def setup(name, type):
n = NeuronClass(name)
n.type(type)
n.member(P.Neuron(name + "R"))
n.member(P.Neuron(name + "L"))
net.neuron(n)
return n
def __init__(self,
pre_cell=None,
post_cell=None,
number=None,
syntype=None,
synclass=None,
termination=None,
**kwargs):
super(Connection, self).__init__(**kwargs)
Connection.ObjectProperty('post_cell', owner=self, value_type=Cell)
Connection.ObjectProperty('pre_cell', owner=self, value_type=Cell)
Connection.DatatypeProperty('number', owner=self)
Connection.DatatypeProperty('synclass', owner=self)
Connection.DatatypeProperty('syntype', owner=self)
Connection.DatatypeProperty('termination', owner=self)
if isinstance(pre_cell, P.Cell):
self.pre_cell(pre_cell)
elif pre_cell is not None:
warnings.warn(
'Passing bare strings for PyOpenWorm.Connection cells is' +
' deprecated. PyOpenWorm.Cell objects should be passed in' +
' instead.', DeprecationWarning)
self.pre_cell(P.Neuron(name=pre_cell, conf=self.conf))
if (isinstance(post_cell, P.Cell)):
self.post_cell(post_cell)
elif post_cell is not None:
warnings.warn(
'Passing bare strings for PyOpenWorm.Connection cells is' +
' deprecated. PyOpenWorm.Cell objects should be passed in' +
' instead.', DeprecationWarning)
self.post_cell(P.Neuron(name=post_cell, conf=self.conf))
if isinstance(termination, six.string_types):
termination = termination.lower()
if termination in ('neuron', Termination.Neuron):
self.termination(Termination.Neuron)
elif termination in ('muscle', Termination.Muscle):
self.termination(Termination.Muscle)
if isinstance(number, int):
self.number(int(number))
elif number is not None:
raise Exception("Connection number must be an int, given %s" %
number)
if isinstance(syntype, six.string_types):
syntype = syntype.lower()
if syntype in ('send', SynapseType.Chemical):
self.syntype(SynapseType.Chemical)
elif syntype in ('gapjunction', SynapseType.GapJunction):
self.syntype(SynapseType.GapJunction)
if isinstance(synclass, six.string_types):
self.synclass(synclass)
def __init__(self,
pre_cell=None,
post_cell=None,
number=None,
syntype=None,
synclass=None,
termination=None,
**kwargs):
super(Connection, self).__init__(**kwargs)
Connection.ObjectProperty('post_cell', owner=self, value_type=Cell)
Connection.ObjectProperty('pre_cell', owner=self, value_type=Cell)
Connection.DatatypeProperty('number', owner=self)
Connection.DatatypeProperty('synclass', owner=self)
Connection.DatatypeProperty('syntype', owner=self)
Connection.DatatypeProperty('termination', owner=self)
if isinstance(pre_cell, P.Cell):
self.pre_cell(pre_cell)
elif pre_cell is not None:
# TODO: don't assume that the pre_cell is a neuron
self.pre_cell(P.Neuron(name=pre_cell, conf=self.conf))
if (isinstance(post_cell, P.Cell)):
self.post_cell(post_cell)
elif post_cell is not None:
# TODO: don't assume that the post_cell is a neuron
self.post_cell(P.Neuron(name=post_cell, conf=self.conf))
if isinstance(termination, basestring):
termination = termination.lower()
if termination in ('neuron', Termination.Neuron):
self.termination(Termination.Neuron)
elif termination in ('muscle', Termination.Muscle):
self.termination(Termination.Muscle)
if isinstance(number, int):
self.number(int(number))
elif number is not None:
raise Exception("Connection number must be an int, given %s" %
number)
if isinstance(syntype, basestring):
syntype = syntype.lower()
if syntype in ('send', SynapseType.Chemical):
self.syntype(SynapseType.Chemical)
elif syntype in ('gapjunction', SynapseType.GapJunction):
self.syntype(SynapseType.GapJunction)
if isinstance(synclass, basestring):
self.synclass(synclass)
def upload_receptors_and_innexins():
try:
conn = sqlite3.connect(SQLITE_DB_LOC)
cur = conn.cursor()
w = P.Worm()
n = P.Network()
w.neuron_network(n)
