[BioC] Agilent G4112A Arrays

[Chuming Chen]

Hi Francois:

The experiment was done five years old. I am just trying to do some 
analysis.

This experiment was performed on human colonic crypts.  They were 
microdissected into two parts - the top 9/10 and the bottom 1/10.  Thus 
in my target file, T or B stands for top or bottom and the number after 
it represents patients 1-5. I guess it belongs to the strange one you 
mentioned.

I am trying to find out the differentially expressed genes for at least 
B1 vs T1, B2 vs T2 etc. There is probably no way to find out the 
differentially expressed genes for other pairs of contrasts.

Thanks,

Chuming

francois at sus.mcgill.ca wrote:
> Hi Chuming,
>
> Would you mind explaining a bit more what the samples are? What you are
> describing below is either a very simple experiment with 5 biological
> replicates or a rather strange one that tries to test 5 conditions at the
> same time with 5 different controls.
>
> If the former, then you can set up your design matrix to show this. You
> would lose the matched nature of your data, but you should get some decent
> results using limma.
>
> If the latter, then whatever statistics you would do on the M values would
> be a bit strange as they would all represent different treatments.
>
> Francois
>
>   
>> Hi Prashantha,
>>
>> Thank you for your suggestion. My target file is as below. Although I
>> couldn't fit a linear model, I still wonder whether I can do some
>> statistic on M (log ratio) values and use the p-value to get the
>> differentially expressed genes.
>>
>> SlideNumber    FileName    Cy3    Cy5
>> 1    B1vsT1.txt    B1    T1
>> 2    B2vsT2.txt    B2    T2
>> 3    B3vsT3.txt    B3    T3
>> 4    B4vsT4.txt    B4    T4
>> 5    B5vsT5.txt    B5    T5
>>
>> Chuming
>>
>>
>> Prashantha Hebbar wrote:
>>     
>>> Dear Chen,
>>>
>>> You need not to look for any other packages. Since, you do not have
>>> any replicates, do not fit linear model, instead just do normalization
>>> with in arrays and look at the M (log ratio) values.
>>>
>>> Regards,
>>>
>>> Prashantha Hebbar Kiradi,
>>> Dept. of Biotechnology,
>>> Manipal Life Sciences Center,
>>> Manipal University,
>>> Manipal, India
>>>
>>>
>>> --- On *Mon, 1/25/10, Chuming Chen /<chumingchen at gmail.com>/* wrote:
>>>
>>>
>>>     From: Chuming Chen <chumingchen at gmail.com>
>>>     Subject: [BioC] Agilent G4112A Arrays
>>>     To: bioconductor at stat.math.ethz.ch
>>>     Date: Monday, January 25, 2010, 6:32 AM
>>>
>>>     Dear All,
>>>
>>>     I am trying to find out the differentially expressed genes from
>>>     some Agilent Human Whole Genome (G4112A) Arrays data.
>>>
>>>     I have tried LIMMA package, but LIMMA gave the error message "no
>>>     residual degrees of freedom in linear model fits" and stopped. My
>>>     guess is that my data has no replicates in the experiment.
>>>
>>>     Is there any other packages I can use to find differentially
>>>     expressed genes which does not require replicates in the experiment?
>>>
>>>     Thanks for your help.
>>>
>>>     Chuming
>>>
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