Open agave82 opened 2 years ago
I have this same query: How do we compare groups of biological replicates?
In the vignette, there is only an example of how to compare groups of technical replicates (Ubi4_vs_Ubi6, Ubi4_vs_Ctrl, Ubi4_vs_Ubi1, Ubi6_vs_Ctrl, Ubi6_vs_Ubi1, Ctrl_vs_Ubi1) but how do you compare all Ubi samples with Ctrl? We could treat biological replicates (Ubi1, Ubi4, Ubi6) in the same way as technical replicates by giving them a replicate number 1 to 9 and the same condition name, but this is not ideal as limma is unaware that each biological replicate is in triplicate.
label | condition | replicate | technical_replicate |
---|---|---|---|
Ubi4_1 | Ubi | 1 | 1 |
Ubi4_2 | Ubi | 2 | 2 |
Ubi4_3 | Ubi | 3 | 3 |
Ubi6_1 | Ubi | 4 | 1 |
Ubi6_2 | Ubi | 5 | 2 |
Ubi6_3 | Ubi | 6 | 3 |
Ubi1_1 | Ubi | 7 | 1 |
Ubi1_2 | Ubi | 8 | 2 |
Ubi1_3 | Ubi | 9 | 3 |
Ctrl_1 | Ctrl | 1 | 1 |
Ctrl_2 | Ctrl | 2 | 2 |
Ctrl_3 | Ctrl | 3 | 3 |
I saw in a related issue https://github.com/arnesmits/DEP/issues/11#issuecomment-782045411 that you could treat the technical replicate as a batch effect and adjust for the technical replicate in the design with ~0 + technical_replicate + condition
.
Is there any better solutions @arnesmits @adomingues @agave82 ?
Many thanks, Oliver
To my knowledge I think you covered most of it @ojziff.
The only other solution I can think of, and I have seen done / suggested, is to average the technical replicates before doing the differential analysis with DEP. It's a rough approach, but it the replicates are well correlated it should be fine.
Hi, I have an experimental design as follows:
WT_1 WT_2 WT3 WT_4 KO_1 KO_2 KO_3 KO_4
_1 and _2 are biological replicates while _3 and _4 are technical replicates.
Please, can you explain how to handle technical and biological replicates in DEP? I understand that I can utilise the option type="all" to make pairwise comparisons: data_diff_all_contrasts <- test_diff(data_imp, type = "all") I hav e done that but would that be enough to take into account the replicates or do I need add the design_formula option in the code? If design_formula needs to be include please, can you explain how to do in my case of experimental design? Thank you very much