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:
If I try to run the function using only design = ~ condition everything works just fine.
my coldata table:
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
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
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
Thanks,
Even
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