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Mixture Models & Bayesian Differential Expression

This tutorial walks through using scribe to perform unsupervised cell-type discovery with a two-component mixture model and Bayesian differential expression analysis on a 50/50 mixture of Jurkat and HEK 293T cells from the 10x Genomics public dataset.

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/5050_jurkat_293t.py on a GPU-enabled machine.

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