Thanks for the reply. Both 1 & 2 can be accomplished in DESeq2. I am looking for a DESeq2 expert to help me set up the design and interaction terms.
Hoping for some help. I can't seem to wrap my brain around how I should set up my design in DESeq2. Here are the details, I have 6 samples from each patients. I have two patients. Each sample represents a different timepoint of treatment. For each patient I have 2 age-matched healthy controls. So I have 8 samples that correspond to patient 1 and 8 samples that correspond to patient 2. We want to do two things:
- Identify any DE miRNAs within a patient as a result of the treatment over time.
- Identfify any DE miRNAs between patients at any of the time points.
I'm also really not sure of how to incoroporate the controls. Any help is greatly appreciated.
2 answers
for 1: check maSigpro. for 2: any DE analysis package can do it.
ok, i see. But all these information should be found in DESeq2 manual.
I actually consider myself very well-versed with the DESeq2 manual and vignettes. Although there is a vignette that describes time course analysis using the Fission dataset I am having a difficult time relating it to my specific conditions. This is why I am reaching out to the community looking for a DESeq2 expert.
Is it reasonable to use the design below to identify DEmiRNAs between patients?:
ddsHTSeq1 <-DESeqDataSetFromHTSeqCount(sampleTable=sampleTable, directory=directory, design = ~ Time + Patient)
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