- Author:
- GitHub <noreply@github.com>
- Date:
- 2024-12-02 10:54:23+13:00
- Desc:
- Merge pull request #1 from AnatomicMaps/annotations
Annotations and updated CellML model. Merging to allow PMR workspace to sync to `main`.
- Permanent Source URI:
- https://staging.physiomeproject.org/workspace/c3d/rawfile/bb26129a6107b4c67ff8a0fc6ad41135ec0f740c/create_annotations.py
from rdflib import Graph, Literal, RDF, URIRef, Namespace
from rdflib.namespace import DCTERMS
import pathlib
from lxml import etree
_LOCAL_ID_COUNTER = 1024
OMEXlib = Namespace('http://omex-library.org/')
LOCAL = Namespace('http://omex-library.org/annotations.ttl#')
BQBIOL = Namespace('http://biomodels.net/biology-qualifiers/')
UBERON = Namespace('http://purl.obolibrary.org/obo/UBERON_')
OPB = Namespace('http://bhi.washington.edu/OPB#')
# OPB:00154 = fluid volume
VOLUME_URI = OPB['OPB_00154']
# OPB:00509 = fluid pressure
PRESSURE_URI = OPB['OPB_00509']
# FMA:9670 = portion of blood
# UBERON:0000178 = Blood: A fluid that is composed of blood plasma and erythrocytes
BLOOD_URI = UBERON['0000178']
def _get_local_id():
global _LOCAL_ID_COUNTER
_LOCAL_ID_COUNTER += 1
return URIRef(f'local-node-{_LOCAL_ID_COUNTER}')
def get_model_ids(model_string):
root = etree.fromstring(model_string)
namespace = "http://www.cellml.org/metadata/1.0#"
attribute_name = "id"
# Collect attributes with the given name and namespace
attributes = []
for elem in root.iter():
# Fully qualified attribute name with namespace
qualified_name = f"{{{namespace}}}{attribute_name}"
if qualified_name in elem.attrib:
attributes.append(elem.attrib[qualified_name])
volume_ids = []
pressure_ids = []
flow_ids = []
for value in attributes:
if value.endswith('.blood.volume'):
volume_ids.append(value)
elif value.endswith('.blood.pressure'):
pressure_ids.append(value)
elif value.endswith('.blood.flow'):
flow_ids.append(value)
else:
print(f'Unknown ID: {value}')
return {
'volume_ids': volume_ids,
'pressure_ids': pressure_ids,
'flow_ids': flow_ids
}
def map_to_uberon_cavity(cavity_abbr):
cavity_map = {
'lv': '0016514', # Luminal space of the left ventricle of the heart
'rv': '0016509', # Luminal space of the right ventricle of the heart.
'la': '0016513', # Luminal space of the left atrium of the heart
'ra': '0016522', # luminal space of the right atrium of the heart
'pa': '0002012', # the actual artery - might not be the right term?
'lung': '0000102', # lung vasculature: The lung vasculature is composed of the tubule structures that carry blood or lymph in the lungs
'pulm-vein': '0002016', # pulmonary vein: Pulmonary veins are blood vessels that transport blood from the lungs to the heart
'brain': '0008998', # vasculature of brain: System pertaining to blood vessels in the brain
'brain-vein': '2005031', # dorsal longitudinal vein: Vessel that connects to the primitive hindbrain channel and the basilar artery at the caudal end of the medulla oblongata. Isogai et al. 2001
'aa': '0001496', # ascending aorta:
'celiac': '0001640', # celiac artery: The first major branch of the abdominal aorta.
'sup-mes': '0001182', # superior mesenteric artery
'stomach': '0000945', # stomach (there is an FMA term for vasulature of the stomach / gastric vasulature)
'spleen': '0036301', # vasculature of spleen
'pancreas': '0001264', # pancreas
'intestine': '0000160', # intestine
'colon': '0001155', # colon
'portal-vein': '0002017', # portal vein
'liver': '0006877' # vasculature of liver
}
if cavity_abbr in cavity_map.keys():
return UBERON[cavity_map[cavity_abbr]]
else:
print(f'Unknown cavity abbreviation: {cavity_abbr}')
return UBERON['0001062'] # anatomical entity
def create_local_blood_cavity_definition(rdf_graph, cavity_uri):
# check if a suitable local entity exists
query = """
SELECT ?subject
WHERE {
?subject ?predicate ?object
}
"""
results = rdf_graph.query(query, initBindings={
'predicate': BQBIOL['isPartOf'],
'object': cavity_uri
})
for row in results:
#print(f'Found an existing local node to use: {row.subject}')
return row.subject
local_node = LOCAL[_get_local_id()]
rdf_graph.add((local_node, BQBIOL['is'], BLOOD_URI))
rdf_graph.add((local_node, BQBIOL['isPartOf'], cavity_uri))
return local_node
def create_blood_volume_annotation(rdf_graph, model, model_id):
model_uri = OMEXlib[f'{model.as_posix()}#{model_id}']
cavity = model_id.split('.')[0]
cavity_uri = map_to_uberon_cavity(cavity)
local_node = create_local_blood_cavity_definition(rdf_graph, cavity_uri)
rdf_graph.add((model_uri, BQBIOL['isPropertyOf'], local_node))
rdf_graph.add((model_uri, BQBIOL['isVersionOf'], VOLUME_URI))
def create_blood_pressure_annotation(rdf_graph, model, model_id):
model_uri = OMEXlib[f'{model.as_posix()}#{model_id}']
cavity = model_id.split('.')[0]
cavity_uri = map_to_uberon_cavity(cavity)
local_node = create_local_blood_cavity_definition(rdf_graph, cavity_uri)
rdf_graph.add((model_uri, BQBIOL['isPropertyOf'], local_node))
rdf_graph.add((model_uri, BQBIOL['isVersionOf'], PRESSURE_URI))
if __name__ == "__main__":
cellml_dir = pathlib.Path('models')
cellml_file = cellml_dir / 'cvs-model.cellml'
if cellml_file.is_file():
model_string = cellml_file.read_text()
#print(model_string)
model_ids = get_model_ids(model_string)
#print(model_ids)
else:
print(f"CellML model file doesn't exist: {cellml_file}")
exit(-1)
g = Graph()
g.bind('OPB', OPB)
g.bind('UBERON', UBERON)
g.bind('OMEXlib', OMEXlib)
g.bind('local', LOCAL)
g.bind('bqbiol', BQBIOL)
for volume in model_ids['volume_ids']:
create_blood_volume_annotation(g, cellml_file, volume)
for pressure in model_ids['pressure_ids']:
create_blood_pressure_annotation(g, cellml_file, pressure)
with open('annotations.ttl', 'w') as f:
f.write(g.serialize(format='ttl'))
