[BioC] question about design for limma time course, 2 conditions and drug treatment microarray experiment

Ninni Nahm [guest] guest at bioconductor.org
Fri Nov 22 16:03:02 CET 2013

Dear list,

I have a conceptual question about creating a design matrix for a more complicated experimental design. 

I have microarray data of 
- two different conditions (treatment/control), 
- over a series of time points (20, 45, 90, 180 minutes) 
- and different dose concentrations of a certain drug (no treatment, 1mg, 2mg, 3mg, 4mg, 5mg). 
- and I have 2 replicates per drug, time point, and condition 
I think, I know how to do it when I want to consider time only (please correct me when I'm wrong!):

## find genes which change over time differently between the treatment and the control.

cont.dif <- makeContrasts(
Dif1  = (treatment_1mg_tp45-treatment_1mg_tp20)-(control_tp45-control_tp20),
Dif2  = (treatment_1mg_tp90-treatment_1mg_tp45)-(control_tp90-control_tp45),
Dif3  = (treatment_1mg_tp180-treatment_1mg_tp90)-(control_tp180-control_tp90),

However, I would like to know which genes are changing over time and drug exposure between control and treatment. 
Would I have to do the contrasts for every dose? 

Any help is much appreciated!


 -- output of sessionInfo(): 

> sessionInfo()
R version 3.0.2 (2013-09-25)
Platform: x86_64-pc-linux-gnu (64-bit)

 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            

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

other attached packages:
[1] sva_3.8.0     mgcv_1.7-27   nlme_3.1-113  corpcor_1.6.6 limma_3.18.3 

loaded via a namespace (and not attached):
[1] grid_3.0.2      lattice_0.20-24 Matrix_1.1-0   

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