| Literature DB >> 32286229 |
Alexander Shakeel Bates1, James D Manton1, Sridhar R Jagannathan2, Marta Costa1,2, Philipp Schlegel1,2, Torsten Rohlfing3, Gregory Sxe Jefferis1,2.
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.Entities:
Keywords: D. melanogaster; analysis software; computational biology; connectomics; mouse; neural circuits; neuroanatomy; neuronal morphology; neuroscience; open-source; systems biology; zebrafish
Year: 2020 PMID: 32286229 PMCID: PMC7242028 DOI: 10.7554/eLife.53350
Source DB: PubMed Journal: Elife ISSN: 2050-084X Impact factor: 8.140