Seurat on both pooled and unpooled samples

Question

[Kristin Muench]

Hello,

I'm analyzing an scRNA-Seq dataset that includes both pooled and unpooled samples. Additionally, the number of cells per sample is different between the unpooled and pooled samples. The overall number of pooled and unpooled samples is balanced across conditions, however.

It's like this:

Sample #1 (unpooled) - Group A - 1000 cells
Sample #2 (unpooled) - Group B - 900 cells
Sample #3 (pooled) - Group A - 10,000 cells
Sample #4 (pooled) - Group B - 10,000 cells

As you might imagine, there is a big difference in the nUMI between Samples #1/2 and Samples #3/4. I could regress this out in Seurat's scaling step, but the difference is so large I'm concerned about over-scaling the data. Is this a relevant concern? Is there a way to do an analysis that includes pooled and unpooled samples with such drastically different cells/sample, aside from randomly selecting 2000 cells (1000 cells/sample) from the pooled samples?

Thanks for your help!

[Ram]

Please use the formatting bar (especially the code option) to present your post better. You can use backticks for inline code (`text` becomes text), or select a chunk of text and use the highlighted button to format it as a code block. I've done it for you this time.

[Kristin Muench]

Thank you for the tip.

[Researcher]

Hi Kristin, I also have 5 samples from two conditions and struggling with the same concern you mentioned above. Did you get the answer to your question, will you mind sharing your experience with the problem?

Thanks in advance!

[Kristin Muench]

Hi there! I never got an answer, but I can tell you what I did So - for the initial analysis, I did not attempt to regress out nUMI because I thought over-regressing the data would be the worse sin. However, we were able to find a way to demultiplex the pooled samples that lessened this initial issue somewhat. Good luck! I'm still curious what other people might do.