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 <monospace>natverse</monospace>. The <monospace>natverse</monospace> 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 <monospace>natverse</monospace> enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The <monospace>natverse</monospace> 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 <monospace>natverse</monospace> 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.
Highlights
Neuroanatomy has become a large-scale, digital and quantitative discipline
This paper describes the Neuroanatomy Toolbox, a general purpose open source R-based package for quantitative neuroanatomy, and a suite of extension R packages that together we call the natverse
Confirmed stable versions of nat,Xnat.templatebrains,Xnat. nblast,Xnat.utils and nabor can be downloaded from the centralised R package repository, CRAN, with developmental versions available from our GitHub page
Summary
Neuroanatomy has become a large-scale, digital and quantitative discipline. Improvements in sample preparation and imaging increasingly enable the collection of large 3D image volumes containing complete neuronal morphologies in the context of whole brains or brain regions. Neuroscientists, need to tackle large amounts of morphological data, often writing custom code to enable repeated analysis using their specific requirements. They need to analyse neuronal morphology and connectivity in the context of whole nervous systems or sub-regions. One important consequence of these free and open-source tools is that they aid collaboration and reproducibility, and reduce the overhead when switching between different types of analysis. Together, these considerations have motivated us to create the NeuroAnatomy Toolbox (nat) and its extensions, which we detail in this paper
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