treem 1.2.0.dev19

Tree-like morphology data processing tool

treem – Neuron Morphology Processing Tool

The treem module (pronounced "trim") provides data structures and command-line tools for accessing and manipulating digital reconstructions of neuronal morphology in the Stockley-Wheal-Cannon (SWC) format.

Release
Platforms
Development
Reference

Main classes

Access to morphological data from the source code is provided through the classes Tree, Node, Morph, and SWC:

• Tree for recursive tree data structure
• Node for morphology data storage
• Morph for neuron morphology representation
• SWC for definitions of the data format

Commands

Common operations with SWC files can be performed using the swc command-line tool:

swc <command> [options] file

Alternatively:

swc <command> file [file ...] [options] 

List of swc commands:

• check tests morphology reconstruction for structural consistency
• convert converts morphology to compliant SWC format
• find locates single nodes in the reconstruction
• measure calculates morphometric features
• modify manipulates morphology reconstruction
• render displays 3D model of the reconstruction
• repair corrects reconstruction errors
• view shows morphology structure

Installation

Install the latest stable release:

pip install treem

Install a development version:

pip install git+https://github.com/a1eko/treem

See also pip documentation for installation alternatives.

Dependencies

The treem module has minimal runtime dependencies:

• python >= 3.7
• matplotlib
• numpy
• PyOpenGL optional, enables swc render command

For testing and documentation, treem requires additional development packages with third-party support:

• sphinx with napoleon and programoutput extensions
• sphinx-rtd-theme
• pytest with optional pytest-cov plugin
• coverage

Documentation

Documentation is available online at Read the Docs.

Citation

• Hjorth JJJ, Hellgren Kotaleski J, Kozlov A (2021) Predicting Synaptic Connectivity for Large-Scale Microcircuit Simulations Using Snudda. Neuroinformatics, 19(4):685-701. DOI: 10.1007/s12021-021-09531-w.

• Kozlov AK (2021) Treem - neuron morphology processing tool. Zenodo. DOI: 10.5281/zenodo.4890844.

Funding

Horizon 2020 Framework Programme (785907, HBP SGA2); Horizon 2020 Framework Programme (945539, HBP SGA3); Vetenskapsrådet (VR-M-2017-02806, VR-M-2020-01652); Swedish e-science Research Center (SeRC); KTH Digital Futures.

We acknowledge the use of Fenix Infrastructure resources, which are partially funded from the European Union's Horizon 2020 research and innovation programme through the ICEI project under the grant agreement No. 800858.

The computations and testing were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS), partially funded by the Swedish Research Council through grant agreement no. 2022-06725, also by the Swedish National Infrastructure for Computing (SNIC) at PDC KTH partially funded by the Swedish Research Council through grant agreement no. 2018-05973.