Hi All,
I have 3 different experiments with 3 biological controls and 3 biological treatments set per experiment. I have done three separate DESeq2 analysis per experiment, which will normalize based on the comparison data sets.
Example:
gene,E1_C1,E1_C2,E1_C3,E1_T1,E1_T2,E1_T3,
etc ....
I was wondering what would be the best strategy to normalize all the data sets together and then do comparisons.
My counts table looks like this:
gene,E1_C1,E1_C2,E1_C3,E2_C1,E2_C2,E2_C3,E3_C3,E3_C2,E1_C3,E1_T1,E1_T2,E1_T3,E2_T1,E2_T2,E2_T3,E3_T1,E3_T2,E3_T3,
The comparison will be like:
E1_C vs E1_T
E2_C vs E2_T
E3_C vs E3_T
But I would like to do the normalization of the data set in the beginning. Is there any parts of DESeq2 that will allow me to do the comparisons separately post normalization?
dds <- DESeq(dds)
Another thought I had was to get output the normalized counts and used those for the differential gene expression analysis via DESeq2? Would that be a better strategy? If so how should I go about that? I know DESeq2 can not take normalized counts for its input and only raw counts are required....
Thank you for the help in advance.
