The C. elegans Connectome Toolbox: an open, extensible framework for multimodal connectomic data integration and analysis

The nematode C. elegans is one of the best studied model organisms in biology. Since the initial description of the C. elegans neuronal connectome by White and colleagues, numerous studies have mapped and analyzed the connectome, and released structured datasets of the connectivity, often merging and adding to previous versions. These datasets now serve as foundational resources that underpin studies into the neuronal basis of C. elegans behavior. In spite of their high utility, heterogeneity in the different datasets and their annotation conventions obscures direct comparison where discrepancies between connectomes frequently stem from differences in coverage or nomenclature rather than genuine biological disagreement. Additionally, datasets describing new connectivity modalities - contact-based (the contactome), extrasynaptic (monoaminergic and neuropeptidergic), and functional connectivity - have also recently become available. Thus, there is a need for a unified framework providing standardized access to these diverse datasets while preserving their individual provenance. Here, we present the C. elegans Connectome Toolbox, a comprehensive framework for consolidating, curating and validating historical and newly published multimodal C. elegans connectivity data. Connectome Toolbox includes an accessible online resource (https://openworm.org/ConnectomeToolbox) for interactive data exploration and is accompanied by a Python library for programmatic access. We demonstrate the utility of the toolbox through a series of analyses that illustrate how connectome data can be explored, visualized, and compared across modalities, including integration of the anatomical connectome with a comprehensive neurotransmitter atlas, and comparison with computational models of C. elegans neural circuits.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-11-05
DOI
https://doi.org/10.64898/2026.11.04.764366
Primary Topic
Neurobiology and Insect Physiology Research
Type
preprint
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preprint

The C. elegans Connectome Toolbox: an open, extensible framework for multimodal connectomic data integration and analysis

Padraig Gleeson, Ankur Sinha, Stephen Larson, Netta Cohen et al.
bioRxiv (Cold Spring Harbor Laboratory)
Neurobiology and Insect Physiology Research
preprint

The C. elegans Connectome Toolbox: an open, extensible framework for multimodal connectomic data integration and analysis

Padraig Gleeson, Ankur Sinha, Stephen Larson, Netta Cohen, Yasinthan Vickneswaran, Adam Ponzi
preprint en

Abstract

The nematode C. elegans is one of the best studied model organisms in biology. Since the initial description of the C. elegans neuronal connectome by White and colleagues, numerous studies have mapped and analyzed the connectome, and released structured datasets of the connectivity, often merging and adding to previous versions. These datasets now serve as foundational resources that underpin studies into the neuronal basis of C. elegans behavior. In spite of their high utility, heterogeneity in the different datasets and their annotation conventions obscures direct comparison where discrepancies between connectomes frequently stem from differences in coverage or nomenclature rather than genuine biological disagreement. Additionally, datasets describing new connectivity modalities - contact-based (the contactome), extrasynaptic (monoaminergic and neuropeptidergic), and functional connectivity - have also recently become available. Thus, there is a need for a unified framework providing standardized access to these diverse datasets while preserving their individual provenance. Here, we present the C. elegans Connectome Toolbox, a comprehensive framework for consolidating, curating and validating historical and newly published multimodal C. elegans connectivity data. Connectome Toolbox includes an accessible online resource (https://openworm.org/ConnectomeToolbox) for interactive data exploration and is accompanied by a Python library for programmatic access. We demonstrate the utility of the toolbox through a series of analyses that illustrate how connectome data can be explored, visualized, and compared across modalities, including integration of the anatomical connectome with a comprehensive neurotransmitter atlas, and comparison with computational models of C. elegans neural circuits.

bioRxiv (Cold Spring Harbor Laboratory)
University of Leeds (GB), Open Geospatial Consortium (GB), University College London (GB)
Neurobiology and Insect Physiology Research
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