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Online conversion of reconstructed neural morphologies into standardized SWC format

Authors :
Giorgio Ascoli
Ketan Mehta
Bengt Ljungquist
James Ogden
Sumit Nanda
Ruben Ascoli
Lydia Ng
Publication Year :
2023
Publisher :
Research Square Platform LLC, 2023.

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. Additionally, we introduce xyz2swc, a free online service that converts all 23 reconstruction formats (and 68 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).

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........86a2724a3957ba95da76432c5a97997e
Full Text :
https://doi.org/10.21203/rs.3.rs-2693387/v1