Adjusting batch effects for known cell types and applying this transformation to all cells in sc-rnaseq

Question

[eonurk]

Hi all,

I have data from single cell rna-seq experiments of bone marrow with two different conditions. I know that T/B cell compartments for these samples will be not affected in these different conditions, but myeloid cells will.

So, my question is that to correct the batch effect between these conditions, can I just use T/B cells and apply this transformation to all cells?

Would that make sense? If so, how would a possible pipeline look like within standard Seurat pipeline?

Best,

[rpolicastro]

what batch effect transformation are you referring to, and at what step in the processing pipeline are you trying to remove batch effects?

Answer 1

[jared.andrews07]

In theory, most integration methods should keep biological distinct cells, well, distinct from each other, only accounting for technical variation between highly biologically similar entities (e.g. T cells from two different people).

In reality, many of them suffer from a heavy hand and force together cells that are "similar" even if they have meaningful biological differences. In this case, since you already have a good idea of what's happening and what should be different, you could try the reciprocal PCA method from Seurat, which allows you to modulate the strength of integration. This would allow you to ensure your unaffected cell compartments show good overlap while your myeloid compartment still retains differences between the conditions.