Hi all.
I have a complex experiment that I try to analyse, and I am not sure how to go about it. I have performed RNA-seq experiments in my cells under two different conditions, starved and stimulated, and I wanted to see how gene expression changed. I repeated the experiment after knocking-down a transcription factor that might influence the response to starvation-stimulation. So, I designed shRNA for this factor, and I performed RNA-seq experiments again under starvation and after stimulation. On top of that, I prepared libraries of cells treated with scramble RNA under and after stimulation. All experiments were performed 3 times and analysed with DESeq2.
Each repeat of this experiment was prepared with each own scramble library. I noticed that I needed to "normalise" each treated sample to its own control. I did this by including a 'prep' group, grouping together all libraries prepared on the same day and sequenced together.
I analysed the data using this DESeq2 design:
Sample Treatment Prep Condition
shRNA-1 treated A Starved
shRNA-2 treated B Starved
shRNA-3 treated C Starved
scr-1 control A Starved
scr-2 control B Starved
scr-3 control C Starved
shRNA-1 treated A Stimulated
shRNA-2 treated B Stimulated
shRNA-3 treated C Stimulated
scr-1 control A Stimulated
scr-2 control B Stimulated
scr-3 control C Stimulated
design= ~ Prep + Treatment
This was done per condition (i.e. one analysis for starved samples, one for stimulated samples). This analysis gave me a few interesting things, but I would like now to see how the expression levels change from starvation to stimulation for my shRNA-treated cells, after some kind of normalisation to the scramble samples. I tried using the following design:
design= ~ Prep + Treatment + Condition
but I am not sure that this makes sense. At least the gene list I am getting does not make much sense. Is there something wrong with using both Prep and Treatment as blocking factors?
Any suggestion whatsoever will be much appreciated.
I have a complex experiment that I try to analyse, and I am not sure how to go about it. I have performed RNA-seq experiments in my cells under two different conditions, starved and stimulated, and I wanted to see how gene expression changed. I repeated the experiment after knocking-down a transcription factor that might influence the response to starvation-stimulation. So, I designed shRNA for this factor, and I performed RNA-seq experiments again under starvation and after stimulation. On top of that, I prepared libraries of cells treated with scramble RNA under and after stimulation. All experiments were performed 3 times and analysed with DESeq2.
Each repeat of this experiment was prepared with each own scramble library. I noticed that I needed to "normalise" each treated sample to its own control. I did this by including a 'prep' group, grouping together all libraries prepared on the same day and sequenced together.
I analysed the data using this DESeq2 design:
Sample Treatment Prep Condition
shRNA-1 treated A Starved
shRNA-2 treated B Starved
shRNA-3 treated C Starved
scr-1 control A Starved
scr-2 control B Starved
scr-3 control C Starved
shRNA-1 treated A Stimulated
shRNA-2 treated B Stimulated
shRNA-3 treated C Stimulated
scr-1 control A Stimulated
scr-2 control B Stimulated
scr-3 control C Stimulated
design= ~ Prep + Treatment
This was done per condition (i.e. one analysis for starved samples, one for stimulated samples). This analysis gave me a few interesting things, but I would like now to see how the expression levels change from starvation to stimulation for my shRNA-treated cells, after some kind of normalisation to the scramble samples. I tried using the following design:
design= ~ Prep + Treatment + Condition
but I am not sure that this makes sense. At least the gene list I am getting does not make much sense. Is there something wrong with using both Prep and Treatment as blocking factors?
Any suggestion whatsoever will be much appreciated.
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