class OWGOEnrichmentAnalysis(widget.OWWidget):
name = "GO Browser"
description = "Enrichment analysis for Gene Ontology terms."
icon = "../widgets/icons/GOBrowser.svg"
priority = 2020
inputs = [("Cluster Data", Orange.data.Table, "setDataset",
widget.Single + widget.Default),
("Reference Data", Orange.data.Table, "setReferenceDataset")]
outputs = [("Data on Selected Genes", Orange.data.Table),
("Data on Unselected Genes", Orange.data.Table),
("Data on Unknown Genes", Orange.data.Table),
("Enrichment Report", Orange.data.Table)]
settingsHandler = settings.DomainContextHandler()
annotationIndex = settings.ContextSetting(0)
geneAttrIndex = settings.ContextSetting(0)
useAttrNames = settings.ContextSetting(False)
geneMatcherSettings = settings.Setting([True, False, False, False])
useReferenceDataset = settings.Setting(False)
aspectIndex = settings.Setting(0)
useEvidenceType = settings.Setting(
{et: True
for et in go.evidenceTypesOrdered})
filterByNumOfInstances = settings.Setting(False)
minNumOfInstances = settings.Setting(1)
filterByPValue = settings.Setting(True)
maxPValue = settings.Setting(0.2)
filterByPValue_nofdr = settings.Setting(False)
maxPValue_nofdr = settings.Setting(0.01)
probFunc = settings.Setting(0)
selectionDirectAnnotation = settings.Setting(0)
selectionDisjoint = settings.Setting(0)
selectionAddTermAsClass = settings.Setting(0)
Ready, Initializing, Running = 0, 1, 2
def __init__(self, parent=None):
super().__init__(self, parent)
self.clusterDataset = None
self.referenceDataset = None
self.ontology = None
self.annotations = None
self.loadedAnnotationCode = "---"
self.treeStructRootKey = None
self.probFunctions = [stats.Binomial(), stats.Hypergeometric()]
self.selectedTerms = []
self.selectionChanging = 0
self.__state = OWGOEnrichmentAnalysis.Initializing
self.annotationCodes = []
#############
## GUI
#############
self.tabs = gui.tabWidget(self.controlArea)
## Input tab
self.inputTab = gui.createTabPage(self.tabs, "Input")
box = gui.widgetBox(self.inputTab, "Info")
self.infoLabel = gui.widgetLabel(box, "No data on input\n")
gui.button(
box,
self,
"Ontology/Annotation Info",
callback=self.ShowInfo,
tooltip="Show information on loaded ontology and annotations")
box = gui.widgetBox(self.inputTab, "Organism")
self.annotationComboBox = gui.comboBox(box,
self,
"annotationIndex",
items=self.annotationCodes,
callback=self._updateEnrichment,
tooltip="Select organism")
genebox = gui.widgetBox(self.inputTab, "Gene Names")
self.geneAttrIndexCombo = gui.comboBox(
genebox,
self,
"geneAttrIndex",
callback=self._updateEnrichment,
tooltip="Use this attribute to extract gene names from input data")
self.geneAttrIndexCombo.setDisabled(self.useAttrNames)
cb = gui.checkBox(genebox,
self,
"useAttrNames",
"Use column names",
tooltip="Use column names for gene names",
callback=self._updateEnrichment)
cb.toggled[bool].connect(self.geneAttrIndexCombo.setDisabled)
gui.button(genebox,
self,
"Gene matcher settings",
callback=self.UpdateGeneMatcher,
tooltip="Open gene matching settings dialog")
self.referenceRadioBox = gui.radioButtonsInBox(
self.inputTab,
self,
"useReferenceDataset", ["Entire genome", "Reference set (input)"],
tooltips=[
"Use entire genome for reference",
"Use genes from Referece Examples input signal as reference"
],
box="Reference",
callback=self._updateEnrichment)
self.referenceRadioBox.buttons[1].setDisabled(True)
gui.radioButtonsInBox(
self.inputTab,
self,
"aspectIndex",
["Biological process", "Cellular component", "Molecular function"],
box="Aspect",
callback=self._updateEnrichment)
## Filter tab
self.filterTab = gui.createTabPage(self.tabs, "Filter")
box = gui.widgetBox(self.filterTab, "Filter GO Term Nodes")
gui.checkBox(
box,
self,
"filterByNumOfInstances",
"Genes",
callback=self.FilterAndDisplayGraph,
tooltip="Filter by number of input genes mapped to a term")
ibox = gui.indentedBox(box)
gui.spin(ibox,
self,
'minNumOfInstances',
1,
100,
step=1,
label='#:',
labelWidth=15,
callback=self.FilterAndDisplayGraph,
callbackOnReturn=True,
tooltip="Min. number of input genes mapped to a term")
gui.checkBox(box,
self,
"filterByPValue_nofdr",
"p-value",
callback=self.FilterAndDisplayGraph,
tooltip="Filter by term p-value")
gui.doubleSpin(gui.indentedBox(box),
self,
'maxPValue_nofdr',
1e-8,
1,
step=1e-8,
label='p:',
labelWidth=15,
callback=self.FilterAndDisplayGraph,
callbackOnReturn=True,
tooltip="Max term p-value")
#use filterByPValue for FDR, as it was the default in prior versions
gui.checkBox(box,
self,
"filterByPValue",
"FDR",
callback=self.FilterAndDisplayGraph,
tooltip="Filter by term FDR")
gui.doubleSpin(gui.indentedBox(box),
self,
'maxPValue',
1e-8,
1,
step=1e-8,
label='p:',
labelWidth=15,
callback=self.FilterAndDisplayGraph,
callbackOnReturn=True,
tooltip="Max term p-value")
box = gui.widgetBox(box, "Significance test")
gui.radioButtonsInBox(box,
self,
"probFunc", ["Binomial", "Hypergeometric"],
tooltips=[
"Use binomial distribution test",
"Use hypergeometric distribution test"
],
callback=self._updateEnrichment)
box = gui.widgetBox(self.filterTab,
"Evidence codes in annotation",
addSpace=True)
self.evidenceCheckBoxDict = {}
for etype in go.evidenceTypesOrdered:
ecb = QCheckBox(etype,
toolTip=go.evidenceTypes[etype],
checked=self.useEvidenceType[etype])
ecb.toggled.connect(self.__on_evidenceChanged)
box.layout().addWidget(ecb)
self.evidenceCheckBoxDict[etype] = ecb
## Select tab
self.selectTab = gui.createTabPage(self.tabs, "Select")
box = gui.radioButtonsInBox(self.selectTab,
self,
"selectionDirectAnnotation",
["Directly or Indirectly", "Directly"],
box="Annotated genes",
callback=self.ExampleSelection)
box = gui.widgetBox(self.selectTab, "Output", addSpace=True)
gui.radioButtonsInBox(
box,
self,
"selectionDisjoint",
btnLabels=[
"All selected genes", "Term-specific genes",
"Common term genes"
],
tooltips=[
"Outputs genes annotated to all selected GO terms",
"Outputs genes that appear in only one of selected GO terms",
"Outputs genes common to all selected GO terms"
],
callback=[self.ExampleSelection, self.UpdateAddClassButton])
self.addClassCB = gui.checkBox(box,
self,
"selectionAddTermAsClass",
"Add GO Term as class",
callback=self.ExampleSelection)
# ListView for DAG, and table for significant GOIDs
self.DAGcolumns = [
'GO term', 'Cluster', 'Reference', 'p-value', 'FDR', 'Genes',
'Enrichment'
]
self.splitter = QSplitter(Qt.Vertical, self.mainArea)
self.mainArea.layout().addWidget(self.splitter)
# list view
self.listView = GOTreeWidget(self.splitter)
self.listView.setSelectionMode(QTreeView.ExtendedSelection)
self.listView.setAllColumnsShowFocus(1)
self.listView.setColumnCount(len(self.DAGcolumns))
self.listView.setHeaderLabels(self.DAGcolumns)
self.listView.header().setSectionsClickable(True)
self.listView.header().setSortIndicatorShown(True)
self.listView.setSortingEnabled(True)
self.listView.setItemDelegateForColumn(
6, EnrichmentColumnItemDelegate(self))
self.listView.setRootIsDecorated(True)
self.listView.itemSelectionChanged.connect(self.ViewSelectionChanged)
# table of significant GO terms
self.sigTerms = QTreeWidget(self.splitter)
self.sigTerms.setColumnCount(len(self.DAGcolumns))
self.sigTerms.setHeaderLabels(self.DAGcolumns)
self.sigTerms.setSortingEnabled(True)
self.sigTerms.setSelectionMode(QTreeView.ExtendedSelection)
self.sigTerms.setItemDelegateForColumn(
6, EnrichmentColumnItemDelegate(self))
self.sigTerms.itemSelectionChanged.connect(self.TableSelectionChanged)
self.sigTableTermsSorted = []
self.graph = {}
self.inputTab.layout().addStretch(1)
self.filterTab.layout().addStretch(1)
self.selectTab.layout().addStretch(1)
self.setBlocking(True)
self._executor = ThreadExecutor()
self._init = EnsureDownloaded([(taxonomy.Taxonomy.DOMAIN,
taxonomy.Taxonomy.FILENAME),
("GO", "taxonomy.pickle")])
self._init.finished.connect(self.__initialize_finish)
self._executor.submit(self._init)
def sizeHint(self):
return QSize(1000, 700)
def __initialize_finish(self):
self.setBlocking(False)
try:
self.annotationFiles = listAvailable()
except ConnectTimeout:
self.error(2, "Internet connection error, unable to load data. " + \
"Check connection and create a new GO Browser widget.")
self.filterTab.setEnabled(False)
self.inputTab.setEnabled(False)
self.selectTab.setEnabled(False)
self.listView.setEnabled(False)
self.sigTerms.setEnabled(False)
else:
self.annotationCodes = sorted(self.annotationFiles.keys())
self.annotationComboBox.clear()
self.annotationComboBox.addItems(self.annotationCodes)
self.annotationComboBox.setCurrentIndex(self.annotationIndex)
self.__state = OWGOEnrichmentAnalysis.Ready
def __on_evidenceChanged(self):
for etype, cb in self.evidenceCheckBoxDict.items():
self.useEvidenceType[etype] = cb.isChecked()
self._updateEnrichment()
def UpdateGeneMatcher(self):
"""Open the Gene matcher settings dialog."""
