I have an experimental set up as described below.
cell dex S.control1 s1 control S.control2 s2 control Scontrol3 s3 control S.condition1.1 s4 Sus S.condition1.2 s5 Sus S.condition1.3 s6 Sus S.condition2.1 s7 Sus1 S.condition2.1.1 s8 Sus1 S.condition2.1.2 s9 Sus1 R.control1.1 s10 R1_ctrl R.control1.2 s11 R1_ctrl R.control1.2.1 s12 R1_ctrl R.condition1.1 s13 R1 R.condition1.2 s14 R1 R.condition1.3 s15 R1 R.control2.1 s16 R2_ctrl R.control2.2 s17 R2_ctrl R.control2.2.1 s18 R2_ctrl R.condition2.1 s19 R2 R.condition2.2 s20 R2 R.condition2.3 s21 R2
I have same one control for all Susceptible (S) where are there are two resistance (R1 & R2) for which i have two different controls. because resistance species are different but the comparison i have is for the orthologous genes between all the three species. My idea is to compare between the control Vs. treated for each conditions but also mainly to understand the genes that are differentially expressed from S Vs R. Ainc ei know they share the same function, i would like to know which ones are different?
what i tried so far is
dat= read.csv("test_eff_counts.csv", header = TRUE, row.names = 1) coldata<-data.frame(row.names=colnames(dat),cell=paste0("s", 1:21), dex= c(rep('control', 3), rep('Sus',3), rep('Sus1',3),rep('R1_ctrl',3),rep('R1',3),rep('R2_ctrl',3), rep('R2',3))) coldata$cell<-factor(coldata$cell,ordered = T) coldata$cell dds <- DESeqDataSetFromMatrix(countData = round(dat), colData = coldata, design = ~ dex) nrow(dds) dds <- dds[ rowSums(counts(dds)) > 1, ] #remove zero rows dds<- DESeq(dds) results(dds,contrast = c("condition","control","Sus")) (continued for all four treated of control vs, treated)
This just give me pair wise comparisons. but how do i understand the genes that are differentially expressed from S Vs R
Any help would be greatly appreciated!!!! :(