This repository is for developing methods to analyze the assocations between miRNAs and periodontal disease.
The repository contains the following notebooks in the notebooks directory.
-
xgboost_miRNA.ipynb
Runs XGBoostClassifer on three datasets:- Sham and infeceted mice from all weeks; i.e., 8 week and 16 week datasets are merged.
- Sham and infected mice at 8 weeks.
- Sham and infected mice at 16 weeks.
In each dataset, there is a flag (named ‘infected’) that marks whether the mice came from the infected group or the sham group.
XGBoost's variable importance and SHAP values are then used to determine which miRNA variable was most important in each cohort dataset.
transpose_merge_miRNA.ipynb
Run notebook to transpose and merge the miRNA data files into a singletransposed_Tf_miRNA.xlsxfile.transpose_Tf_aveolar_bone_resporption.ipynb
Run notebook to transpose theTf_aveolar_bone_resporption.xlsxdata into thetransposed_Tf_aveolar_bone_resporption.xlsxfile.merge_miRNA_bone_resorption.ipynb
Run notebook to create themerged_miRNA_resporption.xlsxdata file.
- To create a virtual environment run the command
python -m venv venv. This will create a virtual environment in thevenvdirectory. You can specify a different directory name if you wish. - Run
source venv/bin/activateto activate (i.e., run) the virtual environment. - After activating the environment, install the project libraries using the command
pip install -r requirements.txt -U.
Jupyter notebooks won't necessarily have access to the libraries installed in the virtual environment.
One hack to get around this is to create a softlink to the Jupyter binary created in the virtual environment like so ln -s venv/bin/jupyter.
You can then start Jupyter within the virtual environment using the softlink. E.g., ./jupyter lab.
The allows the Jupyter notebook to access the libraries in the virtual environment.
Another option is create a Jupyter kernel from the virtual environment. See here for details.