dialog = GeneMatcherDialog(self,
defaults=self.geneMatcherSettings,
modal=True)
if dialog.exec_() != QDialog.Rejected:
self.geneMatcherSettings = [
getattr(dialog, item[0]) for item in dialog.items
]
if self.annotations:
self.SetGeneMatcher()
self._updateEnrichment()
def clear(self):
self.infoLabel.setText("No data on input\n")
self.warning(0)
self.warning(1)
self.geneAttrIndexCombo.clear()
self.ClearGraph()
self.send("Data on Selected Genes", None)
self.send("Data on Unselected Genes", None)
self.send("Data on Unknown Genes", None)
self.send("Enrichment Report", None)
def setDataset(self, data=None):
if self.__state == OWGOEnrichmentAnalysis.Initializing:
self.__initialize_finish()
self.closeContext()
self.clear()
self.clusterDataset = data
if data is not None:
domain = data.domain
allvars = domain.variables + domain.metas
self.candidateGeneAttrs = [var for var in allvars if isstring(var)]
self.geneAttrIndexCombo.clear()
for var in self.candidateGeneAttrs:
self.geneAttrIndexCombo.addItem(*gui.attributeItem(var))
taxid = data_hints.get_hint(data, "taxid", "")
code = None
try:
code = go.from_taxid(taxid)
except KeyError:
pass
except Exception as ex:
print(ex)
if code is not None:
filename = "gene_association.%s.tar.gz" % code
if filename in self.annotationFiles.values():
self.annotationIndex = \
[i for i, name in enumerate(self.annotationCodes) \
if self.annotationFiles[name] == filename].pop()
self.useAttrNames = data_hints.get_hint(data, "genesinrows",
self.useAttrNames)
self.openContext(data)
self.geneAttrIndex = min(self.geneAttrIndex,
len(self.candidateGeneAttrs) - 1)
if len(self.candidateGeneAttrs) == 0:
self.useAttrNames = True
self.geneAttrIndex = -1
elif self.geneAttrIndex < len(self.candidateGeneAttrs):
self.geneAttrIndex = len(self.candidateGeneAttrs) - 1
self._updateEnrichment()
def setReferenceDataset(self, data=None):
self.referenceDataset = data
self.referenceRadioBox.buttons[1].setDisabled(not bool(data))
self.referenceRadioBox.buttons[1].setText("Reference set")
if self.clusterDataset is not None and self.useReferenceDataset:
self.useReferenceDataset = 0 if not data else 1
graph = self.Enrichment()
self.SetGraph(graph)
elif self.clusterDataset:
self.__updateReferenceSetButton()
def handleNewSignals(self):
super().handleNewSignals()
def _updateEnrichment(self):
if self.clusterDataset is not None and \
self.__state == OWGOEnrichmentAnalysis.Ready:
pb = gui.ProgressBar(self, 100)
self.Load(pb=pb)
graph = self.Enrichment(pb=pb)
self.FilterUnknownGenes()
self.SetGraph(graph)
def __updateReferenceSetButton(self):
allgenes, refgenes = None, None
if self.referenceDataset:
try:
allgenes = self.genesFromTable(self.referenceDataset)
except Exception:
allgenes = []
refgenes, unknown = self.FilterAnnotatedGenes(allgenes)
self.referenceRadioBox.buttons[1].setDisabled(not bool(allgenes))
self.referenceRadioBox.buttons[1].setText("Reference set " + (
"(%i genes, %i matched)" %
(len(allgenes), len(refgenes)) if allgenes and refgenes else ""))
def genesFromTable(self, data):
if self.useAttrNames:
genes = [v.name for v in data.domain.variables]
else:
attr = self.candidateGeneAttrs[min(
self.geneAttrIndex,
len(self.candidateGeneAttrs) - 1)]
genes = [str(ex[attr]) for ex in data if not numpy.isnan(ex[attr])]
if any("," in gene for gene in genes):
self.information(
0,
"Separators detected in gene names. Assuming multiple genes per example."
)
genes = reduce(operator.iadd,
(genes.split(",") for genes in genes), [])
return genes
def FilterAnnotatedGenes(self, genes):
matchedgenes = self.annotations.get_gene_names_translator(
genes).values()
return matchedgenes, [
gene for gene in genes if gene not in matchedgenes
]
def FilterUnknownGenes(self):
if not self.useAttrNames and self.candidateGeneAttrs:
geneAttr = self.candidateGeneAttrs[min(
self.geneAttrIndex,
len(self.candidateGeneAttrs) - 1)]
indices = []
for i, ex in enumerate(self.clusterDataset):
if not any(
self.annotations.genematcher.match(n.strip())
for n in str(ex[geneAttr]).split(",")):
indices.append(i)
if indices:
data = self.clusterDataset[indices]
else:
data = None
self.send("Data on Unknown Genes", data)
else:
self.send("Data on Unknown Genes", None)
def Load(self, pb=None):
if self.__state == OWGOEnrichmentAnalysis.Ready:
go_files, tax_files = serverfiles.listfiles(
"GO"), serverfiles.listfiles("Taxonomy")
calls = []
pb, finish = (gui.ProgressBar(self, 0),
True) if pb is None else (pb, False)
count = 0
if not tax_files:
calls.append(("Taxonomy", "ncbi_taxnomy.tar.gz"))
count += 1
org = self.annotationCodes[min(self.annotationIndex,
len(self.annotationCodes) - 1)]
if org != self.loadedAnnotationCode:
count += 1
if self.annotationFiles[org] not in go_files:
calls.append(("GO", self.annotationFiles[org]))
count += 1
if "gene_ontology_edit.obo.tar.gz" not in go_files:
calls.append(("GO", "gene_ontology_edit.obo.tar.gz"))
count += 1
if not self.ontology:
count += 1
pb.iter += count * 100
for args in calls:
serverfiles.localpath_download(*args,
**dict(callback=pb.advance))
i = len(calls)
if not self.ontology:
self.ontology = go.Ontology(
progress_callback=lambda value: pb.advance())
i += 1
if org != self.loadedAnnotationCode:
self.annotations = None
gc.collect() # Force run garbage collection
code = self.annotationFiles[org].split(".")[-3]
self.annotations = go.Annotations(
code,
genematcher=gene.GMDirect(),
progress_callback=lambda value: pb.advance())
i += 1
self.loadedAnnotationCode = org
count = defaultdict(int)
geneSets = defaultdict(set)
for anno in self.annotations.annotations:
count[anno.evidence] += 1
geneSets[anno.evidence].add(anno.geneName)
for etype in go.evidenceTypesOrdered:
ecb = self.evidenceCheckBoxDict[etype]
ecb.setEnabled(bool(count[etype]))
ecb.setText(etype + ": %i annots(%i genes)" %
(count[etype], len(geneSets[etype])))
if finish:
pb.finish()
def SetGeneMatcher(self):
if self.annotations:
taxid = self.annotations.taxid
matchers = []
for matcher, use in zip(
[gene.GMGO, gene.GMKEGG, gene.GMNCBI, gene.GMAffy],
self.geneMatcherSettings):
if use:
try:
if taxid == "352472":
matchers.extend([
matcher(taxid),
gene.GMDicty(),
[matcher(taxid),
gene.GMDicty()]
])
# The reason machers are duplicated is that we want `matcher` or `GMDicty` to
# match genes by them self if possible. Only use the joint matcher if they fail.
else:
matchers.append(matcher(taxid))
except Exception as ex:
print(ex)
self.annotations.genematcher = gene.matcher(matchers)
self.annotations.genematcher.set_targets(
self.annotations.gene_names)
def Enrichment(self, pb=None):
assert self.clusterDataset is not None
pb = gui.ProgressBar(self, 100) if pb is None else pb
if not self.annotations.ontology:
self.annotations.ontology = self.ontology
if isinstance(self.annotations.genematcher, gene.GMDirect):
self.SetGeneMatcher()
self.error(1)
self.warning([0, 1])
if self.useAttrNames:
clusterGenes = [
v.name for v in self.clusterDataset.domain.attributes
]
self.information(0)
elif 0 <= self.geneAttrIndex < len(self.candidateGeneAttrs):
geneAttr = self.candidateGeneAttrs[self.geneAttrIndex]
clusterGenes = [
str(ex[geneAttr]) for ex in self.clusterDataset
if not numpy.isnan(ex[geneAttr])
]
if any("," in gene for gene in clusterGenes):
self.information(
0,
"Separators detected in cluster gene names. Assuming multiple genes per example."
)
clusterGenes = reduce(operator.iadd,
(genes.split(",")
for genes in clusterGenes), [])
else:
self.information(0)
else:
self.error(1, "Failed to extract gene names from input dataset!")
return {}
genesSetCount = len(set(clusterGenes))
self.clusterGenes = clusterGenes = self.annotations.get_gene_names_translator(
clusterGenes).values()
self.infoLabel.setText(
"%i unique genes on input\n%i (%.1f%%) genes with known annotations"
% (genesSetCount, len(clusterGenes), 100.0 * len(clusterGenes) /
genesSetCount if genesSetCount else 0.0))
referenceGenes = None
if not self.useReferenceDataset or self.referenceDataset is None:
self.information(2)
self.information(1)
referenceGenes = self.annotations.gene_names
elif self.referenceDataset is not None:
if self.useAttrNames:
referenceGenes = [
v.name for v in self.referenceDataset.domain.attributes
]
self.information(1)
elif geneAttr in (self.referenceDataset.domain.variables +
self.referenceDataset.domain.metas):
referenceGenes = [
str(ex[geneAttr]) for ex in self.referenceDataset
if not numpy.isnan(ex[geneAttr])
]
if any("," in gene for gene in clusterGenes):
self.information(
1,
"Separators detected in reference gene names. Assuming multiple genes per example."
)
referenceGenes = reduce(operator.iadd,
(genes.split(",")
for genes in referenceGenes), [])
else:
self.information(1)
else:
self.information(1)
referenceGenes = None
if referenceGenes is None:
referenceGenes = list(self.annotations.gene_names)
self.referenceRadioBox.buttons[1].setText("Reference set")
self.referenceRadioBox.buttons[1].setDisabled(True)
self.information(
2,
"Unable to extract gene names from reference dataset. Using entire genome for reference"
)
self.useReferenceDataset = 0
else:
refc = len(referenceGenes)
referenceGenes = self.annotations.get_gene_names_translator(
referenceGenes).values()
self.referenceRadioBox.buttons[1].setText(
"Reference set (%i genes, %i matched)" %
(refc, len(referenceGenes)))
self.referenceRadioBox.buttons[1].setDisabled(False)
self.information(2)
else:
self.useReferenceDataset = 0
if not referenceGenes:
self.error(1, "No valid reference set")
return {}
self.referenceGenes = referenceGenes
evidences = []
for etype in go.evidenceTypesOrdered:
if self.useEvidenceType[etype]:
evidences.append(etype)
aspect = ["P", "C", "F"][self.aspectIndex]
if clusterGenes:
self.terms = terms = self.annotations.get_enriched_terms(
clusterGenes,
referenceGenes,
evidences,
aspect=aspect,
prob=self.probFunctions[self.probFunc],
use_fdr=False,
progress_callback=lambda value: pb.advance())
ids = []
pvals = []
for i, d in self.terms.items():
ids.append(i)
pvals.append(d[1])
for i, fdr in zip(ids, stats.FDR(
pvals)): # save FDR as the last part of the tuple
terms[i] = tuple(list(terms[i]) + [fdr])
else:
self.terms = terms = {}
if not self.terms:
self.warning(0, "No enriched terms found.")
else:
self.warning(0)
pb.finish()
self.treeStructDict = {}
ids = self.terms.keys()
self.treeStructRootKey = None
parents = {}
for id in ids:
parents[id] = set([term for _, term in self.ontology[id].related])
children = {}
for term in self.terms:
children[term] = set([id for id in ids if term in parents[id]])
for term in self.terms:
self.treeStructDict[term] = TreeNode(self.terms[term],
children[term])
if not self.ontology[term].related and not getattr(
self.ontology[term], "is_obsolete", False):
self.treeStructRootKey = term
return terms
def FilterGraph(self, graph):
if self.filterByPValue_nofdr:
graph = go.filterByPValue(graph, self.maxPValue_nofdr)
if self.filterByPValue: #FDR
graph = dict(
filter(lambda item: item[1][3] <= self.maxPValue,
graph.items()))
if self.filterByNumOfInstances:
graph = dict(
filter(lambda item: len(item[1][0]) >= self.minNumOfInstances,
graph.items()))
return graph
def FilterAndDisplayGraph(self):
if self.clusterDataset:
self.graph = self.FilterGraph(self.originalGraph)
if self.originalGraph and not self.graph:
self.warning(1, "All found terms were filtered out.")
