358 lines
12 KiB
Python
358 lines
12 KiB
Python
import gtk
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from fluents import dataset, logger, plots, workflow, fluents
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import geneontology
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#import gostat
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from scipy import array, randn, log, ones, zeros
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import networkx
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import re
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EVIDENCE_CODES=[('IMP', 'Inferred from mutant phenotype'),
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('IGI', 'Inferred from genetic interaction'),
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('IPI', 'Inferred from physical interaction'),
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('ISS', 'Inferred from sequence or structure similarity'),
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('IDA', 'Inferred from direct assay'),
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('IEP', 'Inferred on expression pattern'),
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('IEA', 'Inferred from electronic annotation'),
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('TAS', 'Traceable author statement'),
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('NAS', 'Non-traceable author statement'),
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('ND', 'No biological data available'),
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('RCA', 'Inferred from reviewed computational analysis'),
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('IC', 'Inferred by curator')]
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DISTANCE_METRICS = [('resnik', 'Resnik'),
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('jiang', 'Jiang & Conrath'),
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('fussimeg', 'FuSSiMeG')]
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GO_DATA_DIR = '/home/einarr/data'
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evidence = None
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go = None
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class GoTermView (gtk.Frame):
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def __init__(self):
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gtk.Frame.__init__(self)
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tab = gtk.Table(2, 2, False)
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self._table = tab
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self._name = gtk.Label('')
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self._name.set_line_wrap(True)
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self._name.set_alignment(0, 0)
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name_label = gtk.Label('Name:')
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name_label.set_alignment(0, 0)
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tab.attach(name_label, 0, 1, 0, 1, gtk.FILL, gtk.FILL, 5, 5)
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tab.attach(self._name, 1, 2, 0, 1, gtk.FILL|gtk.EXPAND, gtk.FILL, 5, 5)
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self._def = gtk.TextBuffer()
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textview = gtk.TextView(self._def)
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textview.set_wrap_mode(gtk.WRAP_WORD)
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scrolled_window = gtk.ScrolledWindow()
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scrolled_window.add(textview)
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def_label = gtk.Label('Def:')
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def_label.set_alignment(0.0, 0.0)
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tab.attach(def_label, 0, 1, 1, 2, gtk.FILL, gtk.FILL, 5, 5)
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tab.attach(scrolled_window, 1, 2, 1, 2, gtk.FILL|gtk.EXPAND, gtk.FILL|gtk.EXPAND, 5, 5)
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self.add(tab)
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self.set_go_term(None)
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def set_go_term(self, term):
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if term:
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self.set_label(term['id'])
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self._name.set_text(term['name'])
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self._def.set_text(term['def'])
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else:
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self.set_label('GO Term')
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self._name.set_text('')
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self._def.set_text('')
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class GeneOntologyTree (gtk.HPaned):
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def __init__(self, network):
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gtk.HPaned.__init__(self)
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treemodel = geneontology.get_go_treestore(network)
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self._treemodel = treemodel
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self._tree_view = gtk.TreeView(treemodel)
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renderer = gtk.CellRendererText()
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go_column = gtk.TreeViewColumn('GO ID', renderer, text=0)
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self._tree_view.insert_column(go_column, 0)
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renderer = gtk.CellRendererText()
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go_column = gtk.TreeViewColumn('Name', renderer, text=1)
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self._tree_view.insert_column(go_column, 1)
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self._desc_view = GoTermView()
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self._tree_view.connect('cursor-changed', self._on_cursor_changed)
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scrolled_window = gtk.ScrolledWindow()
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scrolled_window.add(self._tree_view)
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self.add1(scrolled_window)
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self.add2(self._desc_view)
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self.show_all()
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def _on_cursor_changed(self, tree):
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path, col = self._tree_view.get_cursor()
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current = self._treemodel.get_iter(path)
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term = self._treemodel.get_value(current, 2)
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self._desc_view.set_go_term(term)
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class GoWorkflow (workflow.Workflow):
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name = 'Gene Ontology'
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ident = 'go'
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description = 'Gene Ontology Workflow. For tree distance measures based '\
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+ 'on the GO tree.'
