Useful code

PERSONAL RESEARCH COOKBOOK

Readable workflows for bioinformatics.

Browse R, Python, and Quarto guides by method. Open a notebook on GitHub to inspect its code and assumptions.

8notebooks

6method areas

Research workflows. Check assumptions and validate outputs for your study. Read the reuse guidance.

Search includes notebook text.

Single-cell RNA

3 notebooks

Single-cell analysis with Seurat, AnnData, and pyUCell.

Includes: Seurat QC and inference; AnnData velocity and activity; Python signature scoring

Bulk RNA

1 notebooks

One count-aware edgeR workflow from tximport through sample-level scoring.

Includes: tximport, QC, differential expression, GSEA, singscore, GSVA

scATAC-seq

1 notebooks

One Signac workflow from count matrix and fragments through motif analysis.

Includes: Signac QC, LSI, differential peaks, motifs, chromVAR

Multiome

1 notebooks

One paired RNA/ATAC workflow for QC, WNN, linkage, and label transfer.

Includes: paired QC, weighted nearest neighbors, peak-gene links, label transfer

Multi-omics / MOFA

1 notebooks

One MOFA2 workflow from matched views through model diagnostics and interpretation.

Includes: view matching, fitting, factors, variance, weights

Biomarker machine learning

1 notebooks

One sample-level bias-reduced classifier with a locked held-out evaluation.

Includes: brglm2 classification and held-out reporting