[BioC] help needed with the design matrix

[Nair [guest]]

Hi All,

I am in the process of performing a DE of the RNA-seq data.

I have "paired" experimental design for a "treatment".In addition to this, I have 4 categorical explanatory variables. I am aiming to look for DE genes upon "treatment" which might be dependent upon these categorical variables. The design I used:

design<-model.matrix(~treat+pair+var1+var2, data=x )

When I tried to run "estimateGLMCommonDisp" using this design, I am getting the following error.

Error in glmFit.default(y, design = design, dispersion = dispersion, offset = offset,  : 
  Design matrix not of full rank.  The following coefficients not estimable:


Do you have any idea about a correct design matrix for this kind of setting in edgeR ?

Thanks a lot
Nair

 -- output of sessionInfo(): 



> sessionInfo()
R version 3.1.0 (2014-04-10)
Platform: x86_64-pc-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=fi_FI.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8    
 [5] LC_MONETARY=fi_FI.UTF-8    LC_MESSAGES=en_GB.UTF-8   
 [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
[1] lattice_0.20-29   gplots_2.13.0     VennDiagram_1.6.5 edgeR_3.4.2      
[5] limma_3.18.13    

loaded via a namespace (and not attached):
[1] bitops_1.0-6       caTools_1.16       gdata_2.13.3       gtools_3.3.1      
[5] KernSmooth_2.23-12


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