Neuroscientists, therefore, need to tackle large amounts of morphological data, often writing custom code to enable repeated analysis using their specific requirements. 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. Neuroanatomy has become a large-scale, digital and quantitative discipline. 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. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse also enables transformations between different template spaces and imaging modalities. 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 allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments.
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