A set of tools for navigating, viewing and manipulating hierarchical brain atlases
Project description
Brain Atlas Toolkit
This package is intended as a toolkit for manipulating hierarchical brain atlases. For example, the Allen Mouse Brain Atlas has a parent-child ontology of this structure:
{
"id": 997,
"acronym": "root",
"name": "root",
"graph_order": 0,
"parent_structure_id": null,
"children": [
{
"id": 8,
"acronym": "grey",
"name": "Basic cell groups and regions",
"graph_order": 1,
"parent_structure_id": 997,
"children": [
{
"id": 567,
"acronym": "CH",
"name": "Cerebrum",
"graph_order": 2,
"parent_structure_id": 8,
"children": [
...
Requirements
- python>=3.7
- A system-wide installation of graphviz: https://www.graphviz.org/ if you are going to use any of the visualization tools in this package.
Examples
Load a custom brain atlas from JSON file
from brain_atlas_toolkit import graph_tools
json_file = "allen_ontology.json"
with open(json_file,'r') as infile:
ontology_dict = json.load(infile)
Initialize ontology graph
ontology_graph = graph_tools.Graph(ontology_dict)
Get all progeny (a.k.a. descendents or subregions) of a region of interest returned in a list
ontology_graph.get_progeny('Somatomotor areas')
which returns:
['Somatomotor areas, Layer 1', 'Somatomotor areas, Layer 2/3', 'Somatomotor areas, Layer 5', 'Somatomotor areas, Layer 6a', 'Somatomotor areas, Layer 6b', 'Primary motor area', 'Primary motor area, Layer 1', 'Primary motor area, Layer 2/3', 'Primary motor area, Layer 5', 'Primary motor area, Layer 6a', 'Primary motor area, Layer 6b', 'Secondary motor area', 'Secondary motor area, layer 1', 'Secondary motor area, layer 2/3', 'Secondary motor area, layer 5', 'Secondary motor area, layer 6a', 'Secondary motor area, layer 6b']
Print a branch of the ontology
ontology_graph.print_branch('Somatomotor areas')
which returns
0 Somatomotor areas
1 Somatomotor areas, Layer 1
1 Somatomotor areas, Layer 2/3
1 Somatomotor areas, Layer 5
1 Somatomotor areas, Layer 6a
1 Somatomotor areas, Layer 6b
1 Primary motor area
2 Primary motor area, Layer 1
2 Primary motor area, Layer 2/3
2 Primary motor area, Layer 5
2 Primary motor area, Layer 6a
2 Primary motor area, Layer 6b
1 Secondary motor area
2 Secondary motor area, layer 1
2 Secondary motor area, layer 2/3
2 Secondary motor area, layer 5
2 Secondary motor area, layer 6a
2 Secondary motor area, layer 6b
Print a branch of the ontology and control the depth of the tree
ontology_graph.print_branch('Somatomotor areas',stoplevel=1)
which returns
0 Somatomotor areas
1 Somatomotor areas, Layer 1
1 Somatomotor areas, Layer 2/3
1 Somatomotor areas, Layer 5
1 Somatomotor areas, Layer 6a
1 Somatomotor areas, Layer 6b
1 Primary motor area
1 Secondary motor area
Visualize a branch of the ontology
digraph = ontology_graph.visualize_graph('Somatomotor areas',level=2)
digraph.format='png' # control the image type; supports png, pdf and other formats
digraph.view()
The last line will save and then open up an image in your default image viewer application. The image should look like this (click image to view zoomed in version):
For full documentation of the digraph
object, see the graphviz Python API documentation: https://graphviz.readthedocs.io/en/stable/
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