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Wildly variable retained barcode list

See original GitHub issue

Hello, I just tried out CellBender on 21 datasets of 10x v2 single nuclei data that should be generally comparable (Cell Ranger retains ~1500-3500 barcodes in each) but I got wildly variable results with CellBender.

I used the following parameters: expected-cells = 5000 , total-droplets-included = 15000, epochs = 1500.

The number of barcodes retained by CellBender (from the output.csv file) are below. I’m surprised to see do many datasets with the maximum number of 15k, as well as 2 datasets with 0. Could this be a result of overfitting because I did 1500 epochs? In the output.pdf I noticed that only a train score is provided, so it’s hard to diagnose overfit…

Here are the knee plots in case they help diagnose things. All datasets are pretty similar.

Issue Analytics

State:
Created 3 years ago
Comments:8 (4 by maintainers)

Top GitHub Comments

1reaction

Munfredcommented, Oct 5, 2020

Yes I do believe there is something funky with the data I’m working with. It is a single nuclei dataset of C. elegans, with a new dissociation protocol. It seems to have a lot of background (which is odd since nuclei are washed).

Thanks for the help. I’ll give another shot with cellbender next time I have a less problematic dataset.

0reactions

sjflemingcommented, Oct 5, 2020

By the way, the latent space for that “hard” example above looks like this:

To me, your latent space being a sort of formless blob seems to be another possible hint that there may be some kind of a quality control failure. It’s not definitive of course… for some experiments without much cellular diversity, the latent space will tend to just look like a blob.