I have a dataset (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE158442) with very few cells for certain cases after the QC and clustering steps:
I was wondering high reliable it would be to use counts across such few number of cells at case level?
The original authors divide the cases in 4 different stages so they end up with a good number of cells per stage per cell type. However I am more interested in individual cases.
A second question related to the first one is that I don't have much interest in expression values across different cells for the specific set of genes I am interested in as they seem to have similar patterns across all cell types. So my question is what would be a good strategy to convert raw counts across all cells, for each individual case, to a bulk-like RNA-seq format, to able to use cells that are filtered out due to multiplet detection and other purity measures during QC and clustering.