The natverse, a versatile toolbox for combining and analysing neuroanatomical data
Abstract
To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community.
Data availability
All code is described at natverse.org which links to individual git repositories at github.com/natverse.
Article and author information
Author details
Funding
Medical Research Council (MC-U105188491)
- Alexander S Bates
- James D Manton
- Gregory SXE Jefferis
H2020 European Research Council (649111)
- Alexander S Bates
- James D Manton
- Marta Costa
- Gregory SXE Jefferis
Wellcome (203261/Z/16/Z)
- Sridhar R Jagannathan
- Marta Costa
- Philipp Schlegel
- Gregory SXE Jefferis
Boehringer Ingelheim Fonds
- Alexander S Bates
Herchel Smith Fund
- Alexander S Bates
Fitzwilliam College
- James D Manton
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Bates 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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