[BioC] issue with limma?

[Wei Shi]

Hi Kripa,

Yes, the subset order has to be the same with that in your target file. Otherwise you will be comparing wrong samples.

BTW, limma has its own normalization function for normalizing Illumina BeadChip data. Have a look at the neqc function in limma.

Cheers,
Wei

On Dec 1, 2011, at 9:20 AM, Kripa R wrote:

> 
> Hello forum,
> Outline of my analysis: lumi for pre-processing and filtering, then i take a subset of the normalized group and run this through limma. 
> I've noticed that if i select my subset differently, the topTable generated after limma differs. ie rather than select=c(1,2,3,4,5,6) it is changed to select=c(1,4,3,2,5,6)  the final topTable differ although the samples input are actually identical
> Does this mean that the subset order must be identical to that in the targets file? Or have I missed something in my current limma code (see below)? 
> I believe I'm currently lacking a line which would indicate which sample fits in each spot of the model.matrix, if that makes sense? 
> 
> Any help would be greatly appreciated!!
> 
> 
> example of my code.
> subset <- subset(selDataMatrix, select=c(1,2,3,4,5,6)); 
> 
> targets<-read.csv("targets.csv", skip=7);
> targets
> Sample_Name   Sample_Group   Pairs   Sentrix_ID   Sentrix_Position
> 1                       T                      1         
> 2                       C                      2
> 3                       C                      1
> 4                       T                      2
> 5                       T                      3
> 6                       C                      3
> 
> 
> clinical <- factor(targets$Sample_Group);
> individual <- factor(targets$Pairs);
> 
> design <- model.matrix(~1+clinical+individual)
> #design headers appear are as followe: (Intercept)    clinicalT   individual2   individual3
> 
> fit <- lmFit(subset, design);  
> ebayes <- eBayes(fit); 		 	   		  
> 	[[alternative HTML version deleted]]
> 
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