else:
self.warning(1)
self.ClearGraph()
self.DisplayGraph()
def SetGraph(self, graph=None):
self.originalGraph = graph
if graph:
self.FilterAndDisplayGraph()
else:
self.graph = {}
self.ClearGraph()
def ClearGraph(self):
self.listView.clear()
self.listViewItems = []
self.sigTerms.clear()
def DisplayGraph(self):
fromParentDict = {}
self.termListViewItemDict = {}
self.listViewItems = []
enrichment = lambda t: len(t[0]) / t[2] * (len(self.referenceGenes) /
len(self.clusterGenes))
maxFoldEnrichment = max(
[enrichment(term) for term in self.graph.values()] or [1])
def addNode(term, parent, parentDisplayNode):
if (parent, term) in fromParentDict:
return
if term in self.graph:
displayNode = GOTreeWidgetItem(self.ontology[term],
self.graph[term],
len(self.clusterGenes),
len(self.referenceGenes),
maxFoldEnrichment,
parentDisplayNode)
displayNode.goId = term
self.listViewItems.append(displayNode)
if term in self.termListViewItemDict:
self.termListViewItemDict[term].append(displayNode)
else:
self.termListViewItemDict[term] = [displayNode]
fromParentDict[(parent, term)] = True
parent = term
else:
displayNode = parentDisplayNode
for c in self.treeStructDict[term].children:
addNode(c, parent, displayNode)
if self.treeStructDict:
addNode(self.treeStructRootKey, None, self.listView)
terms = self.graph.items()
terms = sorted(terms, key=lambda item: item[1][1])
self.sigTableTermsSorted = [t[0] for t in terms]
self.sigTerms.clear()
for i, (t_id, (genes, p_value, refCount, fdr)) in enumerate(terms):
item = GOTreeWidgetItem(self.ontology[t_id],
(genes, p_value, refCount, fdr),
len(self.clusterGenes),
len(self.referenceGenes),
maxFoldEnrichment, self.sigTerms)
item.goId = t_id
self.listView.expandAll()
for i in range(5):
self.listView.resizeColumnToContents(i)
self.sigTerms.resizeColumnToContents(i)
self.sigTerms.resizeColumnToContents(6)
width = min(self.listView.columnWidth(0), 350)
self.listView.setColumnWidth(0, width)
self.sigTerms.setColumnWidth(0, width)
# Create and send the enrichemnt report table.
termsDomain = Orange.data.Domain(
[],
[],
# All is meta!
[
Orange.data.StringVariable("GO Term Id"),
Orange.data.StringVariable("GO Term Name"),
Orange.data.ContinuousVariable("Cluster Frequency"),
Orange.data.ContinuousVariable("Genes in Cluster",
number_of_decimals=0),
Orange.data.ContinuousVariable("Reference Frequency"),
Orange.data.ContinuousVariable("Genes in Reference",
number_of_decimals=0),
Orange.data.ContinuousVariable("p-value"),
Orange.data.ContinuousVariable("FDR"),
Orange.data.ContinuousVariable("Enrichment"),
Orange.data.StringVariable("Genes")
])
terms = [[t_id,
self.ontology[t_id].name,
len(genes) / len(self.clusterGenes),
len(genes),
r_count / len(self.referenceGenes),
r_count,
p_value,
fdr,
len(genes) / len(self.clusterGenes) * \
len(self.referenceGenes) / r_count,
",".join(genes)
]
for t_id, (genes, p_value, r_count, fdr) in terms]
if terms:
X = numpy.empty((len(terms), 0))
M = numpy.array(terms, dtype=object)
termsTable = Orange.data.Table.from_numpy(termsDomain, X, metas=M)
else:
termsTable = Orange.data.Table(termsDomain)
self.send("Enrichment Report", termsTable)
def ViewSelectionChanged(self):
if self.selectionChanging:
return
self.selectionChanging = 1
self.selectedTerms = []
selected = self.listView.selectedItems()
self.selectedTerms = list(set([lvi.term.id for lvi in selected]))
self.ExampleSelection()
self.selectionChanging = 0
def TableSelectionChanged(self):
if self.selectionChanging:
return
self.selectionChanging = 1
self.selectedTerms = []
selectedIds = set([
self.sigTerms.itemFromIndex(index).goId
for index in self.sigTerms.selectedIndexes()
])
for i in range(self.sigTerms.topLevelItemCount()):
item = self.sigTerms.topLevelItem(i)
selected = item.goId in selectedIds
term = item.goId
if selected:
self.selectedTerms.append(term)
for lvi in self.termListViewItemDict[term]:
try:
lvi.setSelected(selected)
if selected:
lvi.setExpanded(True)
except RuntimeError: # Underlying C/C++ object deleted
pass
self.ExampleSelection()
self.selectionChanging = 0
def UpdateAddClassButton(self):
self.addClassCB.setEnabled(self.selectionDisjoint == 1)
def ExampleSelection(self):
self.commit()
def commit(self):
if self.clusterDataset is None:
return
terms = set(self.selectedTerms)
genes = reduce(operator.ior,
(set(self.graph[term][0]) for term in terms), set())
evidences = []
for etype in go.evidenceTypesOrdered:
if self.useEvidenceType[etype]:
# if getattr(self, "useEvidence" + etype):
evidences.append(etype)
allTerms = self.annotations.get_annotated_terms(
genes,
direct_annotation_only=self.selectionDirectAnnotation,
evidence_codes=evidences)
if self.selectionDisjoint > 0:
count = defaultdict(int)
for term in self.selectedTerms:
for g in allTerms.get(term, []):
count[g] += 1
ccount = 1 if self.selectionDisjoint == 1 else len(
self.selectedTerms)
selectedGenes = [
gene for gene, c in count.items()
if c == ccount and gene in genes
]
else:
selectedGenes = reduce(operator.ior,
(set(allTerms.get(term, []))
for term in self.selectedTerms), set())
if self.useAttrNames:
vars = [
self.clusterDataset.domain[gene] for gene in set(selectedGenes)
]
domain = Orange.data.Domain(vars,
self.clusterDataset.domain.class_vars,
self.clusterDataset.domain.metas)
newdata = self.clusterDataset.from_table(domain,
self.clusterDataset)
self.send("Data on Selected Genes", newdata)
self.send("Data on Unselected Genes", None)
elif self.candidateGeneAttrs:
selectedExamples = []
unselectedExamples = []
geneAttr = self.candidateGeneAttrs[min(
self.geneAttrIndex,
len(self.candidateGeneAttrs) - 1)]
if self.selectionDisjoint == 1:
goVar = Orange.data.DiscreteVariable("GO Term",
values=list(
self.selectedTerms))
newDomain = Orange.data.Domain(
self.clusterDataset.domain.variables, goVar,
self.clusterDataset.domain.metas)
goColumn = []
for i, ex in enumerate(self.clusterDataset):
if not numpy.isnan(ex[geneAttr]) and any(
gene in selectedGenes
for gene in str(ex[geneAttr]).split(",")):
if self.selectionDisjoint == 1 and self.selectionAddTermAsClass:
terms = filter(
lambda term: any(gene in self.graph[term][0]
for gene in str(ex[geneAttr]).
split(",")), self.selectedTerms)
term = sorted(terms)[0]
goColumn.append(goVar.values.index(term))
selectedExamples.append(i)
else:
unselectedExamples.append(i)
if selectedExamples:
selectedExamples = self.clusterDataset[selectedExamples]
if self.selectionDisjoint == 1 and self.selectionAddTermAsClass:
selectedExamples = Orange.data.Table.from_table(
newDomain, selectedExamples)
view, issparse = selectedExamples.get_column_view(goVar)
assert not issparse
view[:] = goColumn
else:
selectedExamples = None
if unselectedExamples:
unselectedExamples = self.clusterDataset[unselectedExamples]
else:
unselectedExamples = None
self.send("Data on Selected Genes", selectedExamples)
self.send("Data on Unselected Genes", unselectedExamples)
def ShowInfo(self):
dialog = QDialog(self)
dialog.setModal(False)
dialog.setLayout(QVBoxLayout())
label = QLabel(dialog)
label.setText(
"Ontology:\n" +
self.ontology.header if self.ontology else "Ontology not loaded!")
dialog.layout().addWidget(label)
label = QLabel(dialog)
label.setText("Annotations:\n" +
self.annotations.header.replace("!", "") if self.
annotations else "Annotations not loaded!")
dialog.layout().addWidget(label)
dialog.show()
def onDeleteWidget(self):
"""Called before the widget is removed from the canvas.
"""
self.annotations = None
self.ontology = None
gc.collect() # Force collection
class OWGOEnrichmentAnalysis(widget.OWWidget):
name = "GO Browser"
description = "Enrichment analysis for Gene Ontology terms."
