class FBAModel(StoredObject):
"""
A class representing an FBA Model in the stored environment
Parent Classes: StoredObject -> FBAModel
"""
storedType = service.types()['FBAModel']
DEFAULT_BIOCHEM = Biochemistry(6, 489)
def get_reactions(self):
"""
Returns a list of ModelReaction objects representing this model's reactions
"""
model_obj = self.get_object()
return [ModelReaction(r) for r in model_obj['modelreactions']
] # Potentially Wasteful but maintains D.R.Y.
def get_features(self):
"""
returns a set<str> of all gene features in the model
:return: set<str> features
"""
rxns = self.get_reactions()
features = set()
for r in rxns:
features |= r.gpr.ftrs
return features
class ReactionProbabilities(StoredObject):
"""
a class representing a ReactionProbabilities in the stored environment
"""
storedType = service.types()['ReactionProbabilities']
def __init__(self, object_id, workspace_id):
super(ReactionProbabilities, self).__init__(object_id, workspace_id)
self._prob_hash = None
def probability_hash(self):
"""
:return: a dictionary of the reactions in this object to their probabilities
"""
if self._prob_hash is not None:
return self._prob_hash
prob_hash = dict()
for rxn in self.data['reaction_probabilities']:
prob_hash[rxn[0]] = rxn[1]
self._prob_hash = prob_hash
return prob_hash
def get_likelihood(self, reaction_id):
"""
returns the likelihood a reaction is represented in the genome, raises ValueError if not found
:param reaction_id:
:return:
"""
try:
return self.probability_hash()[reaction_id]
except KeyError:
return -1
class Media(StoredObject):
"""
a class representing a media in the stored environment
"""
storedType = service.types()['Media']
def fba_formulation(self, arguments=None):
"""
Generates an FBA formulation used to create an FBA object.
:param arguments: (optional) additional arguments to FBA formulation
:return: dictionary of arguments to FBA (fba_formulation)
"""
return service.fba_formulation(self)
class ProteomeComparison(StoredObject):
"""
a class representing a Porteome Comparison in the stored environment
"""
storedType = service.types()['ProteomeComparison']
def get_genomes(self):
"""
returns the genomes of the compared genomes
:return: tuple (Genome, Genome)
"""
g1ws, g1obj, _version = self.data['genome1ref'].split('/')
g12ws, g2obj, _version = self.data['genome2ref'].split('/')
return Genome(g1obj, g1ws), Genome(g2obj, g12ws)
def find_matches(self, gene, genome=None):
"""
Finds the matches for a particular gene in the proteome comparison. The genome can be inferred or set manually
:param gene: gene to look for matches
:param genome: (optional) the genome the gene is located in
:return: list of tuples(string, int) (gene, %hit) that were found as matches, often a singleton list
"""
# Set genome to index of the genome in the comparison (have to because of ugly KBase ProtComp Data Structure0
if genome is not None:
genomes = [g.get_genome_id() for g in self.get_genomes()]
if genome.get_genome_id() not in genomes:
raise ValueError('gene: ' + str(gene) + ' not in genomes: ' +
str(genomes))
genome = genomes.index(genome.get_genome_id())
else:
genomes = [g.get_genome_id() for g in self.get_genomes()]
for i in range(len(genomes)):
if gene.startswith(genomes[i]):
genome = i
if genome is None:
raise ValueError('gene: ' + str(gene) + ' not in genomes: ' +
str(genomes))
# Find map index in proteome comp data structure for gene
map_key = 'proteome' + str(genome + 1) + 'map'
match_name_key = 'proteome1names' if map_key == 'proteome2map' else 'proteome2names'
data_key = 'data' + str(genome + 1)
names_map = self.data[map_key]
matches = self.data[data_key][names_map[gene]]
result = []
for m in matches:
result.append((self.data[match_name_key][m[0]], m[2]))
return result
def get_genome_names(self):
return [g.get_genome_name() for g in self.get_genomes()]
class Biochemistry(StoredObject):
"""
a class representing a Biochemistry Object
"""
storedType = service.types()['Biochemistry']
def get_compound(self, compound_id):
"""
returns dictionary of information on a compound
:param compound_id: str e.g. 'cpd00011'
:return:
"""
for c in self.data['compounds']:
if compound_id == c['id']:
return c
raise ValueError(str(compound_id) + ' is not in the biochemistry')
class Genome(StoredObject):
"""
a class representing a genome in the stored environment
"""
storedType = service.types()['Genome']
def get_genome_id(self):
return self.data['id']
def get_genome_name(self):
return self.data['scientific_name']
def get_features(self):
return self.data['features']
def alias_map(self, key_str, val_str=None):
"""
returns a dictionary of aliases id types for this genome (a key and value reference same gene)
:param key_str: A key indicating what kind of alias to use as keys (the standard prefix ('MMP', 'kb|g.575')
:param val_str: (optional) str indicating what kind of alias to map to (default is ID (e.g. kb|g.575)
:return: dictionary of alias mappings
"""
result = dict()
for f in self.get_features():
if 'aliases' in f:
for alias in f['aliases']:
if alias.startswith(key_str):
if val_str is not None:
values = [
a for a in f['aliases']
if a.startswith(val_str)
]
assert len(values) <= 1
if len(values) > 0:
result[alias] = values[0]
else:
result[alias] = f['id']
for key in result:
val = result[key]
for f in self.get_features():
if 'aliases' in f and val in f['aliases']:
assert f['id'] == key, 'Not a 1:1 mapping ' + str(
key) + ', ' + str(val)
return result
return result
class FBA(StoredObject):
"""
a class representing an FBA result in the stored environment
"""
storedType = service.types()['FBA']
def __init__(self, object_id, workspace_id):
super(FBA, self).__init__(object_id, workspace_id)
self.objective = self.get_objective()
def get_objective(self):
"""
returns the objective value from the FBA Run
:return:
"""
return self.data['objectiveValue']
def get_model(self):
"""
returns the FBAModel associated with this FBA
:return: FBAModel
"""
info = self.data['fbamodel_ref'].split('/')
return FBAModel(info[1], info[0])
def get_media(self):
"""
returns the Media associated with this FBA
:return: Media
"""
info = self.data['media_ref'].split('/')
return Media(info[1], info[0])
def blocked_reactions(self):
"""
returns a list of rxn_ids of reactions that were incapable of carrying flux in FBA
WARNING: MAKE SURE THIS LINKS TO AN FBA OBJECT WHERE FVA WAS RUN OR ERRONEROUS RESULTS WILL BE FOUND
:return:
"""
result = list()
for r in self.data['FBAReactionVariables']:
if r['max'] == 0 and r['min'] == 0:
assert r['class'] == 'Blocked'
result.append(r['modelreaction_ref'].split('/')[-1])
return result
def primary_exchanges(self):
"""
Returns the 10
:return:
"""
biochem = FBAModel.DEFAULT_BIOCHEM
flux = [[f['value'], f['modelcompound_ref'].split('/')[-1]]
for f in self.data['FBACompoundVariables']]
for f in flux:
try:
c = biochem.get_compound(f[1].split('_')[0])
f[1] = c['name'] + '(' + c['formula'] + ')'
except ValueError:
pass
flux.sort()
return flux[0:10], flux[-10:]