This repo contains the code associated with the paper (citation coming soon)
Data: (link coming soon)
Installation: A list of the libraries required to execute the notebooks is in requirements.txt To install the libraries, run (ideally in a virtual environment) pip install -r requirements.txt
Structure of repository
SSD: Sparse Structure Discovery
- Tutorial Jupyter notebook (SSD/Example.ipynb)
- Python script that generates factorizer objects for the data analyzed in the paper (SSD/factorizer_examples.py)
- Notebooks generating the figures presented in the paper (SSD/{bbq, genotoxin, hub_synthetic, independent_synthetic, kinsler}_figures.ipynb)
- Utils folder containing code that executes our ssd method (SSD/utils/ssd.py) and stores solutions across a range of regularization values (SSD/utils/factorizer.py)
QTL: Multi-phenotype QTL mapping.
This folder contains joint_qtl_mapping.py, which executes our joint QTL mapping pipeline. Code in this folder recreates the QTL mapping on the BBQ dataset. See README in folder for further description.