I am currently working in plant pathogen interaction and is trying to make a gene co-expression network using RNA-seq data. I used HTseq-count to get the read counts.
My dataset consist of Resis_treated (1st day, 3rd day and 7th day) samples taken under 3 time point with 2 replicated for each time point. I have a factor with 3 levels
condition Day1 Day1 Day3 Day3 Day7 Day7
I am trying to get the DEGs between Day3_Vs_Day1, Day7_VsDay1 and Day7_Vs_Day3. The code I used is as follows
library(DESeq2) directory<-'D:/test_deseq/tempora' sampleFiles<-grep('Day',list.files(directory),value=TRUE) sampleCondition<-c('Day1','Day1','Day3','Day3', 'Day7','Day7') sampleTable<-data.frame(sampleName=sampleFiles, fileName=sampleFiles, condition=sampleCondition) ddsHTSeq<-DESeqDataSetFromHTSeqCount(sampleTable=sampleTable, directory=directory, design=~condition) colData(ddsHTSeq)$condition<-factor(colData(ddsHTSeq)$condition, levels=c('Day1','Day3','Day7')) colData(ddsHTSeq) ddsHTSeq <- ddsHTSeq[ rowSums(counts(ddsHTSeq)) > 1, ] ddsHTSeq dds <- DESeq(ddsHTSeq) resultsNames(dds)  "Intercept" "condition_Day3_vs_Day1" "condition_Day7_vs_Day1"
But, how do I get all pairwise combinations of all levels? ie; condition_Day7_vs_Day3 along with the other two combinations
Will LRT test give a good all_vs_all level comparison, If so how I should design the DEseq2 condition for it.