StripePy

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StripePy is a CLI application written in Python that recognizes architectural stripes found in the interaction matrix files generated by Chromosome Conformation Capture experiments, such as Hi-C and Micro-C.

StripePy is developed on Linux and macOS and is also tested on Windows. Installing StripePy is quick and easy using pip:

pip install 'stripepy-hic[all]'

For other installation options (conda, source, and Docker or Singularity/Apptainer), and details on ensuring StripePy is in your PATH, please refer to the official documentation.

Why Choose StripePy?

StripePy stands out with several key features that make it a fast and robust stripe caller:

• Broad Format Support: Compatible with major formats: .hic, .cool and .mcool; outputs to .hdf5 and BEDPE.
• User-Friendly: Designed with an intuitive command-line interface, making stripe analysis accessible even to less experienced users.
• Stripe descriptors: Computes stripe width, height, and generates various statistics for post-processing, e.g., ranking and filtering.
• Optimized performance: Outperforms other tools over diverse datasets and a simulated benchmark, StripeBench.
• Exceptional speed & Low Memory: Significantly faster than existing tools (2x Chromosight, 66x Stripenn), with much lower memory usage.

Key Features

StripePy is organized into a few subcommands:

• stripepy download: download a minified sample dataset suitable to quickly test StripePy - link.
• stripepy call: run the stripe detection algorithm and store the identified stripes in a .hdf5 file - link.
• stripepy view: take the result.hdf5 file generated by stripepy call and extract stripes in BEDPE format - link.
• stripepy plot: generate various kinds of plots to inspect the stripes identified by stripepy call- link.

For a quick introduction to the tool, refer to the Quickstart section in the documentation.

For more information on the subcommands, please run stripepy --help and refer to the documentation and the paper.

Getting help

For any issues regarding StripePy installation, walkthrough, and output interpretation please open a discussion on GitHub.

If you've found a bug or would like to suggest a new feature, please open a new issue instead.

Citing

If you use StripePy in your research, please cite the following publication:

Andrea Raffo, Roberto Rossini, Jonas Paulsen
StripePy: fast and robust characterization of architectural stripes
Bioinformatics, Volume 41, Issue 6, June 2025, btaf351
https://doi.org/10.1093/bioinformatics/btaf351

@article{stripepy,
    author = {Raffo, Andrea and Rossini, Roberto and Paulsen, Jonas},
    title = {{StripePy: fast and robust characterization of architectural stripes}},
    journal = {Bioinformatics},
    volume = {41},
    number = {6},
    pages = {btaf351},
    year = {2025},
    month = {06},
    issn = {1367-4811},
    doi = {10.1093/bioinformatics/btaf351},
    url = {https://doi.org/10.1093/bioinformatics/btaf351},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/41/6/btaf351/63484367/btaf351.pdf},
}