Understanding differential gene expression analysis

Interesting discussion. Can I ask a question regarding the sampling process. I am fairly new to this tool, and use it now more and like it.

Q:
If we compare the differential gene expression between one clusters with two conditions - and we have 100 cells from condition_A and 1000 cells from condition_B . Condition_A has a normally distributed expression around 10 and treatment_B has also a normally distributed expression value around 8 (for the sake of the example, but this brings up another question how the expression is distributed in clusters in general after QC?). Then we (maybe) would a significant higher expression in condition_A than in condition_B - although the cell numbers are off right (this applies to all the method for DGE I guess)? Do we correct for that bias somehow, or is that something to observe and take care of?

Another question I would have is also regarding the sampling with replacement - how small (from the cell count) can clusters get to compare them - can we compare clusters with 10 cells each for DGE if we do sampling with replacement?

Thanks in advance for your feedback, really looking forward to understand the tool better,
best wishes,
Simon