icon = "../widgets/icons/GOBrowser.svg"
priority = 2020
inputs = [("Cluster Data", Orange.data.Table,
"setDataset", widget.Single + widget.Default),
("Reference Data", Orange.data.Table,
"setReferenceDataset")]
outputs = [("Data on Selected Genes", Orange.data.Table),
("Data on Unselected Genes", Orange.data.Table),
("Data on Unknown Genes", Orange.data.Table),
("Enrichment Report", Orange.data.Table)]
settingsHandler = settings.DomainContextHandler()
annotationIndex = settings.ContextSetting(0)
geneAttrIndex = settings.ContextSetting(0)
useAttrNames = settings.ContextSetting(False)
geneMatcherSettings = settings.Setting([True, False, False, False])
useReferenceDataset = settings.Setting(False)
aspectIndex = settings.Setting(0)
useEvidenceType = settings.Setting(
{et: True for et in go.evidenceTypesOrdered})
filterByNumOfInstances = settings.Setting(False)
minNumOfInstances = settings.Setting(1)
filterByPValue = settings.Setting(True)
maxPValue = settings.Setting(0.2)
filterByPValue_nofdr = settings.Setting(False)
maxPValue_nofdr = settings.Setting(0.01)
probFunc = settings.Setting(0)
selectionDirectAnnotation = settings.Setting(0)
selectionDisjoint = settings.Setting(0)
selectionAddTermAsClass = settings.Setting(0)
Ready, Initializing, Running = 0, 1, 2
def __init__(self, parent=None):
super().__init__(self, parent)
self.clusterDataset = None
self.referenceDataset = None
self.ontology = None
self.annotations = None
self.loadedAnnotationCode = "---"
self.treeStructRootKey = None
self.probFunctions = [stats.Binomial(), stats.Hypergeometric()]
self.selectedTerms = []
self.selectionChanging = 0
self.__state = OWGOEnrichmentAnalysis.Initializing
self.annotationCodes = []
#############
## GUI
#############
self.tabs = gui.tabWidget(self.controlArea)
## Input tab
self.inputTab = gui.createTabPage(self.tabs, "Input")
box = gui.widgetBox(self.inputTab, "Info")
self.infoLabel = gui.widgetLabel(box, "No data on input\n")
gui.button(box, self, "Ontology/Annotation Info",
callback=self.ShowInfo,
tooltip="Show information on loaded ontology and annotations")
box = gui.widgetBox(self.inputTab, "Organism")
self.annotationComboBox = gui.comboBox(
box, self, "annotationIndex", items=self.annotationCodes,
callback=self._updateEnrichment, tooltip="Select organism")
genebox = gui.widgetBox(self.inputTab, "Gene Names")
self.geneAttrIndexCombo = gui.comboBox(
genebox, self, "geneAttrIndex", callback=self._updateEnrichment,
tooltip="Use this attribute to extract gene names from input data")
self.geneAttrIndexCombo.setDisabled(self.useAttrNames)
cb = gui.checkBox(genebox, self, "useAttrNames", "Use column names",
tooltip="Use column names for gene names",
callback=self._updateEnrichment)
cb.toggled[bool].connect(self.geneAttrIndexCombo.setDisabled)
gui.button(genebox, self, "Gene matcher settings",
callback=self.UpdateGeneMatcher,
tooltip="Open gene matching settings dialog")
self.referenceRadioBox = gui.radioButtonsInBox(
self.inputTab, self, "useReferenceDataset",
["Entire genome", "Reference set (input)"],
tooltips=["Use entire genome for reference",
"Use genes from Referece Examples input signal as reference"],
box="Reference", callback=self._updateEnrichment)
self.referenceRadioBox.buttons[1].setDisabled(True)
gui.radioButtonsInBox(
self.inputTab, self, "aspectIndex",
["Biological process", "Cellular component", "Molecular function"],
box="Aspect", callback=self._updateEnrichment)
## Filter tab
self.filterTab = gui.createTabPage(self.tabs, "Filter")
box = gui.widgetBox(self.filterTab, "Filter GO Term Nodes")
gui.checkBox(box, self, "filterByNumOfInstances", "Genes",
callback=self.FilterAndDisplayGraph,
tooltip="Filter by number of input genes mapped to a term")
ibox = gui.indentedBox(box)
gui.spin(ibox, self, 'minNumOfInstances', 1, 100,
step=1, label='#:', labelWidth=15,
callback=self.FilterAndDisplayGraph,
callbackOnReturn=True,
tooltip="Min. number of input genes mapped to a term")
gui.checkBox(box, self, "filterByPValue_nofdr", "p-value",
callback=self.FilterAndDisplayGraph,
tooltip="Filter by term p-value")
gui.doubleSpin(gui.indentedBox(box), self, 'maxPValue_nofdr', 1e-8, 1,
step=1e-8, label='p:', labelWidth=15,
callback=self.FilterAndDisplayGraph,
callbackOnReturn=True,
tooltip="Max term p-value")
#use filterByPValue for FDR, as it was the default in prior versions
gui.checkBox(box, self, "filterByPValue", "FDR",
callback=self.FilterAndDisplayGraph,
tooltip="Filter by term FDR")
gui.doubleSpin(gui.indentedBox(box), self, 'maxPValue', 1e-8, 1,
step=1e-8, label='p:', labelWidth=15,
callback=self.FilterAndDisplayGraph,
callbackOnReturn=True,
tooltip="Max term p-value")
box = gui.widgetBox(box, "Significance test")
gui.radioButtonsInBox(box, self, "probFunc", ["Binomial", "Hypergeometric"],
tooltips=["Use binomial distribution test",
"Use hypergeometric distribution test"],
callback=self._updateEnrichment)
box = gui.widgetBox(self.filterTab, "Evidence codes in annotation",
addSpace=True)
self.evidenceCheckBoxDict = {}
for etype in go.evidenceTypesOrdered:
ecb = QCheckBox(
etype, toolTip=go.evidenceTypes[etype],
checked=self.useEvidenceType[etype])
ecb.toggled.connect(self.__on_evidenceChanged)
box.layout().addWidget(ecb)
self.evidenceCheckBoxDict[etype] = ecb
## Select tab
self.selectTab = gui.createTabPage(self.tabs, "Select")
box = gui.radioButtonsInBox(
self.selectTab, self, "selectionDirectAnnotation",
["Directly or Indirectly", "Directly"],
box="Annotated genes",
callback=self.ExampleSelection)
box = gui.widgetBox(self.selectTab, "Output", addSpace=True)
gui.radioButtonsInBox(
box, self, "selectionDisjoint",
btnLabels=["All selected genes",
"Term-specific genes",
"Common term genes"],
tooltips=["Outputs genes annotated to all selected GO terms",
"Outputs genes that appear in only one of selected GO terms",
"Outputs genes common to all selected GO terms"],
callback=[self.ExampleSelection,
self.UpdateAddClassButton])
self.addClassCB = gui.checkBox(
box, self, "selectionAddTermAsClass", "Add GO Term as class",
callback=self.ExampleSelection)
# ListView for DAG, and table for significant GOIDs
self.DAGcolumns = ['GO term', 'Cluster', 'Reference', 'p-value',
'FDR', 'Genes', 'Enrichment']
self.splitter = QSplitter(Qt.Vertical, self.mainArea)
self.mainArea.layout().addWidget(self.splitter)
# list view
self.listView = GOTreeWidget(self.splitter)
self.listView.setSelectionMode(QTreeView.ExtendedSelection)
self.listView.setAllColumnsShowFocus(1)
self.listView.setColumnCount(len(self.DAGcolumns))
self.listView.setHeaderLabels(self.DAGcolumns)
self.listView.header().setSectionsClickable(True)
self.listView.header().setSortIndicatorShown(True)
self.listView.setSortingEnabled(True)
self.listView.setItemDelegateForColumn(
6, EnrichmentColumnItemDelegate(self))
self.listView.setRootIsDecorated(True)
self.listView.itemSelectionChanged.connect(self.ViewSelectionChanged)
# table of significant GO terms
self.sigTerms = QTreeWidget(self.splitter)
self.sigTerms.setColumnCount(len(self.DAGcolumns))
self.sigTerms.setHeaderLabels(self.DAGcolumns)
self.sigTerms.setSortingEnabled(True)
self.sigTerms.setSelectionMode(QTreeView.ExtendedSelection)
self.sigTerms.setItemDelegateForColumn(
6, EnrichmentColumnItemDelegate(self))
self.sigTerms.itemSelectionChanged.connect(self.TableSelectionChanged)
self.sigTableTermsSorted = []
self.graph = {}
self.inputTab.layout().addStretch(1)
self.filterTab.layout().addStretch(1)
self.selectTab.layout().addStretch(1)
self.setBlocking(True)
self._executor = ThreadExecutor()
self._init = EnsureDownloaded(
[(taxonomy.Taxonomy.DOMAIN, taxonomy.Taxonomy.FILENAME),
("GO", "taxonomy.pickle")]
)
self._init.finished.connect(self.__initialize_finish)
self._executor.submit(self._init)
def sizeHint(self):
return QSize(1000, 700)
def __initialize_finish(self):
self.setBlocking(False)
try:
self.annotationFiles = listAvailable()
except ConnectTimeout:
self.error(2, "Internet connection error, unable to load data. " + \
"Check connection and create a new GO Browser widget.")
self.filterTab.setEnabled(False)
self.inputTab.setEnabled(False)
self.selectTab.setEnabled(False)
self.listView.setEnabled(False)
self.sigTerms.setEnabled(False)
else:
self.annotationCodes = sorted(self.annotationFiles.keys())
self.annotationComboBox.clear()
self.annotationComboBox.addItems(self.annotationCodes)
self.annotationComboBox.setCurrentIndex(self.annotationIndex)
self.__state = OWGOEnrichmentAnalysis.Ready
def __on_evidenceChanged(self):
for etype, cb in self.evidenceCheckBoxDict.items():
self.useEvidenceType[etype] = cb.isChecked()
self._updateEnrichment()
def UpdateGeneMatcher(self):
"""Open the Gene matcher settings dialog."""
dialog = GeneMatcherDialog(self, defaults=self.geneMatcherSettings, modal=True)
if dialog.exec_() != QDialog.Rejected:
self.geneMatcherSettings = [getattr(dialog, item[0]) for item in dialog.items]
if self.annotations:
self.SetGeneMatcher()
self._updateEnrichment()
def clear(self):
self.infoLabel.setText("No data on input\n")
self.warning(0)
self.warning(1)
self.geneAttrIndexCombo.clear()
self.ClearGraph()
self.send("Data on Selected Genes", None)
self.send("Data on Unselected Genes", None)
self.send("Data on Unknown Genes", None)
self.send("Enrichment Report", None)
def setDataset(self, data=None):
if self.__state == OWGOEnrichmentAnalysis.Initializing:
self.__initialize_finish()
self.closeContext()
self.clear()
self.clusterDataset = data
if data is not None:
domain = data.domain
allvars = domain.variables + domain.metas
self.candidateGeneAttrs = [var for var in allvars if isstring(var)]
self.geneAttrIndexCombo.clear()
for var in self.candidateGeneAttrs:
self.geneAttrIndexCombo.addItem(*gui.attributeItem(var))
taxid = data_hints.get_hint(data, "taxid", "")
code = None
try:
code = go.from_taxid(taxid)
except KeyError:
pass
except Exception as ex:
print(ex)
if code is not None:
filename = "gene_association.%s.tar.gz" % code
if filename in self.annotationFiles.values():
self.annotationIndex = \
[i for i, name in enumerate(self.annotationCodes) \
if self.annotationFiles[name] == filename].pop()
self.useAttrNames = data_hints.get_hint(data, "genesinrows",
self.useAttrNames)
self.openContext(data)
self.geneAttrIndex = min(self.geneAttrIndex,
len(self.candidateGeneAttrs) - 1)
if len(self.candidateGeneAttrs) == 0:
self.useAttrNames = True
self.geneAttrIndex = -1
elif self.geneAttrIndex < len(self.candidateGeneAttrs):
self.geneAttrIndex = len(self.candidateGeneAttrs) - 1
self._updateEnrichment()
def setReferenceDataset(self, data=None):
self.referenceDataset = data
self.referenceRadioBox.buttons[1].setDisabled(not bool(data))
self.referenceRadioBox.buttons[1].setText("Reference set")
if self.clusterDataset is not None and self.useReferenceDataset:
self.useReferenceDataset = 0 if not data else 1
graph = self.Enrichment()
self.SetGraph(graph)
elif self.clusterDataset:
self.__updateReferenceSetButton()
def handleNewSignals(self):
super().handleNewSignals()
def _updateEnrichment(self):
if self.clusterDataset is not None and \
self.__state == OWGOEnrichmentAnalysis.Ready:
pb = gui.ProgressBar(self, 100)
self.Load(pb=pb)
graph = self.Enrichment(pb=pb)
self.FilterUnknownGenes()
self.SetGraph(graph)
def __updateReferenceSetButton(self):
allgenes, refgenes = None, None
if self.referenceDataset:
try:
allgenes = self.genesFromTable(self.referenceDataset)
except Exception:
allgenes = []
refgenes, unknown = self.FilterAnnotatedGenes(allgenes)
self.referenceRadioBox.buttons[1].setDisabled(not bool(allgenes))
self.referenceRadioBox.buttons[1].setText("Reference set " + ("(%i genes, %i matched)" % (len(allgenes), len(refgenes)) if allgenes and refgenes else ""))
def genesFromTable(self, data):
if self.useAttrNames:
genes = [v.name for v in data.domain.variables]
else:
attr = self.candidateGeneAttrs[min(self.geneAttrIndex, len(self.candidateGeneAttrs) - 1)]
genes = [str(ex[attr]) for ex in data if not numpy.isnan(ex[attr])]
if any("," in gene for gene in genes):
self.information(0, "Separators detected in gene names. Assuming multiple genes per example.")
