paulsengroup/stripepy repository overview

⁠StripePy

This repository hosts the Docker images for StripePy: a tool to recognize architectural stripes in 3C and Hi-C contact maps using geometric reasoning.

⁠Quick reference

StripePy is developed and maintained by the Paulsen group⁠.

If you have questions regarding StripePy, please start a new discussion⁠ on GitHub.

⁠Useful links

• Code repository: github.com/paulsengroup/StripePy⁠
• Documentation: github.com/paulsengroup/StripePy⁠
• Dockerfile: source code⁠

⁠Additional information

Images are automatically built using GitHub Actions every time a commit is pushed on the main branch, or whenever a new release is tagged.

Build logs: link⁠

⁠Supported tags and Dockerfile links

• main⁠ - Dockerfile⁠
• 1.3.0⁠ - Dockerfile⁠
• 0.0.2⁠ - Dockerfile⁠

⁠What's in this image?

This image contains the StripePy library CLI tools. The CLI consists of a single executable (stripepy) with a few subcommands.

⁠Quickstart

First, pull the latest version of StripePy from DockerHub.

For production use, we recommend pulling the latest stable release:

docker pull paulsengroup/stripepy:1.3.0

Otherwise, feel free to pull the latest available image:

docker pull paulsengroup/stripepy

Note that depending on your OS, you may need admin/root permissions (which are usually obtained by e.g. prefixing the pull command with sudo).

⁠Printing the help message

user@dev:/tmp$ docker run paulsengroup/stripepy --help

usage: stripepy [-h] [-v] {call,download,plot,view} ...

stripepy is designed to recognize linear patterns in contact maps (.hic, .mcool, .cool) through the geometric reasoning, including topological persistence and quasi-interpolation.

options:
  -h, --help            show this help message and exit
  -v, --version         show program's version number and exit

subcommands:
  {call,download,plot,view}
                        List of available subcommands:
    call                stripepy works in four consecutive steps:
                        • Step 1: Pre-processing
                        • Step 2: Recognition of loci of interest (also called 'seeds')
                        • Step 3: Shape analysis (i.e., width and height estimation)
                        • Step 4: Signal analysis
    download            Helper command to simplify downloading datasets that can be used to test StripePy.
    plot                Generate various static plots useful to visually inspect the output produced by stripepy call.
    view                Fetch stripes from the HDF5 file produced by stripepy call.

For more details and examples on how to use stripepy, please refer to the official documentation⁠.

⁠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 bioRxiv 2024.12.20.629789; doi: https://doi.org/10.1101/2024.12.20.629789⁠

@article {stripepy,
  author = {Raffo, Andrea and Rossini, Roberto and Paulsen, Jonas},
  title = {StripePy: fast and robust characterization of architectural stripes},
  elocation-id = {2024.12.20.629789},
  year = {2024},
  doi = {10.1101/2024.12.20.629789},
  publisher = {Cold Spring Harbor Laboratory},
  abstract = {
    Architectural stripes in Hi-C and related data are crucial for gene regulation, development, and DNA repair.
    Despite their importance, few tools exist for automatic stripe detection.
    We introduce StripePy, which leverages computational geometry methods to identify and analyze architectural stripes in contact maps from Chromosome Conformation Capture experiments like Hi-C and Micro-C.
    StripePy outperforms existing tools, as shown through tests on various datasets and a newly developed simulated benchmark, StripeBench, providing a valuable resource for the community.Competing Interest StatementThe authors have declared no competing interest.@
  },
  URL = {https://www.biorxiv.org/content/early/2024/12/22/2024.12.20.629789},
  eprint = {https://www.biorxiv.org/content/early/2024/12/22/2024.12.20.629789.full.pdf},
  journal = {bioRxiv}
}