The program requires a standard computer with at least 8GB RAM to support the in-memory computation.
- Operating System: Linux Ubuntu 16.04
- Python version: 3.7.3
- Python dependencies: numpy(v1.17.2), pandas(v0.25.1), scikit-learn(v0.21.3), scipy(v1.3.1)
- R version: 3.4.4
- R dependencies: MALDIquantForeign(v0.12)
After unzipping the code, install the necessary dependency packages
pip install -r requirements.txt
It will take several minutes to install, depends on the network.
├── README.md
├── Tools
│ ├── Assessment.py
│ ├── DataTools.py
│ └── FileTools.py
├── mzml2csv
│ └── initData.py
├── preprocess
│ └── dataPreprocess.py
├── model
│ └── model.py
├── plot
│ ├── cm.py
│ └── roc.py
└── requirements.txt
The Tools folder stores tool files, including functions related to file reading and writing, data organization, and metric evaluation. The file initData.py in the mzml2csv folder is used to reformat the original data, and the mzml format file is converted to csv format by calling the program in R. The file dataPreprocess in preprocess folder is used to preprocess the converted data. The file model.py in model folder is the main file of the method and contains the key steps of model training. The plot folder contains two files for drawing confusion matrix and ROC curves.
Apache 2.0 License.