Hello seasoned bioinformaticians and biologists:
I am really new to bioinformatics and I am trying to use DESeq2 to perform differential expression analysis for my data. I have muscle RNA sequences from 60 individuals at 7 different time points (420 samples total). Running through DESeq2 with the following workflow:
dds <- DESeqDataSetFromMatrix(countData = countData, colData = colData, design = ~ timepoint, tidy = TRUE)
I can generate DEGs between specific time points with:
res <- results(dds, contrast=c("timepoint","t1","t2"))
However, I am wondering if the p-values for each gene generated in the results table are the result of a paired comparison (personx@timepoint1 v.s. personx@timepoint2 for all individuals) or a mean comparison (average expression of the gene for all individuals@timepoint1 v.s. same type of average@timepoint2). To me, it seems like this difference in the analysis method is similar to the comparison between a paired t-test vs. a t-test. I am really trying to optimize the pipeline so it is aware of the variability in gene expression between individuals by NOT comparing averages across time points while retaining the real DEGs.
Now I have found a potential solution here from the DESeq2 tutorial:
Can I use DESeq2 to analyze paired samples?
Yes, you should use a multi-factor design which includes the sample information as a term in the design formula. This will account for differences between the samples while estimating the effect due to the condition. The condition of interest should go at the end of the design formula, e.g.~ subject + condition.
I am wondering if adding additional information about individual ID for each RNA-seq sample and adding it as "subject" in the design formula, will DESeq2 use a comparison method more similar to a paired t-test than the current method I am using where the design formula is only the timepoints? I would love to have some input from someone with experience analyzing time series RNA-seq data where measurements were taken for each individual at each time points were taken. Thank you in advance!
