Dear Bioconductor Community,
I have a workflow for multiple plates single-cell RNASeq that works as follows
- QC
- Use RUVSeq to eliminate library complexity bias from data (this works really well, with pre and post)
- Account for Zero Inflation using Zinbwave
- Model differential expression using DESeq with model: ~W_1 + group
I appreciate any comments on this, but this works very well, with improved ERCC estimates (better fit) and increased detection of known differentially expressed genes (two transgenes). (This is not the question)
I have multiple plates, and each is biologically different from the next (different age, region), however all have condition X and Y. My collaborator wants to merge some analysis. I am not sure that combining these plates is biologically entirely valid, but my collaborator insists that there is biological justification for this. This was obviously not planned, otherwise better batch design would have (possibly) overcome that. (Again not the question)
What I would like to therefore do is combine the plates. This is obviously possible at multiple stages, but I presume the following approach would be best:
- QC plates independently
- Use RUVSeq to obtain W_1 for each plate
- Run zinbwave on each plate
- Run a model that accounts for the batch such as: ~ group + age
Now using this approach, I have two or more W_1 terms that I don't know where to put? Obviously there may be alternative approaches that are better.
Many thanks,
Jakub
