Unstable result

[GwangWooKim]

Hello, I’m going to analyze the single-cell RNA sequencing data using the scVI framework.
After training the scVI model, I found that the result of model.differential_expression is unstable (specifically, it varies from seed to seed).
I’ve been trying to solve this problem, but I still haven’t.
Please tell me the expected cause.
Thank you in advance.

[maheshworpaudel5001]

I am using scvi version 1.4.1 and I am facing the same problem. Any help would be really appreciated.

[ori-kron-wis]

@GwangWooKim

Hello, I’m going to analyze the single-cell RNA sequencing data using the scVI framework.
After training the scVI model, I found that the result of model.differential_expression is unstable (specifically, it varies from seed to seed).
I’ve been trying to solve this problem, but I still haven’t.
Please tell me the expected cause.
Thank you in advance.

The DE analysis is based on sampling, so there will be variability between runs.

But given your model converged (check it) and that there is a real biological signal in the data (not just noise, do HVG) - you can run more MC samples to expect more stable results between seeds. Is it version-dependent?