Question: RNASeq fold change analysis after subtraction of contaminating MEF signal
gravatar for gpalidwor
8 days ago by
gpalidwor0 wrote:

I have a set of Mouse RNASeq data for various points of a differentiation time series, with replicates. A known fraction of the cells in each sample are Mouse Embryonic Fibroblasts (MEFs), that fraction varies quite a bit per sample. I have expression data for a pure MEF sample grown under similar conditions.

I'd like to do a fold change analysis between time points, subtracting the MEF expression contamination in such a way that the resulting increased variance per gene is factored into the fold change analysis.

It seems it may be possible to do it within DESeq2 or using svaseq but I can't figure out how. Can anyone recommend a strategy for doing this; I'm really not clear on how to approach it.


(note this is a crosspost from Biostars, as I wasn't able to get a solution there)

ADD COMMENTlink modified 7 days ago by Michael Love13k • written 8 days ago by gpalidwor0
gravatar for Michael Love
7 days ago by
Michael Love13k
United States
Michael Love13k wrote:

Hi, when you say you have known fraction, do you mean you can give a measured, numeric value for each sample? Or just that you know that some amount will be MEF but you don't know that amount.

ADD COMMENTlink written 7 days ago by Michael Love13k

By "known fraction" I mean I can give a measured numeric value for each sample based on the number of cells. 


ADD REPLYlink written 7 days ago by gpalidwor0

So you could put it in the model as a numeric covariate (you don't do anything special just put it in the design). This however assumes the relationship with expression is log linear (so linear with log expression). You probably want linear with expression though. You can try transforming the MEF variable before putting it in the design, if you expect a certain relationship.

ADD REPLYlink written 7 days ago by Michael Love13k

Thanks! I'll give it a try and post this reply on Biostars.

ADD REPLYlink written 6 days ago by gpalidwor0
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