genes = reduce(operator.iadd, (genes.split(",") for genes in genes), [])
return genes
def FilterAnnotatedGenes(self, genes):
matchedgenes = self.annotations.get_gene_names_translator(genes).values()
return matchedgenes, [gene for gene in genes if gene not in matchedgenes]
def FilterUnknownGenes(self):
if not self.useAttrNames and self.candidateGeneAttrs:
geneAttr = self.candidateGeneAttrs[min(self.geneAttrIndex, len(self.candidateGeneAttrs)-1)]
indices = []
for i, ex in enumerate(self.clusterDataset):
if not any(self.annotations.genematcher.match(n.strip()) for n in str(ex[geneAttr]).split(",")):
indices.append(i)
if indices:
data = self.clusterDataset[indices]
else:
data = None
self.send("Data on Unknown Genes", data)
else:
self.send("Data on Unknown Genes", None)
def Load(self, pb=None):
if self.__state == OWGOEnrichmentAnalysis.Ready:
go_files, tax_files = serverfiles.listfiles("GO"), serverfiles.listfiles("Taxonomy")
calls = []
pb, finish = (gui.ProgressBar(self, 0), True) if pb is None else (pb, False)
count = 0
if not tax_files:
calls.append(("Taxonomy", "ncbi_taxnomy.tar.gz"))
count += 1
org = self.annotationCodes[min(self.annotationIndex, len(self.annotationCodes)-1)]
if org != self.loadedAnnotationCode:
count += 1
if self.annotationFiles[org] not in go_files:
calls.append(("GO", self.annotationFiles[org]))
count += 1
if "gene_ontology_edit.obo.tar.gz" not in go_files:
calls.append(("GO", "gene_ontology_edit.obo.tar.gz"))
count += 1
if not self.ontology:
count += 1
pb.iter += count * 100
for args in calls:
serverfiles.localpath_download(*args, **dict(callback=pb.advance))
i = len(calls)
if not self.ontology:
self.ontology = go.Ontology(progress_callback=lambda value: pb.advance())
i += 1
if org != self.loadedAnnotationCode:
self.annotations = None
gc.collect() # Force run garbage collection
code = self.annotationFiles[org].split(".")[-3]
self.annotations = go.Annotations(code, genematcher=gene.GMDirect(), progress_callback=lambda value: pb.advance())
i += 1
self.loadedAnnotationCode = org
count = defaultdict(int)
geneSets = defaultdict(set)
for anno in self.annotations.annotations:
count[anno.evidence] += 1
geneSets[anno.evidence].add(anno.geneName)
for etype in go.evidenceTypesOrdered:
ecb = self.evidenceCheckBoxDict[etype]
ecb.setEnabled(bool(count[etype]))
ecb.setText(etype + ": %i annots(%i genes)" % (count[etype], len(geneSets[etype])))
if finish:
pb.finish()
def SetGeneMatcher(self):
if self.annotations:
taxid = self.annotations.taxid
matchers = []
for matcher, use in zip([gene.GMGO, gene.GMKEGG, gene.GMNCBI, gene.GMAffy], self.geneMatcherSettings):
if use:
try:
if taxid == "352472":
matchers.extend([matcher(taxid), gene.GMDicty(),
[matcher(taxid), gene.GMDicty()]])
# The reason machers are duplicated is that we want `matcher` or `GMDicty` to
# match genes by them self if possible. Only use the joint matcher if they fail.
else:
matchers.append(matcher(taxid))
except Exception as ex:
print(ex)
self.annotations.genematcher = gene.matcher(matchers)
self.annotations.genematcher.set_targets(self.annotations.gene_names)
def Enrichment(self, pb=None):
assert self.clusterDataset is not None
pb = gui.ProgressBar(self, 100) if pb is None else pb
if not self.annotations.ontology:
self.annotations.ontology = self.ontology
if isinstance(self.annotations.genematcher, gene.GMDirect):
self.SetGeneMatcher()
self.error(1)
self.warning([0, 1])
if self.useAttrNames:
clusterGenes = [v.name for v in self.clusterDataset.domain.attributes]
self.information(0)
elif 0 <= self.geneAttrIndex < len(self.candidateGeneAttrs):
geneAttr = self.candidateGeneAttrs[self.geneAttrIndex]
clusterGenes = [str(ex[geneAttr]) for ex in self.clusterDataset
if not numpy.isnan(ex[geneAttr])]
if any("," in gene for gene in clusterGenes):
self.information(0, "Separators detected in cluster gene names. Assuming multiple genes per example.")
clusterGenes = reduce(operator.iadd, (genes.split(",") for genes in clusterGenes), [])
else:
self.information(0)
else:
self.error(1, "Failed to extract gene names from input dataset!")
return {}
genesSetCount = len(set(clusterGenes))
self.clusterGenes = clusterGenes = self.annotations.get_gene_names_translator(clusterGenes).values()
self.infoLabel.setText("%i unique genes on input\n%i (%.1f%%) genes with known annotations" % (genesSetCount, len(clusterGenes), 100.0*len(clusterGenes)/genesSetCount if genesSetCount else 0.0))
referenceGenes = None
if not self.useReferenceDataset or self.referenceDataset is None:
self.information(2)
self.information(1)
referenceGenes = self.annotations.gene_names
elif self.referenceDataset is not None:
if self.useAttrNames:
referenceGenes = [v.name for v in self.referenceDataset.domain.attributes]
self.information(1)
elif geneAttr in (self.referenceDataset.domain.variables +
self.referenceDataset.domain.metas):
referenceGenes = [str(ex[geneAttr]) for ex in self.referenceDataset
if not numpy.isnan(ex[geneAttr])]
if any("," in gene for gene in clusterGenes):
self.information(1, "Separators detected in reference gene names. Assuming multiple genes per example.")
referenceGenes = reduce(operator.iadd, (genes.split(",") for genes in referenceGenes), [])
else:
self.information(1)
else:
self.information(1)
referenceGenes = None
if referenceGenes is None:
referenceGenes = list(self.annotations.gene_names)
self.referenceRadioBox.buttons[1].setText("Reference set")
self.referenceRadioBox.buttons[1].setDisabled(True)
self.information(2, "Unable to extract gene names from reference dataset. Using entire genome for reference")
self.useReferenceDataset = 0
else:
refc = len(referenceGenes)
referenceGenes = self.annotations.get_gene_names_translator(referenceGenes).values()
self.referenceRadioBox.buttons[1].setText("Reference set (%i genes, %i matched)" % (refc, len(referenceGenes)))
self.referenceRadioBox.buttons[1].setDisabled(False)
self.information(2)
else:
self.useReferenceDataset = 0
if not referenceGenes:
self.error(1, "No valid reference set")
return {}
self.referenceGenes = referenceGenes
evidences = []
for etype in go.evidenceTypesOrdered:
if self.useEvidenceType[etype]:
evidences.append(etype)
aspect = ["P", "C", "F"][self.aspectIndex]
if clusterGenes:
self.terms = terms = self.annotations.get_enriched_terms(
clusterGenes, referenceGenes, evidences, aspect=aspect,
prob=self.probFunctions[self.probFunc], use_fdr=False,
progress_callback=lambda value: pb.advance())
ids = []
pvals = []
for i, d in self.terms.items():
ids.append(i)
pvals.append(d[1])
for i, fdr in zip(ids, stats.FDR(pvals)): # save FDR as the last part of the tuple
terms[i] = tuple(list(terms[i]) + [ fdr ])
else:
self.terms = terms = {}
if not self.terms:
self.warning(0, "No enriched terms found.")
else:
self.warning(0)
pb.finish()
self.treeStructDict = {}
ids = self.terms.keys()
self.treeStructRootKey = None
parents = {}
for id in ids:
parents[id] = set([term for _, term in self.ontology[id].related])
children = {}
for term in self.terms:
children[term] = set([id for id in ids if term in parents[id]])
for term in self.terms:
self.treeStructDict[term] = TreeNode(self.terms[term], children[term])
if not self.ontology[term].related and not getattr(self.ontology[term], "is_obsolete", False):
self.treeStructRootKey = term
return terms
def FilterGraph(self, graph):
if self.filterByPValue_nofdr:
graph = go.filterByPValue(graph, self.maxPValue_nofdr)
if self.filterByPValue: #FDR
graph = dict(filter(lambda item: item[1][3] <= self.maxPValue, graph.items()))
if self.filterByNumOfInstances:
graph = dict(filter(lambda item: len(item[1][0]) >= self.minNumOfInstances, graph.items()))
return graph
def FilterAndDisplayGraph(self):
if self.clusterDataset:
self.graph = self.FilterGraph(self.originalGraph)
if self.originalGraph and not self.graph:
self.warning(1, "All found terms were filtered out.")
else:
self.warning(1)
self.ClearGraph()
self.DisplayGraph()
def SetGraph(self, graph=None):
self.originalGraph = graph
if graph:
self.FilterAndDisplayGraph()
else:
self.graph = {}
self.ClearGraph()
def ClearGraph(self):
self.listView.clear()
self.listViewItems=[]
self.sigTerms.clear()
def DisplayGraph(self):
fromParentDict = {}
self.termListViewItemDict = {}
self.listViewItems = []
enrichment = lambda t: len(t[0]) / t[2] * (len(self.referenceGenes) / len(self.clusterGenes))
maxFoldEnrichment = max([enrichment(term) for term in self.graph.values()] or [1])
def addNode(term, parent, parentDisplayNode):
if (parent, term) in fromParentDict:
return
if term in self.graph:
displayNode = GOTreeWidgetItem(self.ontology[term], self.graph[term], len(self.clusterGenes), len(self.referenceGenes), maxFoldEnrichment, parentDisplayNode)
displayNode.goId = term
self.listViewItems.append(displayNode)
if term in self.termListViewItemDict:
self.termListViewItemDict[term].append(displayNode)
else:
self.termListViewItemDict[term] = [displayNode]
fromParentDict[(parent, term)] = True
parent = term
else:
displayNode = parentDisplayNode
for c in self.treeStructDict[term].children:
addNode(c, parent, displayNode)
if self.treeStructDict:
addNode(self.treeStructRootKey, None, self.listView)
terms = self.graph.items()
terms = sorted(terms, key=lambda item: item[1][1])
self.sigTableTermsSorted = [t[0] for t in terms]
self.sigTerms.clear()
for i, (t_id, (genes, p_value, refCount, fdr)) in enumerate(terms):
item = GOTreeWidgetItem(self.ontology[t_id],
(genes, p_value, refCount, fdr),
len(self.clusterGenes),
len(self.referenceGenes),
maxFoldEnrichment,
self.sigTerms)
item.goId = t_id
self.listView.expandAll()
for i in range(5):
self.listView.resizeColumnToContents(i)
self.sigTerms.resizeColumnToContents(i)
self.sigTerms.resizeColumnToContents(6)
width = min(self.listView.columnWidth(0), 350)
self.listView.setColumnWidth(0, width)
self.sigTerms.setColumnWidth(0, width)
