Computational Biology

Notes on computational biology, single-cell genomics, and statistical methods.

Single-cell methods: presentation notes

These five notes expand my presentations into connected explanations of the methods and their biological interpretation.

Presentation	Topic
01	cNMF and Variant-to-Gene-to-Program analysis
02	GLUE: unpaired multi-omics integration
03	MAGIC: diffusion and expression smoothing
04	muscat: differential states across samples
05	Techniques of scRNA-seq: the full workflow

Start with the workflow note for an overview, then follow the individual methods.

7 minute read

A connected guide to preprocessing, variance stabilization, embeddings, annotation, differential analysis, trajectories, and communication.

5 minute read

Why the sample is the unit of replication, how pseudobulk works, and what different differential-state methods test.

4 minute read

A step-by-step explanation of affinity kernels, Markov transitions, diffusion, and the limits of expression smoothing.

4 minute read

Cell embeddings, feature embeddings, and guidance graphs for integrating assays measured in different cells.

5 minute read

How perturbation screens and gene expression programs connect CAD-associated variants to endothelial cell biology.

less than 1 minute read

Finemapping for GWAS Variant