The natverse, a versatile toolbox for combining and analysing neuroanatomical data

Area of Science:

• Neuroscience
• Bioinformatics
• Computational Biology

Background:

• Analyzing large-scale neuron data is complex, requiring significant effort in managing documentation, dependencies, and software environments.
• Current tools often lack interoperability, hindering comparative analysis of neuronal morphology and connectivity across datasets.

Purpose of the Study:

• To develop an integrated, open-source software environment to streamline large-scale neuron data analysis.
• To facilitate comparative analysis of neuronal morphology and connectivity across diverse datasets and imaging modalities.

Main Methods:

• Development of the natverse, a suite of interoperable open-source R packages.
• Implementation of functionalities for reading local/remote data, visualization, clustering, and graph-theoretic analysis.
• Integration of Drosophila neuroanatomical light and electron microscopy connectomic datasets.

Main Results:

• The natverse provides a unified environment for reading, analyzing, and visualizing neuron data at scale.
• Enables cross-neuron comparisons of morphology and connectivity within common template spaces.
• Facilitates transformations between different template spaces and imaging modalities.
• Demonstrates integration of extensive Drosophila neuroanatomical datasets.

Conclusions:

• The natverse significantly reduces the effort required for large-scale neuron data analysis.
• It serves as an accessible platform for neuroscientists to tackle complex analysis challenges.
• Promotes community contribution through an open platform for developing and sharing new code and packages.