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Issues with interpretation of DESeq2 time series analysis results

Dear colleagues, My research dedicated to transcriptomic analysis of regeneration process in two different sites (Head and Tail) of one invertebrate animal. Experiment design includes RNA-seq data from different time point: 0, 4, 12, 24, 48 and 96 hours. DESeq2 library was used to differential expression analysis:

samps <- read.csv2("Samples_and_conditions.csv")
samps$Site <- factor(samps$Site) 
samps$TPA <- factor(samps$TPA) 
samps$Replicates <- factor(samps$Replicates) 
files <- file.path(samps$X, "quant.sf")
txi.tx <- tximport(files, type="salmon", txOut = TRUE)
ddsTxi <- DESeqDataSetFromTximport(txi.tx, colData=samps, design = ~ Site + TPA + Site:TPA)
dds <- ddsTxi[rowSums(counts(ddsTxi)) > 10, ] 
dds$TPA <- relevel(dds$TPA, ref="0") 
dds <- DESeq(dds, test="LRT", reduced=~Site + TPA)
res <- results(dds)

And I have several questions: 1) Do I understand correctly that function “relevel” sets as a reference point only 1 time point (0 hours) in one site (in my case, Head)? Or will each site have its own reference (0 hours in Head and 0 hours in Tail)?

2) How I should intepretate Sitetail.TPA*(4,12,24,48,96) in output table and heatmaps? If I understand analysis right, these values are log2 fold changes of expression in Tail at *(4, 12,24,48,96) time point regarding to *(4,12,24,48, 96) time point in Head. Please, correct me if I wrong.

3) If I want to find genes which demonstrate differential expression in Tail at any time point regarding to 0 hour in Tail, should I use, for example, next command: results(dds, contrast=list(c(“TPA_4_vs_0”, “Sitetail.TPA4”))) ?

I will be grateful for any help!

deseq2 lrt rna-seq

Is there a specific reason you use txOut = TRUE instead of aggregating the transcripts to gene level? DESeq2 is intended for gene rather than tx-level analysis.

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