Improve DE tutorial

[grst]

Description of feature

In addition to the basic DE tutorial that shows the basic functionality of DE methods, we should have an advanced tutorial that shows how to build more complex contrasts, including interaction terms based on a real-world multi-condition dataset/atlas.

Some work has been d started here, but didn't progress far: https://github.com/scverse/multi-condition-comparisions/blob/main/docs/notebooks/breast_cancer.ipynb

[Zethson]

Added a rough draft https://github.com/scverse/pertpy-tutorials/blob/main/differential_gene_expression.ipynb

TODOs

• [ ] Maybe make the patients as independent covariates work (leads to matrix not being full rank)
• [ ] Better explain what the DE results mean and how they can be used now (maybe a dirty decoupler/GSEA/something analysis
• [ ] Better explain the models
• [ ] Better explain how design matrices and contrasts work (just 1-2 sentences each)
• [ ] Incorporate better visualizations as they become available in pertpy
• [ ] Show how to use scanpy plotting functions with the DE results