This project generates a heatmap for the presence of metabolic pathways across different species within a given genus. The heatmap is visualized as a PDF file, and the underlying data is saved as a CSV file. The data is fetched from the KEGG (Kyoto Encyclopedia of Genes and Genomes) API.
To run this project, you will need Python 3.6 or later and the following Python packages:
- pandas
- numpy
- seaborn
- matplotlib
- requests You can install these packages using pip:
pip install pandas numpy seaborn matplotlib requests
Run the script from the command line by providing the genus name, output CSV filename, and output PDF filename:
python heatmap.py Vibrio matrix.csv heatmap.pdf
Replace Vibrio with the genus name you want to analyze, and matrix.csv and heatmap.pdf with your desired output file names.
Alternatively, you can run the script from an IDE such as VSCode. If you do not provide command-line arguments, the script will use default parameters: "Vibrio" for the genus name, "matrix.csv" for the output matrix CSV, and "heatmap.pdf" for the output heatmap PDF.
The script generates two output files:
- A CSV file containing a matrix representation of the presence of metabolic pathways across different species within the specified genus.
- A PDF file with a heatmap visualization of the data.
If you use this project in your research, please cite the following paper:
[1]Y.-H. Du and J.-H. Mu, “Metabolic-Pathway-Presence-Heatmap (MPPH):Constructing phylogenetic trees based on metabolic pathways.,” Jun. 2023, doi: https://doi.org/10.1101/2023.06.27.546232.