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Principled gene–gene correlations with NBLN + SVI cascade + sparse loadings prior

This tutorial is a sequel to Modeling Assumptions for Single-Cell RNA-seq with scribe. It uses the same Jurkat Cells dataset (~3,200 cells) and focuses on the Negative-Binomial LogNormal (NBLN) model: SVI cascade anchoring, gauge handling, and sparse loadings priors so that reported gene–gene correlations are easier to interpret and defend.

Pre-computed outputs

This notebook requires a GPU to run. All outputs shown below were pre-computed and exported to static HTML. To re-run it yourself, clone the repository and execute the notebook with marimo edit docs/tutorials/jurkat_cells_nbln.py on a GPU-enabled machine.

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