Create Resnik distances and save them as ftsv.
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@ -32,6 +32,7 @@ class GeneOntology(networkx.XDiGraph):
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def __init__(self):
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networkx.XDiGraph.__init__(self)
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self.by_id = {}
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self.undirected = None
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def add_term(self, term):
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self.add_node(term)
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@ -62,12 +63,12 @@ class GeneOntology(networkx.XDiGraph):
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def subsumer(self, t1, t2):
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if t1 == t2:
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# print "t1 == t2"
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return t1
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go_undir = self.to_undirected()
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# print go_undir.nodes()
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path = networkx.shortest_path(go_undir, t1, t2)
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if self.undirected == None:
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self.undirected = self.to_undirected()
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path = networkx.shortest_path(self.undirected, t1, t2)
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if not path:
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print "Woah, path not found."
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return None
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@ -76,12 +77,9 @@ class GeneOntology(networkx.XDiGraph):
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print "This shouldn't happen"
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return t1
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# print t1['id'], t2['id'], path
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# print "path:", path
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for t in path:
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if networkx.shortest_path(self, t, t1) and \
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networkx.shortest_path(self, t, t2):
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# print " ", t1, t2, t
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return t
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print "GeneOntology.subsumer: should not reach this point"
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@ -120,6 +120,7 @@ class GoWorkflow (workflow.Workflow):
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go = workflow.Stage('go', 'Gene Ontology')
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go.add_function(SelectGoTermsFunction(self))
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go.add_function(GoDistanceFunction())
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go.add_function(SaveDistancesFunction())
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self.add_stage(go)
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@ -277,7 +278,7 @@ class SelectGoTermsFunction(workflow.Function):
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self.wf = wf
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def run(self):
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self.wf.project.set_selection('go-terms', set(['GO:0007582', 'GO:0008150', 'GO:0051704']))
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self.wf.project.set_selection('go-terms', set(['GO:0007582', 'GO:0008150', 'GO:0051704', 'GO:0044419']))
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class GoDistanceFunction(workflow.Function):
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@ -296,7 +297,7 @@ class GoDistanceFunction(workflow.Function):
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term2 = go.by_id[t2]
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subsumer = go.subsumer(term1, term2)
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print "%s - %s - %s" % (t1, subsumer['id'], t2)
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m[i, j] = ic[subsumer['id']] - ic[t1] + ic[subsumer['id']] - ic[t2]
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m[i, j] = ic[t1] + ic[t2] - 2.0 * ic[subsumer['id']]
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ds = dataset.Dataset(m, (('go-terms', ids), ('_go-terms', ids)), 'Resnik')
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return ds
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@ -322,11 +323,10 @@ class GoDistanceFunction(workflow.Function):
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for term in reversed(networkx.topological_sort(go)):
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for parent in go.in_neighbors(term):
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annotations[parent['id']] += annotations[term['id']]
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# print "%s -> %s (%s)" % (term['id'], parent['id'], annotations[parent['id']])
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# Create information content dictionary
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for i, v in enumerate(evidence.get_identifiers('go-terms')):
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ic[v] = -log(ann_count_matrix[i] / total_ann)
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for term, count in annotations.items():
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ic[term] = -log(count / total_ann)
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return [self.resnik_distance_matrix(selection, ic)]
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@ -343,6 +343,17 @@ class GoDistanceFunction(workflow.Function):
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return options
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class SaveDistancesFunction(workflow.Function):
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def __init__(self):
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workflow.Function.__init__(self, 'save-matrix', 'Save Matrix')
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def run(self, ds):
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filename = '/home/einarr/data/output.ftsv'
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fd = open(filename, 'w')
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dataset.write_ftsv(fd, ds)
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fd.close()
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class Options(dict):
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def __init__(self):
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dict.__init__(self)
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