Following the old adage that an example is worth a thousand docstrings, we created a set of notebooks that cover many typical Hi-C analyses using the open2c code ecosystem. For users who are new to Hi-C analysis, we recommend going through example notebooks in the following order:
- viz.ipynb: how to load and visualize Hi-C data stored in coolers.
- contacts_vs_distance.ipynb: how to calculate contact frequency as a function of genomic distance-- the most prominent feature in Hi-C maps
- insulation_and_boundaries.ipynb: how to extract insulation profiles and call boundaries using insulation profile minima.
- pileup_CTCF.ipynb: how to create avearge maps around genomic features like CTCF.
- compartments_and_saddles.ipynb: how to extract eigenvectors and create saddleplots reflecting A/B compartments.
Note that these notebooks currently focus on mammalian interphase Hi-C analysis, but are readily extendible to other organisms and cellular contexts.
Clone open2c_examples on your computer using git clone command, and checkout the recent version:
git clone https://github.com/open2c/open2c_examples
git checkout cooltools-0.5.0Then navigate to the open2c_examples directory and use environment.yml file to create a conda environment open2c with the software packages required to run these notebooks:
export PIP_NO_CACHE_DIR=1
cd open2c_examples
conda env create -f environment.ymlNote that the environmental variable PIP_NO_CACHE_DIR is set, as this helped avoid numba and numpy version conflicts.
Activate the environment and launch jupyter:
conda activate open2c
jupyter lab