Transient morphogenetic constraints organize self-assembling axon neighborhoods for robust yet flexible wiring

Transient morphogenetic constraints organize self-assembling axon neighborhoods for robust yet flexible wiring Overview This repository provides data supporting the study of constrained stochastic assembly in the C. elegans nerve ring. It includes embryonic morphogenetic imaging, curated EM-derived neurite contact and spatial domain datasets, and agent-based innervation simulation outputs and intermediate processed data used in all analyses. Source code for agent-based simulations and figure generation is maintained in a companion GitHub repository (https://github.com/cabrittin/constrained-innervation-abm/), with versioned releases archived for reproducibility. Documentation specifies data formats, software dependencies, and instructions for reproducing the analyses and simulations. Data Organization (Conceptual Structure) Conceptually, the datasets are organized into the following categories:- Embryonic imaging data used to identify rosettes, corridor cells and pioneer axon trajectories. - EM-derived neurite contact, spatial domain datasets and neighborhood metrics. - Agent-based simulation outputs Due to file size constraints, datasets are provided as individually downloadable files and compressed archives rather than a nested directory structure. File Manifest exemplar_embryo_rosette_corridor_id.tar.bz2: Exemplar embryo used to identify rosettes and corridor cells; includes raw embryo image and associated AceTree lineage file abm_sim_model54.tar.bz2: ABM simulations for local self-organizing model 54; raw simulation data used for Fig. 5E-M and Fig. S9 abm_sim_model58.tar.bz2: ABM simulations for local self-organizing model 58; raw simulation data used for Fig. 6A,B,C,F,G,H; Fig. 7A-E; Fig. S9 abm_sim_model65.tar.bz2: ABM simulations for local self-organizing model 65; raw simulation data used for Fig. 7F abm_sim_pi_models.tar.bz2: ABM simulations for positionally informed models 66, 67, 68; ABM simulations for positionally informed negative control; raw simulation data used for Fig. S7B Code Availability Source code for agent-based simulations, data processing, and figure generation is hosted in a companion GitHub repository: GitHub: https://github.com/cabrittin/constrained-innervation-abm/ Versioned releases of the codebase are archived via Zenodo for long-term reproducibility. Reproducibility Documentation in the GitHub repository specifies:- Software dependencies- Execution instructions- Scripts to reproduce figures and analyses Processed datasets in this repository correspond to the analyses reported in the manuscript. Citation Citation for this dataset will be updated upon manuscript publication. Zenodo DOI: 10.5281/zenodo.18393124 License Data are released under the CC-BY 4.0 License, unless otherwise noted.Code is released under the MIT License (see GitHub repository). Contact For questions, contact:Christopher Brittin (corresponding author)