Online conversion of reconstructed neural morphologies into standardized SWC format

Ketan Mehta, Bengt Ljungquist, James Ogden, Sumit Nanda, Ruben G. Ascoli, Lydia Ng and Giorgio A. Ascoli ()
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Ketan Mehta: George Mason University
Bengt Ljungquist: George Mason University
James Ogden: George Mason University
Sumit Nanda: George Mason University
Ruben G. Ascoli: George Mason University
Lydia Ng: Allen Institute for Brain Science
Giorgio A. Ascoli: George Mason University

Nature Communications, 2023, vol. 14, issue 1, 1-12

Abstract: Abstract Digital reconstructions provide an accurate and reliable way to store, share, model, quantify, and analyze neural morphology. Continuous advances in cellular labeling, tissue processing, microscopic imaging, and automated tracing catalyzed a proliferation of software applications to reconstruct neural morphology. These computer programs typically encode the data in custom file formats. The resulting format heterogeneity severely hampers the interoperability and reusability of these valuable data. Among these many alternatives, the SWC file format has emerged as a popular community choice, coalescing a rich ecosystem of related neuroinformatics resources for tracing, visualization, analysis, and simulation. This report presents a standardized specification of the SWC file format. In addition, we introduce xyz2swc, a free online service that converts all 26 reconstruction formats (and 72 variations) described in the scientific literature into the SWC standard. The xyz2swc service is available open source through a user-friendly browser interface ( https://neuromorpho.org/xyz2swc/ui/ ) and an Application Programming Interface (API).

Date: 2023
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DOI: 10.1038/s41467-023-42931-x

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