# Copyright (C) 2024 Roberto Rossini <roberros@uio.no>
#
# SPDX-License-Identifier: MIT

cff-version: 1.2.0
message: 'If you use this software, please cite it using the metadata from this file.'
authors:
  - given-names: Andrea
    family-names: Raffo
    orcid: 'https://orcid.org/0000-0003-3559-0533'
    email: andrea.raffo@ibv.uio.no
    affiliation: 'Department of Biosciences, University of Oslo'
  - given-names: Roberto
    family-names: Rossini
    orcid: 'https://orcid.org/0000-0003-3096-1470'
    email: roberros@uio.no
    affiliation: 'Department of Biosciences, University of Oslo'
title: StripePy
abstract: 'StripePy recognizes architectural stripes in 3C and Hi-C contact maps using geometric reasoning'
doi: '10.5281/zenodo.14394041'
url: 'https://github.com/paulsengroup/StripePy'
repository-code: 'https://github.com/paulsengroup/StripePy'
repository-artifact: 'https://github.com/paulsengroup/StripePy/pkgs/container/stripepy'
type: software
license: MIT
keywords:
  - architectural-stripes
  - bioinformatics
  - cli-application
  - hi-c
  - loop-extrusion
  - python
preferred-citation:
  type: article
  authors:
  - given-names: Andrea
    family-names: Raffo
    orcid: 'https://orcid.org/0000-0003-3559-0533'
    email: andrea.raffo@ibv.uio.no
    affiliation: 'Department of Biosciences, University of Oslo'
  - given-names: Roberto
    family-names: Rossini
    orcid: 'https://orcid.org/0000-0003-3096-1470'
    email: roberros@uio.no
    affiliation: 'Department of Biosciences, University of Oslo'
  - given-names: Jonas
    family-names: Paulsen
    orcid: 'https://orcid.org/0000-0002-7918-5495'
    email: jonas.paulsen@ibv.uio.no
    affiliation: 'Department of Biosciences, University of Oslo'
  doi: '10.1101/2024.12.20.629789'
  url: 'https://www.biorxiv.org/content/early/2024/12/22/2024.12.20.629789'
  journal: 'Cold Spring Harbor Laboratory'
  year: 2024
  month: 12
  title: 'StripePy: fast and robust characterization of architectural stripes'
  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.
