Welcome to the repository for my Master Thesis in Biomedical Data Science. This repository hosts the code, tools, and data analysis performed as part of my thesis work. The project focuses on the analysis of MS proteomic data from various studies.
- Python Modules: Custom mdules developed to assist with data analysis.
- Data Analysis Notebook: Jupyter Notebook with detailed data analysis of the datasets listed below.
The following datasets were analyzed in this project:
| Study | Type | Method* |
|---|---|---|
| Iwata, H., et al. (2016) | Bulk | DDA |
| Li, P., et al. (2022) | Bulk | DDA |
| Li, P., et al. (2021) | Bulk | DDA |
| Huffman, R. G., et al. (2022) | Single Cell | DIA |
*Method: DDA (Data-Dependent Acquisition) or DIA (Data-Independent Acquisition)
The repository is structured as follows:
- /src: Contains custom Python tools and modules developed for data analysis.
- /results: Generated HTML files with the results of the network analysis.
- /data: Contains the datasets used in the analysis.
- /QC_*.R: Quality Control files in R.
To use the tools and run the analysis, follow these steps:
-
Clone the repository:
git clone https://github.com/powwowath/pyMSpro.git cd pyMSpro -
Install dependencies:
pip install -r requirements.txt
-
Run the analysis: Open the Notebook "00_workflow_META-ANALYSIS.ipynb" and follow the instructions to perform the analysis.
For any questions or further information, please contact me at [gerard.font@estudiants.urv.cat] or [ath@athzone.com].