This repo contains a set of Jupyter notebooks introducing key features of the gos
genomics visualization library for Python.
The notebooks can be run via Google Colab,
or locally with Jupyter,
jupyter notebook notebooks/
Note The
clinvar.ipynb
notebook contains the option to load large datasets locally rather than via a remote HiGlass server. TheSnakemake
workflow contained in this repo will generate those files if desired, but running these scripts are optional.
conda env create -f environment.yaml
conda activate gos-example
# preprocess data
snakemake -c all data/agg/clinvar.bed.beddb data/agg/density.multires.mv5
# run the notebook
jupyter notebook
Alternatively, using uv:
# brew install llvm (make sure you have `llvm-ar` and specify explicitly)
# preprocess data
AR=/opt/homebrew/opt/llvm/bin/llvm-ar uv run snakemake.py -c all data/agg/clinvar.bed.beddb data/agg/density.multires.mv5
# run the notebook
uvx juv run notebooks/clinvar.ipynb
# or uvx juv run notebooks/getting-started.ipynb, etc