Welcome to the PhD Data Analysis repository! This repository contains various scripts and tools for analyzing biological data, specifically focusing on Kaplan-Meier survival analysis and biofilm inhibition studies.
This repository provides tools to perform Kaplan-Meier survival analysis on C. elegans lifespan data and analyze biofilm inhibition activity. The scripts are designed to be user-friendly, even for those with minimal programming experience.
To get started with this repository, follow these steps:
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Clone the repository to your local machine:
git clone https://github.com/yourusername/yourrepository.git cd yourrepository -
Ensure you have Python installed on your computer. You can download it from python.org.
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Install the required Python packages:
pip install pandas lifelines matplotlib seaborn
The repository is organized as follows:
- KaplanMeier_script.py: This script performs Kaplan-Meier survival analysis on the provided data.
- Template.py: Generates a CSV template for entering survival data.
- README_Kaplan-Meier Survival Analysis.md: Instructions for using the Kaplan-Meier analysis tools.
- scripbiofilm.py: Analyzes biofilm inhibition data and generates visualizations.
- scripbiofilm_alternative.py: An alternative script for biofilm analysis with additional visualization options.
- MIC.py: Analyzes Minimum Inhibitory Concentration (MIC) data and generates plots.
Data should be provided in the specified CSV format. For Kaplan-Meier analysis, use the c_elegans_data_template.csv template generated by the Template.py script. For biofilm analysis, ensure your data is formatted correctly in the input files.
The scripts generate various visualizations, including Kaplan-Meier curves and box plots for biofilm inhibition. Ensure that you have the necessary libraries installed to view these plots.
Contributions are welcome! If you have suggestions for improvements or new features, please open an issue or submit a pull request.