I am analysing data generated on Arabidopsis plants. My experiment design is as follows:
condition treatment 1 FDR Female_insect 2 SAX Female_insect 3 FDR Male_insect 4 SAX Male_insect 5 FDR No_insect 6 SAX No_insect
The question I am trying to answer is: There are some genes which are known to induce in SAX plant compared to FDR in male treatment, but not induced in SAX compared to FDR in No insect (control) and female treatment.
I understand I can use following command in DESeq2
dds <- DESeqDataSetFromMatrix(countData = dataCountTable, colData = dataDesign, design = ~ condition) dds <- estimateSizeFactors(dds) countTable <- counts(dds, normalized=TRUE) dds <-DESeq(dds) dds$group <- factor(paste0(dds$treatment, dds$condition)) design(dds) <- ~ group dds <- DESeq(dds) resultsNames(dds) results(dds, contrast=c("group", "SAX", "male_insect"))
Similarly I can get DE genes for all other comparison. And can do venn diagram for overlap?
Is there any other way to answer this question. And can anyone please comment on the command above if this is right?
Any help would be appreciated. Thanks in advance.