Visualizing anatomically registered data with Brainrender
Abstract
Three-dimensional (3D) digital brain atlases and high-throughput brain wide imaging techniques generate large multidimensional datasets that can be registered to a common reference frame. Generating insights from such datasets depends critically on visualization and interactive data exploration, but this a challenging task. Currently available software is dedicated to single atlases, model species or data types, and generating 3D renderings that merge anatomically registered data from diverse sources requires extensive development and programming skills. Here, we present brainrender: an open-source Python package for interactive visualization of multidimensional datasets registered to brain atlases. Brainrender facilitates the creation of complex renderings with different data types in the same visualization and enables seamless use of different atlas sources. High-quality visualizations can be used interactively and exported as high-resolution figures and animated videos. By facilitating the visualization of anatomically registered data, brainrender should accelerate the analysis, interpretation, and dissemination of brain-wide multidimensional data.
Data availability
All code has been deposited on GitHub and is freely accessible.
Article and author information
Author details
Funding
Gatsby Charitable Foundation (GAT3361)
- Troy W Margrie
- Tiago Branco
Wellcome (214333/Z/18/Z)
- Troy W Margrie
Wellcome (214352/Z/18/Z)
- Tiago Branco
Wellcome (090843/F/09/Z)
- Troy W Margrie
- Tiago Branco
Deutsche Forschungsgemeinschaft (390857198)
- Ruben Portugues
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Claudi et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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