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.
Keywords: D. melanogaster; analysis software; computational biology; connectomics; mouse; neural circuits; neuroanatomy; neuronal morphology; neuroscience; open-source; systems biology; zebrafish.
© 2020, Bates et al.