Closed andreahanel closed 3 months ago
@andreahanel, regarding the metacells assignment of each cell
, do you mean a hard assignment or a probability assignment. For the former, you can treat each metacell as a cell type in a broad sense during CellTypist training. For the latter, I am afraid the current algorithm does not take this into account (i.e., each cell only has one unique identity). Please let me know if I misunderstand your question.
@ChuanXu1 Do you mean, can I use the results of SEACell (merged Metacell matrix with cell type annotations) as input for celltypist reference set training? Now I have a very large scRNA dataset that I want to use as a reference. I have used SEACell to calculate metacells according to each celltypes. Should I use single-cell downsampled data as the input for training or metacells?
@YH-Zheng, theoretically you need a cell-by-gene matrix for model training, with each cell annotated as cell type or meta cell type.
This should be answered. Please reopen this issue if you have further questions.
Hello, Do you see it as possible to use metacells (created by e.g. SEACells or MetaCell) to potentially improve annotation performance? I understand if direct use of metacells is suboptimal for a classifier trained on single cells; though could be the information about the metacells assignment of each cell be introduced into the majority-voting step? Thank you!