{"name":"napari-brainways","display_name":"Brainways","visibility":"public","icon":"","categories":[],"schema_version":"0.2.0","on_activate":null,"on_deactivate":null,"contributions":{"commands":[{"id":"napari-brainways.load_sample_project","title":"Load Brainways sample project","python_name":"napari_brainways._sample_project:load_sample_project","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-brainways.load_sample_project_annotated","title":"Load Brainways sample annotated project","python_name":"napari_brainways._sample_project:load_sample_project_annotated","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-brainways.make_qwidget","title":"Make BrainwaysUI widget","python_name":"napari_brainways.brainways_ui:BrainwaysUI","short_title":null,"category":null,"icon":null,"enablement":null},{"id":"napari-brainways.read_bwp","title":"Read \".bwp\" files","python_name":"napari_brainways.napari_reader:get_reader","short_title":null,"category":null,"icon":null,"enablement":null}],"readers":[{"command":"napari-brainways.read_bwp","filename_patterns":["*.bwp"],"accepts_directories":true}],"writers":null,"widgets":[{"command":"napari-brainways.make_qwidget","display_name":"BrainwaysUI","autogenerate":false}],"sample_data":[{"command":"napari-brainways.load_sample_project","key":"sample_project","display_name":"Sample project"},{"command":"napari-brainways.load_sample_project_annotated","key":"sample_project_annotated","display_name":"Annotated sample project"}],"themes":null,"menus":{},"submenus":null,"keybindings":null,"configuration":[]},"package_metadata":{"metadata_version":"2.1","name":"napari-brainways","version":"0.1.11.1","dynamic":null,"platform":null,"supported_platform":null,"summary":"Brainways UI","description":"# Overview\n\n[![DOI](https://img.shields.io/badge/DOI-10.1101/2023.05.25.542252-green.svg)](https://doi.org/10.1101/2023.05.25.542252)\n[![License GNU GPL v3.0](https://img.shields.io/pypi/l/napari-brainways.svg?color=green)](https://github.com/bkntr/napari-brainways/raw/main/LICENSE)\n[![PyPI](https://img.shields.io/pypi/v/napari-brainways.svg?color=green)](https://pypi.org/project/napari-brainways)\n[![Python Version](https://img.shields.io/pypi/pyversions/napari-brainways.svg?color=green)](https://python.org)\n[![tests](https://github.com/bkntr/napari-brainways/workflows/tests/badge.svg)](https://github.com/bkntr/napari-brainways/actions)\n[![codecov](https://codecov.io/gh/bkntr/napari-brainways/branch/main/graph/badge.svg)](https://codecov.io/gh/bkntr/napari-brainways)\n[![Documentation Status](https://readthedocs.org/projects/napari-brainways/badge/?version=latest)](https://napari-brainways.readthedocs.io/en/latest/?badge=latest)\n[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-brainways)](https://napari-hub.org/plugins/napari-brainways)\n\n\n## What Is Brainways?\n\n\nBrainways is an AI-based tool for automated registration, quantification and generation of brain-wide activity networks based on fluorescence in coronal slices.\n\n![Brainways UI](docs/assets/brainways-ui.gif)\n\n\n## Why Brainways?\n\n\nCoronal slice registration, cell quantification and whole-brain contrast analysis between experimental conditions should be made easily accessible from a single software, without requiring programming experience.\nCustomization should be made easy by having a highly flexible pythonic backend.\n\n## Getting Started\n\nTo install and run brainways, run the following in your python environment:\n\n```bash\npip install napari-brainways\nbrainways ui\n```\n\nFollow our [getting started guide](https://napari-brainways.readthedocs.io/en/latest/getting_started/) for more details.\n\n## How it works\n\nBrainways allows users to register, quantify and provide statistical contrast analysis by following several simple steps:\n\n1. Rigid registration of coronal slices to a 3D atlas.\n1. Non-rigid registration of coronal slices to a 3D atlas, to account for individual difference and imperfections in acquisition procedure.