[BioC] Agilent G4112A Arrays

[Francois Pepin]

Hi Cunming,

I see. You will indeed be stuck at looking at M values for any single  
patient.

One way would be to put them all in limma first to get some basic  
statistics and then just look at the M values for the pairs of  
interest. Then you can ask for say how many have an M value over a  
given threshold or something like that.

Francois

On Jan 25, 2010, at 9:50 AM, Chuming Chen wrote:

> 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
>>>>
>>>>    _______________________________________________
>>>>    Bioconductor mailing list
>>>>    Bioconductor at stat.math.ethz.ch
>>>>    </mc/compose?to=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
>>>>
>>>>
>>>>
>>> _______________________________________________
>>> 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
>>>
>>>
>>
>>
>>
>>