**140**wrote:

Greetings,

I need to analyze data collected from an RNA-seq experiment. This consists of comparing two groups (control vs. treatment) and repeated sampling (1 hour, 2 hours, 3 hours). If this were a univariate problem I know I would use a 2-way rmANOVA analysis but this is RNA-seq and I have thousands of variables. I am very familiar with multiple packages for RNA differential expression analysis (e.g. DESeq2, edgeR, limma, etc.) but I have been unable to figure out what the most appropriate way to analyze such data in this circumstance. The closest answer I can find within the DESeq2 and edgeR manuals (limma is somewhat confusing to me) is to place to main treatment of interest at the end of the design formula, for example:

design(dds) <- formula(~ time + treatment)

Is this what is considered the appropriate way to address repeated measures in mRNA expression experiments? Any thoughts are appreciated.

Regards,

--

Charles Determan

Integrated Biosciences PhD Candidate

University of Minnesota

**37k**• written 5.8 years ago by Charles Determan Jr •

**140**

Charles,

I am looking to do a similar analysis. What was the final method you ended up using to do your repeated measures analysis?

Cheers,

Nate

0This question was continued and answered on a later thread, see: Repeated Measures mRNA expression analysis II

37k