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def __init__(self, app):
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workflow.Workflow.__init__(self, app)
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load = workflow.Stage('load', 'Load GO Annotations')
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load.add_function(LoadGOFunction())
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load.add_function(LoadAnnotationsFunction())
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load.add_function(LoadTextDatasetFunction())
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self.add_stage(load)
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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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self.add_stage(go)
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class LoadGOFunction(workflow.Function):
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def __init__(self):
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workflow.Function.__init__(self, 'load-go', 'Load Gene Ontology')
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def run(self):
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global go
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go = geneontology.read_default_go()
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browser = GeneOntologyTree(go)
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label = gtk.Label('_Gene Ontology')
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label.set_use_underline(True)
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fluents.app['bottom_notebook'].append_page(browser, label)
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class LoadTextDatasetFunction(workflow.Function):
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def __init__(self):
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workflow.Function.__init__(self, 'load-text-ds', 'Load GO Evidence')
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def run(self):
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f = open('/home/einarr/data/goa-condensed.ftsv')
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global evidence
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evidence = dataset.read_ftsv(f)
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return [evidence]
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class LoadAnnotationsFunction(workflow.Function):
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def __init__(self):
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workflow.Function.__init__(self, 'load-go-ann', 'Load Annotations')
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self.annotations = None
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def run(self):
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global evidence
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f = open(GO_DATA_DIR + '/goa-condensed')
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ev_codes = f.readline().split()
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go_terms = []
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lines = f.readlines()
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m = zeros((len(lines), len(ev_codes)))
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for i, l in enumerate(lines):
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values = l.split()
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go_terms.append(values[0])
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for j, v in enumerate(values[1:]):
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m[i,j] = float(v.strip())
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d = dataset.Dataset(m,
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[['go-terms', go_terms], ['evidence', ev_codes]],
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name='GO evidence')
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evidence = d
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return [d]
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class EvidenceCodeFrame(gtk.Frame):
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def __init__(self):
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gtk.Frame.__init__(self, 'Evidence Codes')
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self._ec_buttons = {}
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vbox = gtk.VBox(len(EVIDENCE_CODES))
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for code, desc in EVIDENCE_CODES:
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btn = gtk.CheckButton('%s (%s)' % (code, desc))
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self._ec_buttons[code] = btn
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vbox.add(btn)
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self.add(vbox)
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def set_options(self, options):
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for code, desc in EVIDENCE_CODES:
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self._ec_buttons[code].set_active(options[code])
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def update_options(self, options):
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for code, desc in EVIDENCE_CODES:
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options[code] = self._ec_buttons[code].get_active()
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return options
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class DistanceMetricFrame(gtk.Frame):
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def __init__(self):
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gtk.Frame.__init__(self, 'Distance Metrics')
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self._metric_buttons = {}
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vbox = gtk.VBox()
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prev = None
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for code, text in DISTANCE_METRICS:
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btn = gtk.RadioButton(prev, '%s' % text)
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self._metric_buttons[code] = btn
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vbox.add(btn)
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prev = btn
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self.add(vbox)
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def set_options(self, options):
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self._metric_buttons[options['metric']].set_active(True)
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def update_options(self, options):
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for code, text in DISTANCE_METRICS:
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if self._metric_buttons[code].get_active():
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options['metric'] = code
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return options
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return options
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class GoDistanceDialog(gtk.Dialog):
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def __init__(self):
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gtk.Dialog.__init__(self, 'GO term distance matrix',
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None,
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gtk.DIALOG_MODAL | gtk.DIALOG_DESTROY_WITH_PARENT,
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(gtk.STOCK_OK, gtk.RESPONSE_OK,
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gtk.STOCK_CANCEL, gtk.RESPONSE_CANCEL))
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self._ec_frame = EvidenceCodeFrame()
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self._metric_frame = DistanceMetricFrame()
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self.vbox.add(self._ec_frame)
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self.vbox.add(self._metric_frame)
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def run(self):
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self.vbox.show_all()
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return gtk.Dialog.run(self)
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def set_options(self, options):
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self._ec_frame.set_options(options)
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self._metric_frame.set_options(options)
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def update_options(self, options):
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self._ec_frame.update_options(options)
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self._metric_frame.update_options(options)
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return options
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def set_editable(self, editable):
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self._ec_frame.set_sensitive(editable)
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self._metric_frame.set_sensitive(editable)
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class NumericDict(dict):
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def __init__(self):
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dict.__init__(self)
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def __getitem__(self, key):
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retval = 0
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try:
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retval = dict.__getitem__(self, key)
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except:
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retval = 0.0
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return retval
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class SelectGoTermsFunction(workflow.Function):
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def __init__(self, wf):
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workflow.Function.__init__(self, 'go-select', 'Select GO Terms')
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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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class GoDistanceFunction(workflow.Function):
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def __init__(self):
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workflow.Function.__init__(self, 'go-dist', 'GO term distance matrix')
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self.options = GoDistanceOptions()
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def resnik_distance_matrix(self, selection, ic):
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size = len(selection['go-terms'])
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m = zeros((size, size))
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# Create resnik distance matrix
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ids = list(selection['go-terms'])
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for i, t1 in enumerate(ids):
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for j, t2 in enumerate(ids):
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term1 = go.by_id[t1]
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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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ds = dataset.Dataset(m, (('go-terms', ids), ('_go-terms', ids)), 'Resnik')
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return ds
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def run(self, x, selection):
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global evidence, go
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self.options = self.show_gui(self.options)
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if not selection.has_key('go-terms') or len(selection['go-terms']) == 0:
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logger.log('warning', 'No GO terms selected. Cannot make distance matrix.')
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codes = [c for c, d in EVIDENCE_CODES if self.options[c]]
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ev_indices = evidence.get_indices('evidence', codes)
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ann_count_matrix = evidence._array[:, ev_indices].sum(1)
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total_ann = ann_count_matrix.sum(0)
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annotations = NumericDict()
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ic = NumericDict()
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# Insert annotations into dict
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for i, v in enumerate(evidence.get_identifiers('go-terms')):
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annotations[v] = ann_count_matrix[i]
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# Accumulate annotations
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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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return [self.resnik_distance_matrix(selection, ic)]
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def show_gui(self, options, edit=True):
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dialog = GoDistanceDialog()
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dialog.set_options(self.options)
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dialog.show_all()
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dialog.set_editable(edit)
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response = dialog.run()
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dialog.hide()
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if response == gtk.RESPONSE_OK:
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return dialog.update_options(self.options)
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else:
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return options
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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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class GoDistanceOptions(Options):
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def __init__(self):
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Options.__init__(self)
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for code, desc in EVIDENCE_CODES:
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self[code] = True
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self['metric'] = 'fussimeg'
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