A morphology repair tool
Project description
Introduction
NeuroR is a collection of tools to repair morphologies.
Citation
Cite NeuroR with the following DOI:
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
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 folderIf 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 hintUnravelling
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 unravelThe 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 setuptoolsContributing
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.
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