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
brainways ui

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-0.1.11.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-0.1.11-py3-none-any.whl (199.5 kB view details)

Uploaded Python 3

File details

Details for the file brainways-0.1.11.tar.gz.

File metadata

  • Download URL: brainways-0.1.11.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-0.1.11.tar.gz
Algorithm Hash digest
SHA256 61ce8222da4cb22ffed7c266cd9fba199948122236ae7212b08a1f062ce01259
MD5 ecf08ffc95bd2feba63ee4510b41423d
BLAKE2b-256 ff823d92091218a8c70dbac852dfcaa7093bb57168614a0939022a2aee32e67b

See more details on using hashes here.

File details

Details for the file brainways-0.1.11-py3-none-any.whl.

File metadata

  • Download URL: brainways-0.1.11-py3-none-any.whl
  • Upload date:
  • Size: 199.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.2

File hashes

Hashes for brainways-0.1.11-py3-none-any.whl
Algorithm Hash digest
SHA256 83a908e24ace97bee48bc5d3b39d3e0d062cc91928c4f4b6c36ce5239ddb0bb9
MD5 97097c697f26eac181b98e225d8916e1
BLAKE2b-256 b0b08cdbe643eaf322382a615b71ddc9bac755fe54ee40b54ef71396adf0be6f

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 Pingdom Monitoring Sentry Error logging StatusPage Status page