ma-compbio / Higashi

single-cell Hi-C, scHi-C, Hi-C, 3D genome, nuclear organization, hypergraph
MIT License
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3d-genome hypergraph machine-learning single-cell

Higashi: Multiscale and integrative scHi-C analysis

<img src="https://github.com/ma-compbio/Higashi/blob/main/figs/logo2.png" align="right" alt="logo" width="290">

https://doi.org/10.1038/s41587-021-01034-y

As a computational framework for scHi-C analysis, Higashi has the following features:


figs/Overview.png

Installation

We now have Fast-Higashi on conda. conda install -c ruochiz fasthigashi

The conda support for Higashi is still an on-going effort. Currently, you can install it by:

git clone https://github.com/ma-compbio/Higashi/
cd Higashi
python setup.py install

It is recommended to have pytorch installed (with CUDA support when applicable) after installing higashi / fast-higashi.

Documentation

Please see the wiki for extensive documentation and example tutorials.

Higashi is constantly being updated, see change log for the updating history

Tutorial

Cite

Cite our paper by

@article {Zhang2020multiscale,
    author = {Zhang, Ruochi and Zhou, Tianming and Ma, Jian},
    title = {Multiscale and integrative single-cell Hi-C analysis with Higashi},
    year={2021},
    publisher = {Nature Publishing Group},
    journal = {Nature biotechnology}
}

figs/Overview.png

See also

Fast-Higashi for more efficient and robust scHi-C embeddings https://www.cell.com/cell-systems/fulltext/S2405-4712(22)00395-7

https://github.com/ma-compbio/Fast-Higashi

Contact

Please contact ruochiz@andrew.cmu.edu or raise an issue in the github repo with any questions about installation or usage.