# insert neurons.
# save
# get the receptor (354) and innexin (355)
cur.execute("""
SELECT DISTINCT a.Entity, b.Entity
FROM
tblrelationship q,
tblrelationship r,
tblentity a,
tblentity b
where q.EnID1=a.id and q.Relation = '1515' and q.EnID2='1'
and r.EnID1=a.id and r.Relation = '354' and r.EnID2=b.id
""")
for r in cur.fetchall():
neuron_name = str(r[0])
receptor = str(r[1])
neur = P.Neuron(name=neuron_name)
neur.receptor(receptor)
n.neuron(neur)
cur.execute("""
SELECT DISTINCT a.Entity, b.Entity
FROM
tblrelationship q,
tblrelationship r,
tblentity a,
tblentity b
where q.EnID1=a.id and q.Relation = '1515' and q.EnID2='1'
and r.EnID1=a.id and r.Relation = '355' and r.EnID2=b.id
""")
for r in cur.fetchall():
neuron_name = str(r[0])
innexin = str(r[1])
neur = P.Neuron(name=neuron_name)
neur.innexin(innexin)
n.neuron(neur)
n.save()
#second step, get the relationships between them and add them to the graph
except Exception:
traceback.print_exc()
finally:
conn.close()
def scoring_neurons(self):
print 'calculating neuron completion scores'
score = 0
for n in P.Neuron().load():
score = 0
if len(n.type()) > 0:
score += 1
if len(n.receptor()) > 0:
score += 1
if len(n.innexin()) > 0:
score += 1
if len(n.neurotransmitter()) > 0:
score += 1
if len(n.neuropeptide()) > 0:
score += 1
if len(n.neighbor()) > 0:
score += 1
if len(n.connection()) > 0:
score += 1
for ch in n.channel():
score += IonChannel.objects.get(name=str(ch.name())).completion
score = int((float(score) / (7 + 5 * len(n.channel()))) * float(5))
neuron = Neuron(name=n.name(), completion=score)
neuron.save()
print 'done'
def upload_neurons():
try:
conn = sqlite3.connect(SQLITE_DB_LOC)
cur = conn.cursor()
ev = P.Evidence(title="C. elegans sqlite database")
w = P.Worm()
n = P.Network()
w.neuron_network(n)
# insert neurons.
# save
cur.execute("""
SELECT DISTINCT a.Entity FROM tblrelationship, tblentity a, tblentity b
where EnID1=a.id and Relation = '1515' and EnID2='1'
""")
for r in cur.fetchall():
neuron_name = str(r[0])
n.neuron(P.Neuron(name=neuron_name))
ev.asserts(n)
ev.save()
#second step, get the relationships between them and add them to the graph
print("uploaded neurons")
except Exception:
traceback.print_exc()
finally:
conn.close()
def upload_types():
import csv
ev = P.Evidence(title="neurons.csv")
w = P.Worm()
net = w.neuron_network.one()
data = dict()
for x in csv.reader(open('../aux_data/neurons.csv'), delimiter=';'):
types = []
name = x[0]
types_string = x[1]
if 'sensory' in (types_string.lower()):
types.append('sensory')
if 'interneuron' in (types_string.lower()):
types.append('interneuron')
if 'motor' in (types_string.lower()):
types.append('motor')
data[name] = types
for name in data:
n = P.Neuron(name=name)
types = data[name]
for t in types:
n.type(t)
net.neuron(n)
ev.asserts(net)
ev.save()
print("uploaded types")
def upload_muscles():
""" Upload muscles and the neurons that connect to them
"""
try:
ev = P.Evidence(title="C. elegans sqlite database")
conn = sqlite3.connect(SQLITE_DB_LOC)
cur = conn.cursor()
w = P.Worm()
cur.execute("""
SELECT DISTINCT a.Entity, b.Entity
FROM tblrelationship innervatedBy, tblentity b, tblentity a, tblrelationship type_b
WHERE innervatedBy.EnID1=a.id and innervatedBy.Relation = '1516' and innervatedBy.EnID2=b.id
and type_b.EnID1 = b.id and type_b.Relation='1515' and type_b.EnID2='1519'
""") # 1519 is the
for r in cur.fetchall():
neuron_name = str(r[0])
muscle_name = str(r[1])
m = P.Muscle(muscle_name)
n = P.Neuron(neuron_name)
w.muscle(m)
m.innervatedBy(n)
ev.asserts(w)
ev.save()
#second step, get the relationships between them and add them to the graph
print("uploaded muscles")
except Exception:
traceback.print_exc()
finally:
conn.close()
def set(self, ob, **kwargs):
self.real_neighbor(ob)
if isinstance(ob, NeuronClass):
ob_name = ob.name()
this_name = self.owner.name()
for x in ob.member():
# Get the name for the neighbor
# XXX:
try:
n = x.name()
side = n[n.find(ob_name) + len(ob_name):]
name_here = this_name + side
this_neuron = P.Neuron(name_here)
self.owner.member(this_neuron)
this_neuron.neighbor(x, **kwargs)
except ValueError:
# XXX: could default to all-to-all semantics
print(
'Do not recoginze the membership of this neuron/neuron class',
ob)
elif isinstance(ob, Neuron):
for x in self.owner.member:
x.neighbor(ob)
def upload_neurons():
try:
#TODO: Improve this evidence marker
ev = P.Evidence(title="C. elegans Cell List - WormBase.csv")
w = WORM
n = NETWORK
w.neuron_network(n)
