?  I know it depends on the parameters and stringency, but I want to know an average, or the minimum, to perform a statistical analysis.
What algorithm do you think its better: RMA or MAS 5?

Thanks and regards,

Patrícia






> Hi Naomi & Jim,
>
> thanks for your replies!
> I'll look into doing something along the same lines as you did Naomi.
>
> Have a wonderful weekend,
>
> Yannick
>
> On Jan 17, 2008, at 16:00 , Naomi Altman wrote:
>
>> Dear Yannick,
>> On the whole, most people have equal numbers of duplicates for each 
>> gene, and can use the methods discussed in limma.
>>
>> However, we had a situation similar to yours.
>>
>> First, we did a graphical analysis to determine if the expression 
>> profile of a clone set was fairly parallel over the arrays.  A 
>> parallel profile indicates that the assessment of differential 
>> expression will be the same for any clone.  (Almost all of ours were, 
>> and we suspect that some of the others were possibly assembly
>> errors.)  Then we picked the clone that was at a reasonably high 
>> quantile of the expression distribution.  i.e. we did not pick the 
>> most highly expressed clone, in case this was due to some type of 
>> error.  We picked the median, or the clone at the 75th percentile etc.
>>
>> --Naomi
>>
>> At 07:48 AM 1/17/2008, Yannick Wurm wrote:
>>> Dear List,
>>>
>>> I am a graduate student working with the fire ant Solenopsis invicta.
>>> We did some two-color cDNA microarrays that I've begun analyzing 
>>> with limma. But something feels wrong about how I'm doing things: we 
>>> printed whole clones from a ~25,000 clone cDNA library onto our 
>>> microarray. Simultaneously, we sequenced our clones. They assemble 
>>> to ~12,000 transcripts. Many are singlets, but some transcripts are 
>>> represented by multiple clones (one transcript is represented by 32 
>>> clones!).
>>>
>>> So during analysis, treating each clone as independent feels wrong.
>>> It means:
>>>         - correcting for 25,000 multiple tests rather than 10,000, 
>>> thus reducing my power;
>>>         - and not taking into account the technical replication we 
>>> get by multiple spots on the array.
>>>
>>> The limma manual has a section on Within-Array Replicate Spots. But 
>>> only mentions what to do for people who have a single duplicate of 
>>> every spot on their array.
>>>
>>> I'm sure other people have had to deal with this in the past. Do you 
>>> have any pointers?
>>>
>>> Thanks & regards,
>>>
>>> Yannick
>>>
>>>
>>> --------------------------------------------
>>>           yannick . wurm @ unil . ch Ant Genomics, Ecology & 
>>> Evolution @ Lausanne
>>>    http://www.unil.ch/dee/page28685_fr.html
>>>
>
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Patrícia Luiza Nunes da Costa
Laboratório de Oncologia Experimental, Grupo de Adesão Celular Faculdade de Medicina da Universidade de Paulo-FM USP Av. Dr. Arnaldo, 455 sala 4112 Cerqueira Cesar Cep 01246-903
Tel: (11) 3061-7486 e (11) 8202-7073



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