Thank you Devon Ryan. Yes. you are right that I need to remove complete column and use the contrasts function. Answer is provided here. https://support.bioconductor.org/p/85502/#85519
design matrix for complicated experimental design in limma
Hi,
I am working with microarray data and its experimental design is bit strange. I have 20 samples (expression at 5 time points, at 1 hr with 3 replicates, 2 hr with 4 replicates, 3 hr with 3 replicates, 6hr with 6 replicates and 10hr with 4 replicates).
I want to find the DEGs at each time point vs rest of time points. For instance,
DEGs at 1 hr vs rest of all time points (2, 3, 6, 10)
DEGs at 2 hr vs rest of all time points (1, 3, 6, 10)
DEGs at 3 hr vs rest of all time points (1, 2, 6, 10) etc..
My design matrix is as follows:
complete hr1 hr2 hr3 hr6 hr10
1hr:rep1 1 1 0 0 0 0
1hr:rep2 1 1 0 0 0 0
1hr:rep3 1 1 0 0 0 0
2hr:rep1 1 0 1 0 0 0
2hr:rep2 1 0 1 0 0 0
2hr:rep3 1 0 1 0 0 0
2hr:rep4 1 0 1 0 0 0
3hr:rep1 1 0 0 1 0 0
3hr:rep2 1 0 0 1 0 0
3hr:rep3 1 0 0 1 0 0
6hr:rep1 1 0 0 0 1 0
6hr:rep2 1 0 0 0 1 0
6hr:rep3 1 0 0 0 1 0
6hr:rep4 1 0 0 0 1 0
6hr:rep5 1 0 0 0 1 0
6hr:rep6 1 0 0 0 1 0
10hr:rep1 1 0 0 0 0 1
10hr:rep2 1 0 0 0 0 1
10hr:rep3 1 0 0 0 0 1
10hr:rep4 1 0 0 0 0 1
Is this design matrix correct as per my DEGs comparison?
Moreover, I am getting this error/warning as Warning message:
" Partial NA coefficients for 20214 probe(s) ".
Can anyone help me what's wrong with my design matrix?
Thank you.
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Either get rid of the 'complete' column or one of the time points. I recommend the former if you're going to use contrasts.
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Please can you add the code you used to create the design matrix, along with a phenotype table.
Thank you. I got the answer from bioconductor. Link is provided here. https://support.bioconductor.org/p/85502/#85519