# Create and send the enrichemnt report table.
termsDomain = Orange.data.Domain(
[], [],
# All is meta!
[Orange.data.StringVariable("GO Term Id"),
Orange.data.StringVariable("GO Term Name"),
Orange.data.ContinuousVariable("Cluster Frequency"),
Orange.data.ContinuousVariable("Genes in Cluster", number_of_decimals=0),
Orange.data.ContinuousVariable("Reference Frequency"),
Orange.data.ContinuousVariable("Genes in Reference", number_of_decimals=0),
Orange.data.ContinuousVariable("p-value"),
Orange.data.ContinuousVariable("FDR"),
Orange.data.ContinuousVariable("Enrichment"),
Orange.data.StringVariable("Genes")])
terms = [[t_id,
self.ontology[t_id].name,
len(genes) / len(self.clusterGenes),
len(genes),
r_count / len(self.referenceGenes),
r_count,
p_value,
fdr,
len(genes) / len(self.clusterGenes) * \
len(self.referenceGenes) / r_count,
",".join(genes)
]
for t_id, (genes, p_value, r_count, fdr) in terms]
if terms:
X = numpy.empty((len(terms), 0))
M = numpy.array(terms, dtype=object)
termsTable = Orange.data.Table.from_numpy(termsDomain, X, metas=M)
else:
termsTable = Orange.data.Table(termsDomain)
self.send("Enrichment Report", termsTable)
def ViewSelectionChanged(self):
if self.selectionChanging:
return
self.selectionChanging = 1
self.selectedTerms = []
selected = self.listView.selectedItems()
self.selectedTerms = list(set([lvi.term.id for lvi in selected]))
self.ExampleSelection()
self.selectionChanging = 0
def TableSelectionChanged(self):
if self.selectionChanging:
return
self.selectionChanging = 1
self.selectedTerms = []
selectedIds = set([self.sigTerms.itemFromIndex(index).goId for index in self.sigTerms.selectedIndexes()])
for i in range(self.sigTerms.topLevelItemCount()):
item = self.sigTerms.topLevelItem(i)
selected = item.goId in selectedIds
term = item.goId
if selected:
self.selectedTerms.append(term)
for lvi in self.termListViewItemDict[term]:
try:
lvi.setSelected(selected)
if selected:
lvi.setExpanded(True)
except RuntimeError: # Underlying C/C++ object deleted
pass
self.ExampleSelection()
self.selectionChanging = 0
def UpdateAddClassButton(self):
self.addClassCB.setEnabled(self.selectionDisjoint == 1)
def ExampleSelection(self):
self.commit()
def commit(self):
if self.clusterDataset is None:
return
terms = set(self.selectedTerms)
genes = reduce(operator.ior,
(set(self.graph[term][0]) for term in terms), set())
evidences = []
for etype in go.evidenceTypesOrdered:
if self.useEvidenceType[etype]:
# if getattr(self, "useEvidence" + etype):
evidences.append(etype)
allTerms = self.annotations.get_annotated_terms(
genes, direct_annotation_only=self.selectionDirectAnnotation,
evidence_codes=evidences)
if self.selectionDisjoint > 0:
count = defaultdict(int)
for term in self.selectedTerms:
for g in allTerms.get(term, []):
count[g] += 1
ccount = 1 if self.selectionDisjoint == 1 else len(self.selectedTerms)
selectedGenes = [gene for gene, c in count.items()
if c == ccount and gene in genes]
else:
selectedGenes = reduce(
operator.ior,
(set(allTerms.get(term, [])) for term in self.selectedTerms),
set())
if self.useAttrNames:
vars = [self.clusterDataset.domain[gene]
for gene in set(selectedGenes)]
domain = Orange.data.Domain(
vars, self.clusterDataset.domain.class_vars,
self.clusterDataset.domain.metas)
newdata = self.clusterDataset.from_table(domain, self.clusterDataset)
self.send("Data on Selected Genes", newdata)
self.send("Data on Unselected Genes", None)
elif self.candidateGeneAttrs:
selectedExamples = []
unselectedExamples = []
geneAttr = self.candidateGeneAttrs[min(self.geneAttrIndex, len(self.candidateGeneAttrs)-1)]
if self.selectionDisjoint == 1:
goVar = Orange.data.DiscreteVariable(
"GO Term", values=list(self.selectedTerms))
newDomain = Orange.data.Domain(
self.clusterDataset.domain.variables, goVar,
self.clusterDataset.domain.metas)
goColumn = []
for i, ex in enumerate(self.clusterDataset):
if not numpy.isnan(ex[geneAttr]) and any(gene in selectedGenes for gene in str(ex[geneAttr]).split(",")):
if self.selectionDisjoint == 1 and self.selectionAddTermAsClass:
terms = filter(lambda term: any(gene in self.graph[term][0] for gene in str(ex[geneAttr]).split(",")) , self.selectedTerms)
term = sorted(terms)[0]
goColumn.append(goVar.values.index(term))
selectedExamples.append(i)
else:
unselectedExamples.append(i)
if selectedExamples:
selectedExamples = self.clusterDataset[selectedExamples]
if self.selectionDisjoint == 1 and self.selectionAddTermAsClass:
selectedExamples = Orange.data.Table.from_table(newDomain, selectedExamples)
view, issparse = selectedExamples.get_column_view(goVar)
assert not issparse
view[:] = goColumn
else:
selectedExamples = None
if unselectedExamples:
unselectedExamples = self.clusterDataset[unselectedExamples]
else:
unselectedExamples = None
self.send("Data on Selected Genes", selectedExamples)
self.send("Data on Unselected Genes", unselectedExamples)
def ShowInfo(self):
dialog = QDialog(self)
dialog.setModal(False)
dialog.setLayout(QVBoxLayout())
label = QLabel(dialog)
label.setText("Ontology:\n" + self.ontology.header
if self.ontology else "Ontology not loaded!")
dialog.layout().addWidget(label)
label = QLabel(dialog)
label.setText("Annotations:\n" + self.annotations.header.replace("!", "")
if self.annotations else "Annotations not loaded!")
dialog.layout().addWidget(label)
dialog.show()
def onDeleteWidget(self):
"""Called before the widget is removed from the canvas.
"""
self.annotations = None
self.ontology = None
gc.collect() # Force collection
class OWGOBrowser(widget.OWWidget):
name = "GO Browser"
description = "Enrichment analysis for Gene Ontology terms."
icon = "../widgets/icons/OWGOBrowser.svg"
priority = 7
inputs = [("Cluster Data", Orange.data.Table,
"setDataset", widget.Single + widget.Default),
("Reference Data", Orange.data.Table,
"setReferenceDataset")]
outputs = [("Data on Selected Genes", Orange.data.Table),
("Enrichment Report", Orange.data.Table)]
settingsHandler = settings.DomainContextHandler()
geneAttrIndex = settings.ContextSetting(0)
useAttrNames = settings.ContextSetting(False)
useReferenceDataset = settings.Setting(False)
aspectIndex = settings.Setting(0)
useEvidenceType = settings.Setting(
{et: True for et in go.evidenceTypesOrdered})
filterByNumOfInstances = settings.Setting(False)
minNumOfInstances = settings.Setting(1)
filterByPValue = settings.Setting(True)
maxPValue = settings.Setting(0.2)
filterByPValue_nofdr = settings.Setting(False)
maxPValue_nofdr = settings.Setting(0.01)
probFunc = settings.Setting(0)
selectionDirectAnnotation = settings.Setting(0)
selectionDisjoint = settings.Setting(0)
class Error(widget.OWWidget.Error):
serverfiles_unavailable = widget.Msg('Can not locate annotation files, '
'please check your connection and try again.')
missing_annotation = widget.Msg(ERROR_ON_MISSING_ANNOTATION)
missing_gene_id = widget.Msg(ERROR_ON_MISSING_GENE_ID)
missing_tax_id = widget.Msg(ERROR_ON_MISSING_TAX_ID)
def __init__(self, parent=None):
super().__init__(self, parent)
self.input_data = None
self.ref_data = None
self.ontology = None
self.annotations = None
self.loaded_annotation_code = None
self.treeStructRootKey = None
self.probFunctions = [statistics.Binomial(), statistics.Hypergeometric()]
self.selectedTerms = []
self.selectionChanging = 0
self.__state = State.Ready
self.__scheduletimer = QTimer(self, singleShot=True)
self.__scheduletimer.timeout.connect(self.__update)
#############
# GUI
#############
self.tabs = gui.tabWidget(self.controlArea)
# Input tab
self.inputTab = gui.createTabPage(self.tabs, "Input")
box = gui.widgetBox(self.inputTab, "Info")
self.infoLabel = gui.widgetLabel(box, "No data on input\n")
gui.button(box, self, "Ontology/Annotation Info",
callback=self.ShowInfo,
tooltip="Show information on loaded ontology and annotations")
self.referenceRadioBox = gui.radioButtonsInBox(
self.inputTab, self, "useReferenceDataset",
["Entire genome", "Reference set (input)"],
tooltips=["Use entire genome for reference",
"Use genes from Referece Examples input signal as reference"],
box="Reference", callback=self.__invalidate)
self.referenceRadioBox.buttons[1].setDisabled(True)
gui.radioButtonsInBox(
self.inputTab, self, "aspectIndex",
["Biological process", "Cellular component", "Molecular function"],
box="Aspect", callback=self.__invalidate)
# Filter tab
self.filterTab = gui.createTabPage(self.tabs, "Filter")
box = gui.widgetBox(self.filterTab, "Filter GO Term Nodes")
gui.checkBox(box, self, "filterByNumOfInstances", "Genes",
callback=self.FilterAndDisplayGraph,
tooltip="Filter by number of input genes mapped to a term")
ibox = gui.indentedBox(box)
gui.spin(ibox, self, 'minNumOfInstances', 1, 100,
step=1, label='#:', labelWidth=15,
callback=self.FilterAndDisplayGraph,
callbackOnReturn=True,
tooltip="Min. number of input genes mapped to a term")
gui.checkBox(box, self, "filterByPValue_nofdr", "p-value",
callback=self.FilterAndDisplayGraph,
tooltip="Filter by term p-value")
gui.doubleSpin(gui.indentedBox(box), self, 'maxPValue_nofdr', 1e-8, 1,
step=1e-8, label='p:', labelWidth=15,
