Skip to main content

Brainways

DOI License GNU GPL v3.0 PyPI Python Version tests codecov Documentation Status napari hub

What Is Brainways?

Brainways is an AI-based tool for automated registration, quantification and generation of brain-wide activity networks based on fluorescence in coronal slices.

Brainways UI

Why Brainways?

Coronal 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. Customization should be made easy by having a highly flexible pythonic backend.

Getting Started

To install and run brainways, run the following in your python environment:

pip install napari-brainways
napari -w napari_brainways

Follow our getting started guide for more details.

How it works

Brainways allows users to register, quantify and provide statistical contrast analysis by following several simple steps:

  1. Rigid registration of coronal slices to a 3D atlas.
  2. Non-rigid registration of coronal slices to a 3D atlas, to account for individual difference and imperfections in acquisition procedure.
  3. Cell detection (using StarDist).
  4. Quantification of cell counts per brain region.
  5. Statistical analysis:
    • ANOVA contrast analysis.
    • PLS (Partial Least Square) analysis.
    • Network graph creation.

Architecture

Brainways is implemented as three python packages. napari-brainways contains the GUI implementation as a napari plugin. napari-brainways is using 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.

Development Status

Brainways is being actively developed by Ben Kantor of Bartal lab, Tel Aviv University, Israel. Our releases can be found here.

Citation

If you use brainways, please cite Kantor and Bartal (2023):

@article{kantor2023brainways,
  title={Brainways: An Open-Source AI-based Software For Registration and Analysis of Fluorescent   Markers on Coronal Brain Slices},
  author={Kantor, Ben and Ben-Ami Bartal, Inbal},
  journal={bioRxiv},
  pages={2023--05},
  year={2023},
  publisher={Cold Spring Harbor Laboratory}
}

License

Distributed under the terms of the GNU GPL v3.0 license, "napari-brainways" is free and open source software

Issues

If you encounter any problems, please file an issue along with a detailed description.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

brainways-0.1.10.3.tar.gz (2.3 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

brainways-0.1.10.3-py3-none-any.whl (198.0 kB view details)

Uploaded Python 3

File details

Details for the file brainways-0.1.10.3.tar.gz.

File metadata

  • Download URL: brainways-0.1.10.3.tar.gz
  • Upload date:
  • Size: 2.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.2

File hashes

Hashes for brainways-0.1.10.3.tar.gz
Algorithm Hash digest
SHA256 13eff7f6a479b0d6035aa4fa42db6aa5ddf0d7f2c1d9d835647d65a4adb79d07
MD5 63469597655622ee71d0fddd57ce58ea
BLAKE2b-256 66edd40ca76befc05f72761a2cdd416d9b14406bec873add6590f712231dad6f

See more details on using hashes here.

File details

Details for the file brainways-0.1.10.3-py3-none-any.whl.

File metadata

  • Download URL: brainways-0.1.10.3-py3-none-any.whl
  • Upload date:
  • Size: 198.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.2

File hashes

Hashes for brainways-0.1.10.3-py3-none-any.whl
Algorithm Hash digest
SHA256 512e17f97e66fba473d93ed716facf8dfe54042db015303359690da324399e39
MD5 01a07477da07a10df56715310eae3871
BLAKE2b-256 caef1d29b7b2bff0f32cb2761d67bbfb5034c51a75e7fde88fdee2cc206a0869

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page