I'm dealing with a rather complex RNAseq experiment that follows a nested structure of the tested variables that could be represented like this:
SampleName tissue temp time dev_stage rep Sample1 crown 21 am ds1 rep1 Sample2 crown 21 am ds1 rep3 Sample3 crown 21 am ds1 rep4 Sample4 crown 21 am ds2 rep1 Sample5 crown 21 am ds2 rep2 Sample6 crown 21 am ds2 rep3 Sample7 crown 21 am ds2 rep4 Sample8 crown 21 am ds3 rep1 Sample9 crown 21 am ds3 rep2 Sample10 crown 21 am ds3 rep3 Sample11 crown 21 am ds3 rep4
From the several related posts related to experiment design on multifactor experiments, I came up with the design formula which looks like this:
exp.dds=DESeqDataSetFromMatrix(countData = counts_noZeros.df, colData = exp_coldata, design = ~0+tissue:temp:time:dev_stage)
I'm interested in determining the effect of these 4 variables on gene expression. For which I've 2 questions,
1) If I keep the design as is, is it correct that DESeq will account for a gene's expression considering a nested effect of these variables? In which case, is the model representation correct?
2) If I want to determine expression of only one of these variables should the design formula look something like this?
design = ~0+tissue
Any help is appreciated. With thanks.