callback=self.FilterAndDisplayGraph,
callbackOnReturn=True,
tooltip="Max term p-value")
# use filterByPValue for FDR, as it was the default in prior versions
gui.checkBox(box, self, "filterByPValue", "FDR",
callback=self.FilterAndDisplayGraph,
tooltip="Filter by term FDR")
gui.doubleSpin(gui.indentedBox(box), self, 'maxPValue', 1e-8, 1,
step=1e-8, label='p:', labelWidth=15,
callback=self.FilterAndDisplayGraph,
callbackOnReturn=True,
tooltip="Max term p-value")
box = gui.widgetBox(box, "Significance test")
gui.radioButtonsInBox(box, self, "probFunc", ["Binomial", "Hypergeometric"],
tooltips=["Use binomial distribution test",
"Use hypergeometric distribution test"],
callback=self.__invalidate) # TODO: only update the p values
box = gui.widgetBox(self.filterTab, "Evidence codes in annotation",
addSpace=True)
self.evidenceCheckBoxDict = {}
for etype in go.evidenceTypesOrdered:
ecb = QCheckBox(
etype, toolTip=go.evidenceTypes[etype],
checked=self.useEvidenceType[etype])
ecb.toggled.connect(self.__on_evidenceChanged)
box.layout().addWidget(ecb)
self.evidenceCheckBoxDict[etype] = ecb
# Select tab
self.selectTab = gui.createTabPage(self.tabs, "Select")
box = gui.radioButtonsInBox(
self.selectTab, self, "selectionDirectAnnotation",
["Directly or Indirectly", "Directly"],
box="Annotated genes",
callback=self.ExampleSelection)
box = gui.widgetBox(self.selectTab, "Output", addSpace=True)
gui.radioButtonsInBox(
box, self, "selectionDisjoint",
btnLabels=["All selected genes",
"Term-specific genes",
"Common term genes"],
tooltips=["Outputs genes annotated to all selected GO terms",
"Outputs genes that appear in only one of selected GO terms",
"Outputs genes common to all selected GO terms"],
callback=self.ExampleSelection)
# ListView for DAG, and table for significant GOIDs
self.DAGcolumns = ['GO term', 'Cluster', 'Reference', 'p-value',
'FDR', 'Genes', 'Enrichment']
self.splitter = QSplitter(Qt.Vertical, self.mainArea)
self.mainArea.layout().addWidget(self.splitter)
# list view
self.listView = GOTreeWidget(self.splitter)
self.listView.setSelectionMode(QTreeView.ExtendedSelection)
self.listView.setAllColumnsShowFocus(1)
self.listView.setColumnCount(len(self.DAGcolumns))
self.listView.setHeaderLabels(self.DAGcolumns)
self.listView.header().setSectionsClickable(True)
self.listView.header().setSortIndicatorShown(True)
self.listView.header().setSortIndicator(self.DAGcolumns.index('p-value'), Qt.AscendingOrder)
self.listView.setSortingEnabled(True)
self.listView.setItemDelegateForColumn(
6, EnrichmentColumnItemDelegate(self))
self.listView.setRootIsDecorated(True)
self.listView.itemSelectionChanged.connect(self.ViewSelectionChanged)
# table of significant GO terms
self.sigTerms = QTreeWidget(self.splitter)
self.sigTerms.setColumnCount(len(self.DAGcolumns))
self.sigTerms.setHeaderLabels(self.DAGcolumns)
self.sigTerms.setSortingEnabled(True)
self.sigTerms.setSelectionMode(QTreeView.ExtendedSelection)
self.sigTerms.header().setSortIndicator(self.DAGcolumns.index('p-value'), Qt.AscendingOrder)
self.sigTerms.setItemDelegateForColumn(
6, EnrichmentColumnItemDelegate(self))
self.sigTerms.itemSelectionChanged.connect(self.TableSelectionChanged)
self.sigTableTermsSorted = []
self.graph = {}
self.originalGraph = None
self.inputTab.layout().addStretch(1)
self.filterTab.layout().addStretch(1)
self.selectTab.layout().addStretch(1)
class AnnotationSlot(SimpleNamespace):
taxid = ... # type: str
name = ... # type: str
filename = ... # type:str
@staticmethod
def parse_tax_id(f_name):
return f_name.split('.')[1]
try:
remote_files = serverfiles.ServerFiles().listfiles(DOMAIN)
except (ConnectTimeout, RequestException, ConnectionError):
# TODO: Warn user about failed connection to the remote server
remote_files = []
self.available_annotations = [
AnnotationSlot(
taxid=AnnotationSlot.parse_tax_id(annotation_file),
name=taxonomy.common_taxid_to_name(AnnotationSlot.parse_tax_id(annotation_file)),
filename=FILENAME_ANNOTATION.format(AnnotationSlot.parse_tax_id(annotation_file))
)
for _, annotation_file in set(remote_files + serverfiles.listfiles(DOMAIN))
if annotation_file != FILENAME_ONTOLOGY
]
self._executor = ThreadExecutor()
def sizeHint(self):
return QSize(1000, 700)
def __on_evidenceChanged(self):
for etype, cb in self.evidenceCheckBoxDict.items():
self.useEvidenceType[etype] = cb.isChecked()
self.__invalidate()
def clear(self):
self.infoLabel.setText("No data on input\n")
self.warning(0)
self.warning(1)
self.ClearGraph()
self.send("Data on Selected Genes", None)
self.send("Enrichment Report", None)
def setDataset(self, data=None):
self.closeContext()
self.clear()
self.Error.clear()
if data:
self.input_data = data
self.tax_id = str(self.input_data.attributes.get(TAX_ID, None))
self.use_attr_names = self.input_data.attributes.get(GENE_AS_ATTRIBUTE_NAME, None)
self.gene_id_attribute = self.input_data.attributes.get(GENE_ID_ATTRIBUTE, None)
self.gene_id_column = self.input_data.attributes.get(GENE_ID_COLUMN, None)
self.annotation_index = None
if not(self.use_attr_names is not None
and ((self.gene_id_attribute is None) ^ (self.gene_id_column is None))):
if self.tax_id is None:
self.Error.missing_annotation()
return
self.Error.missing_gene_id()
return
elif self.tax_id is None:
self.Error.missing_tax_id()
return
_c2i = {a.taxid: i for i, a in enumerate(self.available_annotations)}
try:
self.annotation_index = _c2i[self.tax_id]
except KeyError:
self.Error.serverfiles_unavailable()
# raise ValueError('Taxonomy {} not supported.'.format(self.tax_id))
return
self.__invalidate()
def setReferenceDataset(self, data=None):
self.Error.clear()
if data:
self.ref_data = data
self.ref_tax_id = str(self.ref_data.attributes.get(TAX_ID, None))
self.ref_use_attr_names = self.ref_data.attributes.get(GENE_AS_ATTRIBUTE_NAME, None)
self.ref_gene_id_attribute = self.ref_data.attributes.get(GENE_ID_ATTRIBUTE, None)
self.ref_gene_id_column = self.ref_data.attributes.get(GENE_ID_COLUMN, None)
if not (self.ref_use_attr_names is not None
and ((self.ref_gene_id_attribute is None) ^ (self.ref_gene_id_column is None))):
if self.ref_tax_id is None:
self.Error.missing_annotation()
return
self.Error.missing_gene_id()
return
elif self.ref_tax_id is None:
self.Error.missing_tax_id()
return
self.referenceRadioBox.buttons[1].setDisabled(not bool(data))
self.referenceRadioBox.buttons[1].setText("Reference set")
if self.input_data is not None and self.useReferenceDataset:
self.useReferenceDataset = 0 if not data else 1
self.__invalidate()
@Slot()
def __invalidate(self):
# Invalidate the current results or pending task and schedule an
# update.
self.__scheduletimer.start()
if self.__state != State.Ready:
self.__state |= State.Stale
self.SetGraph({})
self.ref_genes = None
self.input_genes = None
def __invalidateAnnotations(self):
self.annotations = None
self.loaded_annotation_code = None
if self.input_data:
self.infoLabel.setText("...\n")
self.__invalidate()
@Slot()
def __update(self):
self.__scheduletimer.stop()
if self.input_data is None:
return
if self.__state & State.Running:
self.__state |= State.Stale
elif self.__state & State.Downloading:
self.__state |= State.Stale
elif self.__state & State.Ready:
if self.__ensure_data():
self.Load()
self.Enrichment()
else:
assert self.__state & State.Downloading
assert self.isBlocking()
def __get_ref_genes(self):
self.ref_genes = []
if self.ref_use_attr_names:
for variable in self.input_data.domain.attributes:
self.ref_genes.append(str(variable.attributes.get(self.ref_gene_id_attribute, '?')))
else:
genes, _ = self.ref_data.get_column_view(self.ref_gene_id_column)
self.ref_genes = [str(g) for g in genes]
def __get_input_genes(self):
self.input_genes = []
if self.use_attr_names:
for variable in self.input_data.domain.attributes:
self.input_genes .append(str(variable.attributes.get(self.gene_id_attribute, '?')))
else:
genes, _ = self.input_data.get_column_view(self.gene_id_column)
self.input_genes = [str(g) for g in genes]
def FilterAnnotatedGenes(self, genes):
matchedgenes = self.annotations.get_gene_names_translator(genes).values()
return matchedgenes, [gene for gene in genes if gene not in matchedgenes]
def __start_download(self, files_list):
# type: (List[Tuple[str, str]]) -> None
task = EnsureDownloaded(files_list)
task.progress.connect(self._progressBarSet)
f = self._executor.submit(task)
fw = FutureWatcher(f, self)
fw.finished.connect(self.__download_finish)
fw.finished.connect(fw.deleteLater)
fw.resultReady.connect(self.__invalidate)
self.progressBarInit(processEvents=None)
self.setBlocking(True)
self.setStatusMessage("Downloading")
self.__state = State.Downloading
@Slot(Future)
def __download_finish(self, result):
# type: (Future[None]) -> None
assert QThread.currentThread() is self.thread()
assert result.done()
self.setBlocking(False)
self.setStatusMessage("")
self.progressBarFinished(processEvents=False)
try:
result.result()
except ConnectTimeout:
logging.getLogger(__name__).error("Error:")
self.error(2, "Internet connection error, unable to load data. " +
"Check connection and create a new GO Browser widget.")
