Package: brain-atlas-toolkit
Brain Atlas ToolkitThis 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":[...Requirementspython>=3.7A system-wide installation of graphviz:https://www.graphviz.org/if you are going to use any of the visualization tools in this package.ExamplesLoad a custom brain atlas from JSON filefrombrain_atlas_toolkitimportgraph_toolsimportjsonjson_file="allen_ontology.json"withopen(json_file,'r')asinfile:ontology_dict=json.load(infile)Note that this JSON file must have the structure of the example ontology shown above. The minimal set of keys in each element are:idnameparent_structure_idInitialize ontology graphontology_graph=graph_tools.Graph(ontology_dict)Get all progeny (a.k.a. descendents or subregions) of a region of interest returned in a flattened listontology_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']Get the parent name of a region of interestontology_graph.get_parent('Somatomotor areas')which returns:IsocortexGet the integer id of a region of interestontology_graph.get_id('Somatomotor areas')which returns:500Get the acronym name of a region of interestontology_graph.get_parent('Somatomotor areas')which returns:MOPrint a branch of the ontologyontology_graph.print_branch('Somatomotor areas')which returns0 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 6bPrint a branch of the ontology and control the depth of the treeontology_graph.print_branch('Somatomotor areas',stoplevel=1)which returns0 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 areaThe default stoplevel value is -1, which means print the entire tree to max depth.Visualize a branch of the ontologydigraph=ontology_graph.visualize_graph('Somatomotor areas',level=2)digraph.format='png'# control the image type; supports png, pdf and other formatsdigraph.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 thedigraphobject, see the graphviz Python API documentation:https://graphviz.readthedocs.io/en/stable/