Jonsson Lab Bioinformatics Templates

A centralized collection of reusable analysis templates for virology and genomics research. Browse the live gallery at: https://jonsson-lab.github.io/lab-bioinfo-templates

Templates

#	Template	Language	Key Analysis
01	Plaque Assay + Violin Plots	R	One-way ANOVA, Tukey HSD, log10 titer
02	Image Infection + Dose-Response	R	4PL regression, EC50/CC50
03	Multi-Condition ANOVA	R	Welch ANOVA, Holm correction
04	MagPix / Luminex Multiplex	R	Two-way ANOVA, emmeans, FDR
05	Phylo-Geographic Analysis	R	Mantel test, scatter pies, maps
06	GO Enrichment Analysis	R	clusterProfiler, KEGG/Reactome
07	RNA-seq / DESeq2	R	Volcano, bubble, PCA, triangle plots
08	VCF Mutation Analysis	Python	Entropy, mutation frequency, heatmaps

Quick Start

R Templates (01–07)

# 1. Install all R packages once
source("install_packages.R")

# 2. Open a template and edit the USER CONFIGURATION block at the top
# 3. Knit / render

Python Template (08)

conda env create -f environment.yml
conda activate jonsson-bioinfo
jupyter notebook templates/08_vcf-mutation-analysis/template.ipynb

How Templates Work

Every template has a clearly marked configuration section at the very top:

## ── USER CONFIGURATION ──────────────────────────────────────────────────────
DATA_FILE   <- "data/your_data.csv"   # <-- change this
GROUP_COL   <- "Treatment"
# ... (all parameters documented inline)
## ────────────────────────────────────────────────────────────────────────────

Only edit the config block. The analysis code below uses those variables and should not need modification for standard use cases.

Synthetic Example Data

Each template ships with a data/simulate_data.R (or .py) script that generates a small, realistic synthetic dataset. These are the datasets used by the Quarto gallery site so every template renders a meaningful example plot.

To regenerate example data:

source("templates/01_plaque-assay-violin/data/simulate_data.R")

Plot Style

All templates preserve the publication-quality plot style established in the lab:

• theme_classic() or theme_bw() base themes
• Arial font family throughout
• Okabe-Ito colorblind-safe palettes where applicable
• TIFF / SVG / PDF output at 300–600 dpi
• Consistent axis tick lengths and line widths

Do not modify the theme() calls unless intentionally changing the style for a specific figure.

Contributing

1. Fork the repo
2. Copy an existing template folder as a starting point
3. Follow the conversion rules in the template header comments
4. Add a row to index.qmd's gallery table
5. Open a pull request

License

MIT — free to use and adapt for academic research.