[BioC] Agilent G4112A Arrays

[Chuming Chen]

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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