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 takesKEGG-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
makeseggNOG-mapper
meetKEGG-Decoder
! It parseseggNOG-mapper
output, make it fit for the input toKEGG-Decoder
and then visualize KEGG Pathways as the heatmap! - Pro-tip:
eggNOG-mapper
andKEGGaNOG
could be wrapped into 🐍Snakemake
pipeline making metabolic profiling a "one-click" process!
# Linux / WSL / macOS
conda create -n kegganog pip -y
conda activate kegganog
pip install kegganog
usage: KEGGaNOG [-h] [-M] -i INPUT -o OUTPUT [-dpi DPI] [-c COLOR] [-n NAME]
[-g] [-V]
KEGGaNOG: Link eggNOG-mapper and KEGG-Decoder for pathway visualization.
optional arguments:
-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
-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 also visit KEGGaNOG wiki page
Wiki page is in process of rewritting!
Output examples
Single mode | Multi mode |
---|---|
These figures are generated using functional groupping mode (-g
/--group
), Blues
colormap and 300 dpi
- Free Access to KEGG Annotations: Provides KEGG Ortholog (KO) annotations without requiring a KEGG license, making it budget-friendly.
- High-Throughput Capability: Optimized for rapid KO assignment in large-scale datasets, ideal for metagenomics and genomics projects.
- Broad Functional Coverage: Leverages the extensive eggNOG database to annotate genes across a wide range of taxa.
- 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.
KEGGaNOG
stands for “KEGG out of NOG”, highlighting its purpose: extracting KEGG Ortholog annotations from eggNOG’s Non-supervised Orthologous Groups.
Contributions are welcome! If you have any ideas, bug fixes, or enhancements, feel free to open an issue or submit a pull request.
For any inquiries or support, feel free to contact me via email
Happy functional annotation! 💻🧬
In previous versions of KEGGaNOG
KEGG-Decoder
was used as a dependecy. It made me use Python 3.6
, which is no good by the end of 2024. In KEGGaNOG
v. 0.7.0 and higher Python 3.13.1
is used. It became possible after I used not the whole KEGG-Decoder
, but its one script. I greatly thank KEGG-Decoder
's developers.