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Old 02-10-2015, 07:00 AM   #1
evenstar
Junior Member
 
Location: the Netherlands

Join Date: Apr 2013
Posts: 1
Unhappy DESeq2 design error

Hi,

I am trying to run DESeq2 using the "Differential analysis of count data ~ the DESeq2 package provided in the bioconductor website. I want to do an Multi-factor design. I created my count files using HTseq and created a combined table from all the count files.

However I am running in the following error after this step:

Code:
> dds <- DESeqDataSetFromMatrix(countData = countDATA,
                             colData = coldata,
                             design = ~ condition + treatment )
Error in DESeqDataSet(se, design = design, ignoreRank) : 
  the model matrix is not full rank, so the model cannot be fit as specified.
  one or more variables or interaction terms in the design formula
  are linear combinations of the others and must be removed
If I try to run the function using only design = ~ condition everything works just fine.

my coldata table:
Code:
row.names	condition	type	treatment	autoAntibodies
HS06	        0	0	0	0
HS07        	0	0	0	0
HS10        	0	0	0	0
HS15	        0	0	0	0
HS16	        0	0	0	0
HS17	        0	0	0	0
RITIS01	1	2	1	1
RITIS02	1	2	2	1
RITIS07	1	2	1	1
RITIS09	1	1	1	2
RITIS10	1	2	2	1
RITIS12	1	1	1	2
RITIS14	1	2	1	1
RITIS16	1	1	1	1
I would like to create a full design which takes all the factors into account (condition, type, treatment and autoAntibodies). Could you please explain why the above design does not work.

Thanks,
Even
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Old 02-10-2015, 02:09 PM   #2
dpryan
Devon Ryan
 
Location: Freiburg, Germany

Join Date: Jul 2011
Posts: 3,480
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If "type", "treatment", and "autoAntibodies" are factors, then "condition" is dictated by them.
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countdata, deseq2, rna seq experiment design

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