# insert neurons.
i = 0
with open(CELL_NAMES_SOURCE) as csvfile:
csvreader = csv.reader(csvfile)
for num, line in enumerate(csvreader):
if num < 4: # skip rows with no data
continue
if line[5] == '1': # neurons marked in this column
neuron_name = normalize(line[0]).upper()
n.neuron(P.Neuron(name=neuron_name))
i = i + 1
ev.asserts(n)
#second step, get the relationships between them and add them to the graph
print("uploaded " + str(i) + " neurons")
except Exception:
traceback.print_exc()
def aneuron(self, name):
"""
Get a neuron by name
:param name: Name of a c. elegans neuron
:returns: Corresponding neuron to the name given
:rtype: PyOpenWorm.Neuron
"""
return PyOpenWorm.Neuron(name)
def test_INS_26_neuropeptide_neuron_list(self):
"""
This test verifies that the set of neurons which contain the
neuropeptide INS-26 is correct (the list is given below).
"""
neuronlist = PyOpenWorm.Neuron()
neuronlist.neuropeptide("INS-26")
thlist = set(x.name() for x in neuronlist.load())
self.assertEqual(set(['ASEL', 'ASER', 'ASIL', 'ASIR']), thlist)
def test_TH_neuropeptide_neuron_list(self):
"""
This test verifies that the set of neurons which contain the
neuropeptide TH is correct (the list is given below).
"""
neuronlist = PyOpenWorm.Neuron()
neuronlist.neuropeptide("TH")
thlist = set(x.name() for x in neuronlist.load())
self.assertEqual(
set(['CEPDR', 'PDER', 'CEPDL', 'PDEL', 'CEPVR', 'CEPVL']), thlist)
def get(self, request, format=None):
Cells = []
try:
for neuron in P.Neuron().load():
Cells.append(Cell(name=str(neuron.name())))
for muscle in P.Muscle().load():
Cells.append(Cell(name=str(muscle.name())))
finally:
print "done"
serializer = CellSerializer(Cells, many=True)
return Response(serializer.data)
def get(self, request, format=None):
Neurons = []
try:
for neuron in P.Neuron().load():
Neurons.append(Neuron(name=str(neuron.name())))
finally:
print "done"
Neurons.sort(key=operator.attrgetter('name'))
serializer = NeuronSerializer(Neurons, many=True)
return Response(serializer.data)
def __init__(self,
pre_cell=None,
post_cell=None,
number=None,
syntype=None,
synclass=None,
**kwargs):
Relationship.__init__(self, **kwargs)
Connection.DatatypeProperty('syntype', owner=self)
Connection.ObjectProperty('pre_cell', owner=self, value_type=Neuron)
Connection.ObjectProperty('post_cell', owner=self, value_type=Neuron)
Connection.DatatypeProperty('synclass', owner=self)
Connection.DatatypeProperty('number', owner=self)
if isinstance(pre_cell, P.Neuron):
self.pre_cell(pre_cell)
elif pre_cell is not None:
self.pre_cell(P.Neuron(name=pre_cell, conf=self.conf))
if (isinstance(post_cell, P.Neuron)):
self.post_cell(post_cell)
elif post_cell is not None:
self.post_cell(P.Neuron(name=post_cell, conf=self.conf))
if isinstance(number, int):
self.number(int(number))
elif number is not None:
raise Exception("Connection number must be an int, given %s" %
number)
if isinstance(syntype, basestring):
syntype = syntype.lower()
if syntype in ('send', SynapseType.Chemical):
self.syntype(SynapseType.Chemical)
elif syntype in ('gapjunction', SynapseType.GapJunction):
self.syntype(SynapseType.GapJunction)
if isinstance(synclass, basestring):
self.synclass(synclass)
def _get_cell_info(cells):
import PyOpenWorm as P
print("Connecting to the PyOpenWorm database...")
