kegganog 0.1.5

A tool for generating KEGG heatmaps from eggnog-mapper outputs.

KEGGaNOG

Motivation

eggNOG-mapper 🤝 KEGG-Decoder

• eggNOG-mapper is a beautiful 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

KEGG-Decoder is hardwired into KEGGaNOG
KEGG-Decoder uses python=3.6
That's why KEGGaNOG uses this version too

conda create -n kegganog python=3.6
conda activate kegganog
pip install kegganog

Usage Guide

usage: kegg_a_nog.py [-h] -i INPUT -o OUTPUT [-dpi DPI] [-c COLOR] [-n NAME]

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

optional arguments:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Path to eggnog-mapper output file
  -o OUTPUT, --output OUTPUT
                        Output folder to save results
  -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)

🔗 Please also visit KEGGaNOG wiki page

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! 💻🧬