Suggestions on discriminating mitosis cells (proliferative cells) from non-proliferative cells by snapatacv2.

[wangmeijiao]

Hi Kai and all,
I found that in many developmental systems (at least in trophoblast linage and center neuron system), it is hard to match proliferative cell types between snRNA and snATAC data, even though they are from the same nucleus (10X multiomics nucleus). Let me explain. 1) in snRNA side, it is quite distinguishable between proliferative and non-proliferative cell clusters (note that they are the same cell type except for proliferation). 2) but in snATAC side, things are different.They are often mixed as one single cell cluster!
The possible reason: As pointed by Noumova et al. in a mitotic chromosome 3D organization study (https://www.science.org/doi/10.1126/science.1236083, https://www.nature.com/articles/s41580-019-0132-4), chromosomes in mitotic are "globally disassembled and reassembled to mitotic chromatin that is composed of linearly compressed loop arrays". It is quite possible that mitotic cells generally loss (if any) high dimension organization and snapatac can not discriminate proliferative cells from non-proliferative ones. Correct me if I was wrong.
My question: could anyone suggest some tips in snapatacv2, for example, variable feature selection, dimension reduction, etc to make proliferative cells distinguishable?

Thanks!

Meijiao

[kaizhang]

Hi Meijiao,

Thanks for your questions. But this is more a scientific question rather than a technical issue. I'm not sure if the two biologically relevant clusters should be distinguishable by the chromatin features. One way to look at this is to find out if there exist differentially accessible regions among these two populations.