\n1. Cell detection (using [StarDist](https://github.com/stardist/stardist)).\n1. Quantification of cell counts per brain region.\n1. Statistical analysis:\n * ANOVA contrast analysis.\n * PLS (Partial Least Square) analysis.\n * Network graph creation.\n\n\n\n## Architecture\n\nBrainways is implemented as three python packages. [*napari-brainways*](https://github.com/bkntr/napari-brainways) contains the GUI implementation as a [napari](https://napari.org/stable/) plugin. napari-brainways is using [*brainways*](https://github.com/bkntr/brainways) as its backend. All of the functionality is implemented in the brainways package. This separation was done to guarantee that brainways is a GUI-agnostic software, and can be fully accessed and manipulated through python code to allow custom complex usage scenarios. The code that was used to train, evaluate and run the automatic registration model resides in [*brainways-reg-model*](https://github.com/bkntr/brainways-reg-model).\n\n## Development Status\n\nBrainways is being actively developed by Ben Kantor of Bartal lab, Tel Aviv University, Israel. Our releases can be found [here](https://github.com/bkntr/napari-brainways/releases).\n\n## Citation\n\nIf you use brainways, please cite [Kantor and Bartal (2023)](https://doi.org/10.1101/2023.05.25.542252):\n\n @article{kantor2023brainways,\n title={Brainways: An Open-Source AI-based Software For Registration and Analysis of Fluorescent Markers on Coronal Brain Slices},\n author={Kantor, Ben and Ben-Ami Bartal, Inbal},\n journal={bioRxiv},\n pages={2023--05},\n year={2023},\n publisher={Cold Spring Harbor Laboratory}\n }\n\n## License\n\nDistributed under the terms of the [GNU GPL v3.0] license,\n\"napari-brainways\" is free and open source software\n\n## Issues\n\nIf you encounter any problems, please [file an issue] along with a detailed description.\n\n[napari]: https://github.com/napari/napari\n[Cookiecutter]: https://github.com/audreyr/cookiecutter\n[@napari]: https://github.com/napari\n[MIT]: http://opensource.org/licenses/MIT\n[BSD-3]: http://opensource.org/licenses/BSD-3-Clause\n[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt\n[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt\n[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0\n[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt\n[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin\n\n[file an issue]: https://github.com/bkntr/napari-brainways/issues\n\n[napari]: https://github.com/napari/napari\n[tox]: https://tox.readthedocs.io/en/latest/\n[pip]: https://pypi.org/project/pip/\n[PyPI]: https://pypi.org/\n","description_content_type":"text/markdown","keywords":null,"home_page":"https://github.com/bkntr/napari-brainways","download_url":null,"author":"Ben Kantor","author_email":"benkantor@mail.tau.ac.il","maintainer":null,"maintainer_email":null,"license":"GPL-3.0","classifier":["Development Status :: 2 - Pre-Alpha","Framework :: napari","Intended Audience :: Developers","License :: OSI Approved :: GNU General Public License v3 (GPLv3)","Operating System :: OS Independent","Programming Language :: Python","Programming Language :: Python :: 3","Programming Language :: Python :: 3 :: Only","Programming Language :: Python :: 3.9","Topic :: Scientific/Engineering :: Image Processing"],"requires_dist":["brainways[all] ==0.1.11","datasets ==2.15.0","importlib-resources","napari[all] ==0.4.18","qtpy ==2.3.1","brainways-reg-model ; extra == 'all'","py ; extra == 'testing'","pyqt5 ; extra == 'testing'","pytest ; extra == 'testing'","pytest-cov ; extra == 'testing'","pytest-qt <4.1.0 ; extra == 'testing'","tox ; extra == 'testing'"],"requires_python":">=3.9","requires_external":null,"project_url":["Bug Tracker, https://github.com/bkntr/napari-brainways/issues","Documentation, https://github.com/bkntr/napari-brainways#README.md","Source Code, https://github.com/bkntr/napari-brainways","User Support, https://github.com/bkntr/napari-brainways/issues"],"provides_extra":["all","testing"],"provides_dist":null,"obsoletes_dist":null},"npe1_shim":false}