P.connect()
#Get the worm object.
worm = P.Worm()
#Extract the network object from the worm object.
net = worm.neuron_network()
#Go through our list and get the neuron object associated with each name.
#Store these in another list.
some_neurons = [P.Neuron(name) for name in cells]
all_neuron_info = collections.OrderedDict()
all_muscle_info = collections.OrderedDict()
for neuron in some_neurons:
print("=====Checking properties of: %s"%neuron)
print neuron.triples()
print neuron.__class__
short = ') %s'%neuron.name()
if 'motor' in neuron.type():
short = 'Mo%s'%short
if 'sensory' in neuron.type():
short = 'Se%s'%short
if 'interneuron' in neuron.type():
short = 'In%s'%short
if _is_muscle(neuron.name()):
short = 'Mu%s'%short
short = '(%s'%short
if 'GABA' in neuron.neurotransmitter():
short = '- %s'%short
elif len(neuron.neurotransmitter())==0:
short = '? %s'%short
else:
short = '+ %s'%short
info = (neuron, neuron.type(), neuron.receptor(), neuron.neurotransmitter(), short)
#print dir(neuron)
if _is_muscle(neuron.name()):
all_muscle_info[neuron.name()] = info
else:
all_neuron_info[neuron.name()] = info
return all_neuron_info, all_muscle_info
def interneurons(self):
"""
Get all interneurons
:returns: A iterable of all interneurons
:rtype: iter(Neuron)
"""
# TODO: make sure these belong to *this* Network
n = P.Neuron()
n.type('interneuron')
for x in n.load():
yield x
def get(self,request, format=None):
print "in cell channel get data set view"
serializer_class = ChannelSerializer
cellname = self.request.query_params.get('cellname', None)
if cellname==None:
Channels=[]
else:
neurons=[]
muscles=[]
for n in P.Neuron().load():
neurons.append(n.name())
for m in P.Muscle().load():
muscles.append(m.name())
if cellname in neurons:
Channels=[]
for ch in P.Neuron(name=str(cellname)).channel():
Channels.append(Channel(name=ch.name()))
if cellname in muscles:
Channels=[]
for ch in P.Muscle(name=str(cellname)).channel():
Channels.append(Channel(name=ch.name()))
serializer = ChannelSerializer(Channels, many=True)
print serializer.data
return Response(serializer.data)
def Neurons(request):
P.connect()
try:
NEURON_DICT = {}
for neuron in P.Neuron().load():
NEURON_DICT[str(neuron)] = {
'name': str(neuron),
'completeness': '#2B7558'
}
finally:
P.disconnect()
return render_to_response('pyopenworm/neurons.html',
{'neurons': NEURON_DICT})
def add_data_to_neuron(data_kind, relation_code):
cur.execute("""
SELECT DISTINCT a.Entity, b.Entity
FROM
tblrelationship q,
tblrelationship r,
tblentity a,
tblentity b
where q.EnID1=a.id and q.Relation = '1515' and q.EnID2='1'
and r.EnID1=a.id and r.Relation = '{}' and r.EnID2=b.id
""".format(relation_code))
for r in cur.fetchall():
name = str(r[0])
data = str(r[1])
if not (name in neurons):
neurons[name] = P.Neuron(name=name)
getattr(neurons[name], data_kind)(data)
def marshall(name):
ret = []
res = None
res2 = None
if name in neurons:
res = P.Neuron(name)
elif name in muscles:
res = P.Muscle(name)
elif name in to_expand_muscles:
res, res2 = expand_muscle(name)
elif name in other_cells:
res = P.Cell(name)
if res is not None:
ret.append(res)
if res2 is not None:
ret.append(res2)
return ret
def Neuron(request, neuron_id):
P.connect()
try:
neuron_dict = {}
for neuron in P.Neuron(neuron_id).load():
neuron_dict[str(neuron)] = {
'name': str(neuron),
'type': list(neuron.type.get()),
'receptor': list(neuron.receptor.get()),
'innexin': list(neuron.innexin.get()),
