KEGGaNOG

<img src="https://github.com/iliapopov17/KEGGaNOG/blob/main/imgs/KaN_logo_light.png#gh-light-mode-only" align="left" width = 25%/> <img src="https://github.com/iliapopov17/KEGGaNOG/blob/main/imgs/KaN_logo_dark.png#gh-dark-mode-only" align="left" width = 25%/> <br> <br>

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Motivation

eggNOG-mapper 🤝 KEGG-Decoder

• eggNOG-mapper is a comprehensive tool for fast functional annotation of novel sequences. Yet it does not provide any visualization functions.
• KEGG-Decoder is a perfect tool for visualizing KEGG Pathways. But it only takes KEGG-Koala outputs as an input (including blastKOALA, ghostKOALA, KOFAMSCAN).
• KEGG-Koala is a web-tool which can work for more than 24 hours. eggNOG-mapper can be installed locally on your PC / server and work faster.
• This tool KEGGaNOG makes eggNOG-mapper meet KEGG-Decoder! It parses eggNOG-mapper output, make it fit for the input to KEGG-Decoder and then visualize KEGG Pathways as the heatmap!
• Pro-tip: eggNOG-mapper and KEGGaNOG could be wrapped into 🐍 Snakemake pipeline making metabolic profiling a "one-click" process!

Installation

# Linux / WSL / macOS
conda create -n kegganog pip -y
conda activate kegganog
pip install kegganog

Usage Guide

Command-line mode

usage: KEGGaNOG [-h] [-M] -i INPUT -o OUTPUT [-overwrite] [-dpi DPI]
                [-c COLOR] [-n NAME] [-g] [-V]

KEGGaNOG: Link eggNOG-mapper and KEGG-Decoder for pathway visualization.

options:
  -h, --help            show this help message and exit
  -M, --multi           “Multi” mode allows to run KEGGaNOG on multiple
                        eggNOG-mapper annotation files (a text file with file
                        location paths must be passed to the input)
  -i INPUT, --input INPUT
                        Path to eggNOG-mapper annotation file
  -o OUTPUT, --output OUTPUT
                        Output folder to save results
  -overwrite, --overwrite
                        Overwrite the output directory if it already exists
  -dpi DPI, --dpi DPI   DPI for the output image (default: 300)
  -c COLOR, --color COLOR, --colour COLOR
                        Cmap for seaborn heatmap. Recommended options: Greys,
                        Purples, Blues, Greens, Oranges, Reds (default: Blues)
  -n NAME, --name NAME  Sample name for labeling (default: SAMPLE) (not active
                        in `--multi` mode)
  -g, --group           Group the heatmap based on predefined categories
  -V, --version         show program's version number and exit

🔗 Please visit KEGGaNOG wiki page

Web interface mode

For an interactive, browser-based experience with live preview and advanced visualization options:

kegganog --web

Then open http://localhost:8000 in your browser.

Features:

• Live preview — visualize plots in real-time as you adjust parameters
• Interactive settings — no command-line arguments needed; drop files, tweak colors and dimensions through an intuitive UI
• Multi-sample analysis — compare samples using heatmaps, radarplots, correlation networks, stacked bars, and streamgraphs
• Re-render on the fly — modify plot parameters without re-running the full analysis (multi mode only)
• Download results — export individual plots or the complete results ZIP

Output examples gallery

Default visualization

|Single mode|Multi mode| |-----------|----------| |||

These figures are generated using functional groupping mode (-g/--group) and Greens colormap

User APIs visualization

|Barplot|Boxplot|Radarplot|Correlation Network| |-------|-------|---------|-------------------| |||||

|Stacked Barplot|Streamgraph|Stacked Barplot + Streamgraph| |-------|-------|-------| ||||

Advantages

1. Seemless Access to KEGG Annotations: Provides KEGG Ortholog (KO) annotations without requiring a KEGG license.
2. High-Throughput Capability: Optimized for rapid KO assignment in large-scale datasets, ideal for metagenomics and genomics projects.
3. Broad Functional Coverage: Leverages the extensive eggNOG database to annotate genes across a wide range of taxa.

Limitation

1. Indirect KO Mapping: eggNOG-mapper doesn’t directly use the KEGG database, its KO term assignments are inferred through orthologous groups (eggNOG entries). This can sometimes result in less precise annotations.

Tool name background

KEGGaNOG stands for “KEGG out of NOG”, highlighting its purpose: extracting KEGG Ortholog annotations from eggNOG’s Non-supervised Orthologous Groups.

Contributing

Contributions are welcome! If you have any ideas, bug fixes, or enhancements, feel free to open an issue or submit a pull request.

Contact

For any inquiries or support, feel free to contact me via email

Happy functional annotation! 💻🧬

Citation

If you use KEGGaNOG in your research, please cite:

Popov, I.V., Chikindas, M.L., Venema, K., Ermakov, A.M. and Popov, I.V., 2025. KEGGaNOG: A Lightweight Tool for KEGG Module Profiling From Orthology-Based Annotations. Molecular Nutrition & Food Research, p.e70269. doi.org/10.1002/mnfr.70269

Acknowledgements

For now KEGGaNOG uses KEGG-Decoder as a main dependecy. I greatly thank KEGG-Decoder's developers.