/setton_hadi_choo_2023

Setton, Hadi, Choo et al Nature 2023

Primary LanguageJupyter NotebookMIT LicenseMIT

setton_hadi_choo_2023

This repository contains code and data to generate the figures presented in Setton, Hadi, Choo et al. Nature 2023.

Most figures (aside from those which rely on random forest training) are found in ./notebooks/figures.ipynb. The remaining figures (Figure 5, Extended Data Figure 8, and Extended Data Figure 9) are found in ./notebooks/random_forest.ipynb.

We have also made available our OnenessTwoness random forest classifier, which predicts whether a tumor sample is HR-proficient, BRCA1-deficient, and BRCA2-deficient. This is saved in the file ./models/stash.retrained.model.rds. We provided the code for training the model and an example of the input data for making predictions in the notebook ./notebooks/oneness_twoness_training_and_examples.ipynb.