'neurotransmitter': list(neuron.neurotransmitter.get()),
'neuropeptide': list(neuron.neuropeptide.get()),
'completeness': '#2B7558'
}
finally:
P.disconnect()
return render_to_response('pyopenworm/neuron.html',
{'neuron': neuron_dict[neuron_id]})
def test_verify_neurons_have_evidence(self):
""" For each neuron in PyOpenWorm, verify
that there is supporting evidence"""
neurons = list(P.Neuron().load())
evcheck = []
for n in neurons:
hasEvidence = len(get_supporting_evidence(n)) + len(
get_supporting_evidence(n.neurotransmitter)) + len(
get_supporting_evidence(n.type)) + len(
get_supporting_evidence(n.innexin)) + len(
get_supporting_evidence(n.neuropeptide)) + len(
get_supporting_evidence(n.receptor))
print get_supporting_evidence(n.neurotransmitter)
evcheck.append(hasEvidence)
self.assertTrue(0 not in evcheck,
"There appears to be no evidence: " + str(evcheck))
def get(self,request, format=None):
neurons=[]
muscles=[]
for neuron in P.Neuron().load():
neurons.append(str(neuron.name()))
for muscle in P.Muscle().load():
muscles.append(str(muscle.name()))
cellname = self.request.query_params.get('cellname', None)
if cellname==None:
Channels=[]
else:
if cellname in neurons:
net = P.Worm().get_neuron_network()
neuron = net.aneuron(cellname)
serializer = NeuronDetailSerializer(NeuronDetail(neuron))
elif cellname in muscles:
muscle = P.Muscle(cellname)
serializer = MuscleDetailSerializer(MuscleDetail(muscle))
print serializer.data
return Response(serializer.data)
def aneuron(self, name):
"""
Get a neuron by name.
Example::
# Grabs the representation of the neuronal network
>>> net = P.Worm().get_neuron_network()
# Grab a specific neuron
>>> aval = net.aneuron('AVAL')
>>> aval.type()
set([u'interneuron'])
:param name: Name of a c. elegans neuron
:returns: Neuron corresponding to the name given
:rtype: PyOpenWorm.Neuron
"""
n = P.Neuron(name=name,conf=self.conf)
return n
def test_neuron_Syn_degree(self):
""" Get the number of chemical synapses from a networkx representation """
# was 187 -- now returning 105 -- are we sure this is correct?
self.assertEqual(PyOpenWorm.Neuron(name='AVAL').Syn_degree(), 105)
def test_neuron_get_reference(self):
self.assertEquals(
PyOpenWorm.Neuron('ADER').get_reference(0, 'EXP-1'),
['http://dx.doi.org/10.100.123/natneuro'])
self.assertEquals(
PyOpenWorm.Neuron('ADER').get_reference(0, 'DOP-2'), None)
def test_neuron_receptors(self):
self.assertTrue('GLR-2' in PyOpenWorm.Neuron('AVAL').receptors())
self.assertTrue('OSM-9' in PyOpenWorm.Neuron('PHAL').receptors())
See: "Metadata in PyOpenWorm" for discussion on semantics of what giving
evidence for an object means.
"""
import sys
import PyOpenWorm as P
#Create dummy database configuration.
d = P.Data({})
#Connect to database with dummy configuration
P.connect(conf=d)
#Create a new Neuron object to work with
n = P.Neuron(name='AVAL')
#Create a new Evidence object with `doi` and `pmid` fields populated.
#See `PyOpenWorm/evidence.py` for other available fields.
e = P.Evidence(doi='125.41.3/ploscompbiol', pmid='57182010')
#Evidence object asserts something about the enclosed dataObject.
#Here we add a receptor to the Neuron we made earlier, and "assert it".
#As the discussion (see top) reads, this might be asserting the existence of
#receptor UNC-8 on neuron AVAL.
e.asserts(n.receptor('UNC-8'))
#Save the Neuron and Evidence objects to the database.
n.save()
e.save()
