brainglobe-workflows 1.0.0

A collection of end-to-end data analysis workflows executed using BrainGlobe tools.

BrainGlobe Workflows

brainglobe-workflows is a package that provides users with a number of out-of-the-box data analysis workflows employed in neuroscience, implemented using BrainGlobe tools. You can view the full documentation for each workflow online. You can also find the documentation for the backend BrainGlobe tools these workflows use on our website.

At present, the package offers the following workflows:

• cellfinder: Whole-brain detection, registration, and analysis.

Installation

If you want to install BrainGlobe workflows as a standalone tool, you can run pip install in your desired environment:

pip install brainglobe-workflows

brainglobe-workflows is built using BrainGlobe tools, and it will automatically fetch the tools that it needs and install them into your environment. Once BrainGlobe version 1 is available, this package will fetch all BrainGlobe tools and handle their install into your environment, to prevent potential conflicts from partial-installs.

Contributing

Contributions to BrainGlobe are more than welcome. Please see the developers guide.

Citing brainglobe-workflows

If you use any tools in the brainglobe suite, please let us know, and we'd be happy to promote your paper/talk etc.

If you find cellfinder useful, and use it in your research, please cite the paper outlining the cell detection algorithm:

Tyson, A. L., Rousseau, C. V., Niedworok, C. J., Keshavarzi, S., Tsitoura, C., Cossell, L., Strom, M. and Margrie, T. W. (2021) “A deep learning algorithm for 3D cell detection in whole mouse brain image datasets’ PLOS Computational Biology, 17(5), e1009074 https://doi.org/10.1371/journal.pcbi.1009074

If you use any of the image registration functions in cellfinder, please also cite brainreg.

---

Cellfinder

Whole-brain cell detection, registration and analysis.

If you want to just use the cell detection part of cellfinder, please see the standalone cellfinder-core package, or the cellfinder plugin for napari.

cellfinder is a collection of tools developed by Adam Tyson, Charly Rousseau and Christian Niedworok in the Margrie Lab, generously supported by the Sainsbury Wellcome Centre.

cellfinder is a designed for the analysis of whole-brain imaging data such as serial-section imaging and lightsheet imaging in cleared tissue. The aim is to provide a single solution for:

• Cell detection (initial cell candidate detection and refinement using deep learning) (using cellfinder-core),
• Atlas registration (using brainreg),
• Analysis of cell positions in a common space.

Basic usage:

cellfinder -s signal_images -b background_images -o output_dir --metadata metadata

Full documentation can be found here.