I'm working on the DE analysis with DESeq2, here's my experimental design:
Genotype Time Replicates Wild_type 6hr 3 for each Wild_type 10hr Wild_type 12hr cht7 6hr cht7 10hr cht7 12hr CHT7HA 6hr CHT7HA 10hr CHT7HA 12hr
With the following code, I'm able to generate the result tables comparing two different groups of genotype+time (e.g. Wild_type_6hr_vs_cht7_6hr):
Salmon_dds <-DESeqDataSetFromTximport(gene_quant, colData = sampleTable, design = ~genotype + time + time:genotype) Salmon_dds$genotype <- factor(Salmon_dds$genotype, levels= c("Wild_type","cht7", "CHT7HA")) Salmon_dds$time <- factor(Salmon_dds$time, levels = c("6","10","12")) Salmon_dds$group <-factor(paste0(Salmon_dds$genotype, Salmon_dds$time)) design(Salmon_dds1) <- ~group results(Salmon_dds, contrast = c("group", "cht76", "Wild_type6"), tidy = TRUE)
If I understand correctly, the resulting table can help me to identify the DE genes in cht7_6 compared to wild_type_6.
However, I also want to pick a specific group and compare it to all of the groups to find the DE genes, e.g. genes in cht7_6hr which have a greater than 2-fold expression difference (and padj <0.05) from their mean expression of all samples (BaseMean). Is there any way to generate a table like this?
The reason for doing this is to to get a list of DE genes which are differentially expressed in at least one group across all groups so I can do the follow-up gene clustering.