Is it possible to merge scRNAseq data from experiments with different design? I have 4 different single-cell RNAseq experiments, each one representing a different sample of cell type population. I'd like to merge them to a single dataset. However, different cell types are enriched in each sample, and different samples can represent also different conditions (control and disease).

If I run a PCA on the merged dataset (without any processing of data) I find that the different sample's cells cluster separately. This could be due to biological and technical (i.e. batch effects) variation.

Is it possible to merge these different samples while retaining a good amount of information or should they be analyzed separately?
It’s right there on the cellranger manual:

#aggregate results of counts for separate samples
cellranger aggr
#analyse the combined results
cellranger reanalyze


Note: I’m not sure this applies to the above case where batch effects could be an issue. However, this is how the analysis is performed for 10X data from multiple runs in principle.

cellranger aggr

cellranger reanalyze