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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.
This project was developed by Yiheng Du.
Research School of Biology, Australian National University (ACT, ACT, AU)
2023 to 2024 | Master (Quantitative Biology and Bioinformatics)
Education details: Link
Research School of Biology, Australian National University (ACT, ACT, AU)
2020 to 2023 | Bachelor (Quantitative Biology and Bioinformatics)
Education details: Link
Shandong University(Shandong, CN)
2019 to 2023 | Bachelor (Biology)
Education details: Link
The associated article by Yiheng Du has been published and can be accessed through the following link: https://doi.org/10.1101/2023.06.27.546232