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A morphology repair tool

Project description

Introduction

NeuroR is a collection of tools to repair morphologies.

Citation

Cite NeuroR with the following DOI:

https://zenodo.org/badge/244944511.svg

NeuroR implements the methods discussed in the following paper:

Anwar H., Riachi I., Schürmann F., Markram H. (2009). “An approach to capturing neuron morphological diversity,” in Computational Neuroscience: Realistic Modeling for Experimentalistsed. De Schutter E., editor. (Cambridge: The MIT Press) 211–232

DOI: 10.7551/mitpress/9780262013277.003.0010

Morphology repair with NeuroR

There are presently three types of repair which are outlined below.

Sanitization

This is the process of curating a morphological file. It currently:

  • removes zero-length segments
  • raises if the morphology has no soma
  • raises if the morphology has negative diameters

Note: more functionality may be added in the future

Cut plane repair

The cut plane repair aims at regrowing part of a morphologies that have been cut out when the cell has been experimentally sliced.

neuror cut-plane repair contains the collection of CLIs to perform this repair.

Additionally, there are CLIs for the cut plane detection and writing detected cut planes to JSON files:

  • If the cut plane is aligned with one of the X, Y or Z axes, the cut plane detection can be done automatically with the CLIs:
neuror cut-plane file
neuror cut-plane folder
  • If the cut plane is not one the X, Y or Z axes, the detection has to be performed through the helper web application that can be launched with the following CLI:
neuror cut-plane hint

Unravelling

Unravelling is the action of “stretching” the cell that has been shrunk because of the dehydratation caused by the slicing.

The unravelling CLI sub-group is:

neuror unravel

Info

Unravelling is also part of the “full” process that performs unravelling and cut plane repair. The corresponding CLI is:

neuror cut-plane repair full

The unravelling algorithm can be described as follows:

  • Segments are unravelled iteratively.
  • Each segment direction is replaced by the averaged direction in a sliding window around this segment.
  • The original segment length is preserved.
  • The start position of the new segment is the end of the latest unravelled segment.

Installation

NeuroR is distributed as a Python package available on PyPi:

$ pip install --pre neuror[plotly]

Note: NeuroR relies on the experimental version 2 of NeuroM, hence the --pre option.

Only Python 3.6 and above are supported.

Prior to running pip install, we recommend updating pip in your virtual environment unless you have a compelling reason not to do it:

$ pip install --upgrade pip setuptools

Contributing

If you want to improve the project or you see any issue, every contribution is welcome. Please check the contribution guidelines for more information.

License

NeuroR is licensed under the terms of the GNU Lesser General Public License version 3. Refer to COPYING.LESSER and COPYING for details.

Project details


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