Hi I am analyzing a RNAseq experiment with 2 factors,
I have been reading vignettes and other questions but I am still confused on what to do
donor(genotype) with 2 levels "WT" and "imKO", condition with 3 levels "naive" "cisplatin" and "cispAIBP",
design = ~donor +condition + donor:condition
and my ref levels,
dds$condition <- relevel( dds$condition, ref="naive" )
dds$donor <- relevel(dds$donor, ref="WT"),
ddsCollapsed <- DESeq(ddsCollapsed)
- I want to know if there is an effect of conditions in each genotype (main effect)?
res_cisp <- results(ddsCollapsed, test= "Wald", contrast=c("condition", "cisplatin", "naive"), alpha=.05) head(res_cisp) res_AIBP <- results(ddsCollapsed, test="Wald", contrast=c("condition", "cispAIBP", "cisplatin"), alpha=.05) head(res_AIBP)
However, If I do this how can I extract or compare the DEGs in only one genotype, for instance, WT?, I don't want to know the effect of each condition regardless of genotype but most the effect inside each genotype level. will the idea below work? I understand rescisp and resAIBP are comparisons of my first level (WT) and then for other genotype:
res_cisp_KO <- results(ddscollapsed, test="Wald", contrast=list( c("condition_cisplatin_vs_naive","donor_imKO.condition_cisplatin") )) res_AIBP_KO <- results(ddscollapsed, test="Wald", contrast=list( c("condition_cispAIBP_vs_cisplatin","donor_imKO.condition_cispAIBP") ))
however, my results are not computing
should i relevel my condition factor? in which case, should I create a second dds "ddsCollapsed2" with the new levels using cisplatin as reference and run DESeq to extract resAIBPKO ?
> resultsNames(ddsCollapsed)  "Intercept" "donor_imKO_vs_WT"  "condition_cisplatin.it.AIBP_vs_naive" "condition_cisplatin.it.saline_vs_naive"  "donorimKO.conditioncisplatin.it.AIBP" "donorimKO.conditioncisplatin.it.saline"
I think using a grouping variable might be an easier way to do it. but then the other question that I have is to know if there is a difference in condition effect across genotype, and that is why I included the interaction in the design. ,
it seems like my DESeq function results without arguments
res <- results(ddsCollapsed) is doing it
but again, I don't know how to extract "donorimKO.conditioncisplatin.it.AIBP" "donorimKO.conditioncisplatin.it.saline" DEGs., based on
?results I think the following might work. but I don't really understand why.
i don't think I understand resultsName output either Bytheway
res_cisp_ko_vs_wt <- results(ddsCollapsed, name="donor_imKO.condition_cisplatin") res_AIBP_ko_vs_wt <- results(ddsCollapsed, name="donor_imKO.condition_cispAIBP")
resAIBPkovswt in this case is comparing AIBP effect but taking the first level "naive" as reference right? should I relevel?
and I also want to compare "donorimKO _vsWT" but at condition "naive" which is the reference level. is this the comparison in
resultsNames(ddsCollapsed) ? If not I don't know how to do it. and I think the grouping variable will help here too.
can I use 2 different designs so I can do the grouping for my comparison and then including the interaction for the genotype effect on the main condition effect? OR I should do an LRT instead and in that case which should be my
I appreciate any help,