Bioinformatics Handbook
A practical bioinformatics methods handbook for transcriptomics, single-cell analysis, genomics, proteomics, epigenomics, clinical statistics, experimental design, and data resources.
Quick start
Open the docs locally and choose a topic or protocol from the left navigation.
notebook/
├─ docs/ # this documentation site
├─ sources/ # companion md, py, R, json, csv files
├─ INDEX.ipynb # Jupyter notebook index
├─ skills_index.csv # protocol-level manifest
└─ file_manifest.csv # file-level manifestCourse map
Counts → differential expression → enrichment → networks. Where most people start.
Heterogeneity at the resolution of single cells and tissue coordinates.
From DNA variation to disease causality — a different mindset from expression.
Measuring proteins, and stitching many omics into one picture.
Answers 'who regulates these genes' — four ways to use ChIP-Atlas.
Making conclusions survive statistical scrutiny — where beginners stumble most.
No analysis rescues a bad design — understand how data is born at the bench.
Discovery built on public data and existing knowledge — landing on targets and the clinic.
What is included
- 39 method protocols across 8 bioinformatics topics.
- Companion Markdown, Python, R, JSON and CSV files for reproducible workflows.
- Teaching figures, source-code previews, and topic-level navigation.
- Notebook and manifest links for reuse in research projects.