Source code to reproduce analyses for the paper Molecular profiling of tissue biopsies reveals unique signatures associated with streptococcal necrotizing soft tissue infections

Code was tested with the following package versions (see requirements.txt)

- Python>=3.6
- biopython==1.72
- matplotlib==3.0.2
- networkx==2.2
- numpy==1.15.4
- pandas==0.23.4
- scikit-learn==0.20.1
- scipy==1.1.0
- statsmodels==0.9.0
- urllib3==1.24.1
- XlsxWriter==1.1.2

- R>=3.5
- Boruta==6.0.0

    git clone https://github.com/MolProfileStrepNSTI/NSTI_src_code.git

pip

    python -m pip install -r requirements.txt

conda

    conda install --file requirements.txt

• script to creates source data table and a GO ontology subgraph in gml file format in the results/figure3 folder

    python ./figure3.py

• script to creates source data table for Figure 4B in the results/figure4 folder

    python ./Figure4.py

• scripts to create source data tables and figures in the results/figure7 folder
• hyperparameter tuning for each classifier is located in the notebooks folder as a jupyter notebook or in .html format or

    python ./Figure7_Classifier_train_test_val.py

Results

• Figure 7A

• Figure 7C

• Figure 7D

    Rscript --vanilla ./Figure7B_boruta.R

Results

• Figure 7B

This work is licensed under the MIT license

This application uses Open Source components. You can find the source code of their open source projects along with license information below. We acknowledge and are grateful to these developers for their contributions to open source.

• https://github.com/jdrudolph/goenrich
• License (MIT)