I have a scRNAseq dataset (Smartseq2-method), below called the query dataset, that I want to annotate the cell types in. I have a good quality reference dataset, also with Smartseq2-methodology. I'm using Seurat mainly for my analysis. Seurat provides a cell type classification tool for this purpose (well described tutorial https://satijalab.org/seurat/articles/integration_mapping.html, and the article https://www.cell.com/cell/fulltext/S0092-8674(19)30559-8). Seurat offers also a tool for integrating datasets and to visualize them in the same UMAP. Problem is that the query cell types classified using the cell type classification tool doesn't always make sense in the integrated UMAP (some classified query cells are next to reference cells of different labels).
One thought that I've had is to integrate the two datasets as above for the integrated UMAP, and then perform the clustering algorithm of Seurat on the integrated data, and classify the query cells based on which reference cell types they end up clustering together with. The result makes much more sense visually on the integrated UMAP. But I have not been able to find any publication or similar using this method as a cell type classification method. And I was wondering why? Is there a big mistake of doing this? In the integration algorithm the query dataset is modified together with the reference dataset, which is does not happen in the cell type classification algorithm, but I'm thinking that the integration process also removes batch effects between the query and the reference dataset, which could be preferable. But I'm also thinking that there must be a good reason why Seurat doesn't suggests this as an alternative for cell type classification.
Thanks for your input.
SingleRshould help with this: https://bioconductor.org/packages/devel/bioc/vignettes/SingleR/inst/doc/SingleR.html
Thank you for this response, I appreciate the link. However, I was not really looking for an alternative cell type classification tool (I know that there are several out there), merely, I was interested to get some input why my second approach is not used usually.