except RequestException as err:
logging.getLogger(__name__).error("Error:")
self.error(2, "Internet error:\n" + str(err))
except BaseException as err:
logging.getLogger(__name__).error("Error:")
self.error(2, "Error:\n" + str(err))
raise
else:
self.error(2)
finally:
self.__state = State.Ready
def __ensure_data(self):
# Ensure that all required database (ontology and annotations for
# the current selected organism are present. If not start a download in
# the background. Return True if all dbs are present and false
# otherwise
assert self.__state == State.Ready
annotation = self.available_annotations[self.annotation_index]
go_files = [fname for domain, fname in serverfiles.listfiles(DOMAIN)]
files = []
if annotation.filename not in go_files:
files.append(("GO", annotation.filename))
if FILENAME_ONTOLOGY not in go_files:
files.append((DOMAIN, FILENAME_ONTOLOGY))
if files:
self.__start_download(files)
assert self.__state == State.Downloading
return False
else:
return True
def Load(self):
a = self.available_annotations[self.annotation_index]
if self.ontology is None:
self.ontology = go.Ontology()
if a.taxid != self.loaded_annotation_code:
self.annotations = None
gc.collect() # Force run garbage collection
self.annotations = go.Annotations(a.taxid)
self.loaded_annotation_code = a.taxid
count = defaultdict(int)
geneSets = defaultdict(set)
for anno in self.annotations.annotations:
count[anno.evidence] += 1
geneSets[anno.evidence].add(anno.gene_id)
for etype in go.evidenceTypesOrdered:
ecb = self.evidenceCheckBoxDict[etype]
ecb.setEnabled(bool(count[etype]))
ecb.setText(etype + ": %i annots(%i genes)" % (count[etype], len(geneSets[etype])))
def Enrichment(self):
assert self.input_data is not None
assert self.__state == State.Ready
if not self.annotations.ontology:
self.annotations.ontology = self.ontology
self.error(1)
self.warning([0, 1])
self.__get_input_genes()
self.input_genes = set(self.input_genes)
self.known_input_genes = self.annotations.get_genes_with_known_annotation(self.input_genes)
# self.clusterGenes = clusterGenes = self.annotations.map_to_ncbi_id(self.input_genes).values()
self.infoLabel.setText("%i unique genes on input\n%i (%.1f%%) genes with known annotations" %
(len(self.input_genes), len(self.known_input_genes),
100.0*len(self.known_input_genes)/len(self.input_genes)
if len(self.input_genes) else 0.0))
if not self.useReferenceDataset or self.ref_data is None:
self.information(2)
self.information(1)
self.ref_genes = self.annotations.genes()
self.ref_genes = set(self.ref_genes)
elif self.ref_data is not None:
self.__get_ref_genes()
self.ref_genes = set(self.ref_genes)
ref_count = len(self.ref_genes)
if ref_count == 0:
self.ref_genes = self.annotations.genes()
self.referenceRadioBox.buttons[1].setText("Reference set")
self.referenceRadioBox.buttons[1].setDisabled(True)
self.information(2, "Unable to extract gene names from reference dataset. "
"Using entire genome for reference")
self.useReferenceDataset = 0
else:
self.referenceRadioBox.buttons[1].setText("Reference set ({} genes)".format(ref_count))
self.referenceRadioBox.buttons[1].setDisabled(False)
self.information(2)
else:
self.useReferenceDataset = 0
self.ref_genes = []
if not self.ref_genes:
self.error(1, "No valid reference set")
return {}
evidences = []
for etype in go.evidenceTypesOrdered:
if self.useEvidenceType[etype]:
evidences.append(etype)
aspect = ['Process', 'Component', 'Function'][self.aspectIndex]
self.progressBarInit(processEvents=False)
self.setBlocking(True)
self.__state = State.Running
if self.input_genes:
f = self._executor.submit(
self.annotations.get_enriched_terms,
self.input_genes, self.ref_genes, evidences, aspect=aspect,
prob=self.probFunctions[self.probFunc], use_fdr=False,
progress_callback=methodinvoke(
self, "_progressBarSet", (float,))
)
fw = FutureWatcher(f, parent=self)
fw.done.connect(self.__on_enrichment_done)
fw.done.connect(fw.deleteLater)
return
else:
f = Future()
f.set_result({})
self.__on_enrichment_done(f)
def __on_enrichment_done(self, results):
# type: (Future[Dict[str, tuple]]) -> None
self.progressBarFinished(processEvents=False)
self.setBlocking(False)
self.setStatusMessage("")
if self.__state & State.Stale:
self.__state = State.Ready
self.__invalidate()
return
self.__state = State.Ready
try:
results = results.result() # type: Dict[str, tuple]
except Exception as ex:
results = {}
error = str(ex)
self.error(1, error)
if results:
terms = list(results.items())
fdr_vals = statistics.FDR([d[1] for _, d in terms])
terms = [(key, d + (fdr,))
for (key, d), fdr in zip(terms, fdr_vals)]
terms = dict(terms)
else:
terms = {}
self.terms = terms
if not self.terms:
self.warning(0, "No enriched terms found.")
else:
self.warning(0)
self.treeStructDict = {}
ids = self.terms.keys()
self.treeStructRootKey = None
parents = {}
for id in ids:
parents[id] = set([term for _, term in self.ontology[id].related])
children = {}
for term in self.terms:
children[term] = set([id for id in ids if term in parents[id]])
for term in self.terms:
self.treeStructDict[term] = TreeNode(self.terms[term], children[term])
if not self.ontology[term].related and not getattr(self.ontology[term], "is_obsolete", False):
self.treeStructRootKey = term
self.SetGraph(terms)
self._updateEnrichmentReportOutput()
self.commit()
def _updateEnrichmentReportOutput(self):
terms = sorted(self.terms.items(), key=lambda item: item[1][1])
# Create and send the enrichemnt report table.
termsDomain = Orange.data.Domain(
[], [],
# All is meta!
[Orange.data.StringVariable("GO Term Id"),
Orange.data.StringVariable("GO Term Name"),
Orange.data.ContinuousVariable("Cluster Frequency"),
Orange.data.ContinuousVariable("Genes in Cluster",
number_of_decimals=0),
Orange.data.ContinuousVariable("Reference Frequency"),
Orange.data.ContinuousVariable("Genes in Reference",
number_of_decimals=0),
Orange.data.ContinuousVariable("p-value"),
Orange.data.ContinuousVariable("FDR"),
Orange.data.ContinuousVariable("Enrichment"),
Orange.data.StringVariable("Genes")])
terms = [[t_id,
self.ontology[t_id].name,
len(genes) / len(self.input_genes),
len(genes),
r_count / len(self.ref_genes),
r_count,
p_value,
fdr,
len(genes) / len(self.input_genes) * \
len(self.ref_genes) / r_count,
",".join(genes)
]
for t_id, (genes, p_value, r_count, fdr) in terms
if genes and r_count]
if terms:
X = numpy.empty((len(terms), 0))
M = numpy.array(terms, dtype=object)
termsTable = Orange.data.Table.from_numpy(termsDomain, X,
metas=M)
else:
termsTable = None
self.send("Enrichment Report", termsTable)
@Slot(float)
def _progressBarSet(self, value):
assert QThread.currentThread() is self.thread()
self.progressBarSet(value, processEvents=None)
@Slot()
def _progressBarFinish(self):
assert QThread.currentThread() is self.thread()
self.progressBarFinished(processEvents=None)
def FilterGraph(self, graph):
if self.filterByPValue_nofdr:
graph = go.filterByPValue(graph, self.maxPValue_nofdr)
if self.filterByPValue: # FDR
graph = dict(filter(lambda item: item[1][3] <= self.maxPValue, graph.items()))
if self.filterByNumOfInstances:
graph = dict(filter(lambda item: len(item[1][0]) >= self.minNumOfInstances, graph.items()))
return graph
def FilterAndDisplayGraph(self):
if self.input_data and self.originalGraph is not None:
self.graph = self.FilterGraph(self.originalGraph)
if self.originalGraph and not self.graph:
self.warning(1, "All found terms were filtered out.")
else:
self.warning(1)
self.ClearGraph()
self.DisplayGraph()
def SetGraph(self, graph=None):
self.originalGraph = graph
if graph:
self.FilterAndDisplayGraph()
else:
self.graph = {}
self.ClearGraph()
def ClearGraph(self):
self.listView.clear()
self.listViewItems=[]
self.sigTerms.clear()
def DisplayGraph(self):
fromParentDict = {}
self.termListViewItemDict = {}
self.listViewItems = []
def enrichment(t):
try:
return len(t[0]) / t[2] * (len(self.ref_genes) / len(self.input_genes))
except ZeroDivisionError:
# TODO: find out why this happens
return 0
maxFoldEnrichment = max([enrichment(term) for term in self.graph.values()] or [1])
def addNode(term, parent, parentDisplayNode):
if (parent, term) in fromParentDict:
return
if term in self.graph:
displayNode = GOTreeWidgetItem(self.ontology[term], self.graph[term], len(self.input_genes),
len(self.ref_genes), maxFoldEnrichment, parentDisplayNode)
displayNode.goId = term
self.listViewItems.append(displayNode)
if term in self.termListViewItemDict:
self.termListViewItemDict[term].append(displayNode)
else:
self.termListViewItemDict[term] = [displayNode]
fromParentDict[(parent, term)] = True
parent = term
else:
displayNode = parentDisplayNode
for c in self.treeStructDict[term].children:
addNode(c, parent, displayNode)
if self.treeStructDict:
addNode(self.treeStructRootKey, None, self.listView)
terms = self.graph.items()
terms = sorted(terms, key=lambda item: item[1][1])
self.sigTableTermsSorted = [t[0] for t in terms]
self.sigTerms.clear()
for i, (t_id, (genes, p_value, refCount, fdr)) in enumerate(terms):
item = GOTreeWidgetItem(self.ontology[t_id],
(genes, p_value, refCount, fdr),
len(self.input_genes),
len(self.ref_genes),
maxFoldEnrichment,
self.sigTerms)
item.goId = t_id
self.listView.expandAll()
for i in range(5):
self.listView.resizeColumnToContents(i)
self.sigTerms.resizeColumnToContents(i)
self.sigTerms.resizeColumnToContents(6)
width = min(self.listView.columnWidth(0), 350)
self.listView.setColumnWidth(0, width)
self.sigTerms.setColumnWidth(0, width)
def ViewSelectionChanged(self):
if self.selectionChanging:
return
self.selectionChanging = 1
self.selectedTerms = []
selected = self.listView.selectedItems()
self.selectedTerms = list(set([lvi.term.id for lvi in selected]))
self.ExampleSelection()
self.selectionChanging = 0
def TableSelectionChanged(self):
if self.selectionChanging:
return
self.selectionChanging = 1
self.selectedTerms = []
selectedIds = set([self.sigTerms.itemFromIndex(index).goId for index in self.sigTerms.selectedIndexes()])
for i in range(self.sigTerms.topLevelItemCount()):
item = self.sigTerms.topLevelItem(i)
selected = item.goId in selectedIds
term = item.goId
if selected:
self.selectedTerms.append(term)
for lvi in self.termListViewItemDict[term]:
try:
lvi.setSelected(selected)
if selected:
lvi.setExpanded(True)
except RuntimeError: # Underlying C/C++ object deleted
pass
self.selectionChanging = 0
self.ExampleSelection()
def ExampleSelection(self):
self.commit()
def commit(self):
if self.input_data is None or self.originalGraph is None or \
self.annotations is None:
return
if self.__state & State.Stale:
return
terms = set(self.selectedTerms)
genes = reduce(operator.ior,
(set(self.graph[term][0]) for term in terms), set())
evidences = []
for etype in go.evidenceTypesOrdered:
if self.useEvidenceType[etype]:
evidences.append(etype)
allTerms = self.annotations.get_annotated_terms(
genes, direct_annotation_only=self.selectionDirectAnnotation,
evidence_codes=evidences)
if self.selectionDisjoint > 0:
count = defaultdict(int)
for term in self.selectedTerms:
for g in allTerms.get(term, []):
count[g] += 1
ccount = 1 if self.selectionDisjoint == 1 else len(self.selectedTerms)
selected_genes = [gene for gene, c in count.items() if c == ccount and gene in genes]
else:
selected_genes = reduce(
operator.ior,
(set(allTerms.get(term, [])) for term in self.selectedTerms), set())
if self.use_attr_names:
selected = [column for column in self.input_data.domain.attributes
if self.gene_id_attribute in column.attributes and
str(column.attributes[self.gene_id_attribute]) in set(selected_genes)]
domain = Orange.data.Domain(selected, self.input_data.domain.class_vars, self.input_data.domain.metas)
new_data = self.input_data.from_table(domain, self.input_data)
self.send("Data on Selected Genes", new_data)
else:
selected_rows = []
for row_index, row in enumerate(self.input_data):
gene_in_row = str(row[self.gene_id_column])
if gene_in_row in self.input_genes and gene_in_row in selected_genes:
selected_rows.append(row_index)
if selected_rows:
selected = self.input_data[selected_rows]
else:
selected = None
self.send("Data on Selected Genes", selected)
def ShowInfo(self):
dialog = QDialog(self)
dialog.setModal(False)
dialog.setLayout(QVBoxLayout())
label = QLabel(dialog)
label.setText("Ontology:\n" + self.ontology.header
if self.ontology else "Ontology not loaded!")
dialog.layout().addWidget(label)
label = QLabel(dialog)
label.setText("Annotations:\n" + self.annotations.header.replace("!", "")
if self.annotations else "Annotations not loaded!")
dialog.layout().addWidget(label)
dialog.show()
def onDeleteWidget(self):
"""Called before the widget is removed from the canvas.
"""
self.annotations = None
self.ontology = None
gc.collect() # Force collection
