def __init__(self,parent=None, signalManager = None):
OWWidget.__init__(self, parent, signalManager, "&Display Motifs", 0)
# set default settings
self.colorBy = None
self.pvalThresholdIndex = None
self.pvalThreshold = None
#load settings
self.loadSettings()
# GUI
self.graph = OWGraph(self.mainArea)
self.graph.setYRlabels(None)
self.graph.enableGridXB(0)
self.graph.enableGridYL(1)
self.graph.setAxisMaxMinor(QwtPlot.xBottom, 10)
self.graph.setAxisMaxMajor(QwtPlot.xBottom, 10)
self.graph.setAxisAutoScale(QwtPlot.xBottom)
self.graph.setAxisScale(QwtPlot.xBottom, -1020, 0, 0)
self.mainArea.layout().addWidget(self.graph)
# inputs
# data and graph temp variables
self.inputs = [("Examples", ExampleTable, self.cdata, Default), ("Genes", list, self.newGeneList, Default), ("Motifs", list, self.newMotifList, Default)]
self.data = None
self.motifLines = []
self.visibleValues = []
self.valueToCurve = {}
self.allGenes = [] ## genes displayed always in same order
self.geneList = [] ## selected genes
self.motifList = [] ## selected motifs
self.valuesPresentInData = []
self.clusterPostProbThreshold = 0
# GUI
self.selValues = OWGUI.widgetBox(self.controlArea, "Values")
self.selcolorBy = OWGUI.widgetBox(self.controlArea, "Color By")
self.colorByCombo = OWGUI.comboBox(self.selcolorBy, self, "colorBy",
items=[],
callback=self.colorByChanged)
self.pvalThresholdCombo = OWGUI.comboBox(self.selValues, self, "pvalThresholdIndex",
items=[],
callback=self.pvalThresholdChanged)
self.valuesQLB = QListWidget(self.selValues)
self.valuesQLB.setSelectionMode(QListWidget.MultiSelection)
self.connect(self.valuesQLB, SIGNAL("itemSelectionChanged()"), self.valuesSelectionChange)
self.selValues.layout().addWidget(self.valuesQLB)
self.unselectAllQLB = OWGUI.button(self.selValues, self, "Unselect all",
callback = self.unselAll)
def __init__(self, parent=None, signalManager=None):
OWWidget.__init__(self, parent, signalManager, "&Display Motifs", 0)
# set default settings
self.colorBy = None
self.pvalThresholdIndex = None
self.pvalThreshold = None
#load settings
self.loadSettings()
# GUI
self.graph = OWGraph(self.mainArea)
self.graph.setYRlabels(None)
self.graph.enableGridXB(0)
self.graph.enableGridYL(1)
self.graph.setAxisMaxMinor(QwtPlot.xBottom, 10)
self.graph.setAxisMaxMajor(QwtPlot.xBottom, 10)
self.graph.setAxisAutoScale(QwtPlot.xBottom)
self.graph.setAxisScale(QwtPlot.xBottom, -1020, 0, 0)
self.mainArea.layout().addWidget(self.graph)
# inputs
# data and graph temp variables
self.inputs = [("Examples", ExampleTable, self.cdata, Default),
("Genes", list, self.newGeneList, Default),
("Motifs", list, self.newMotifList, Default)]
self.data = None
self.motifLines = []
self.visibleValues = []
self.valueToCurve = {}
self.allGenes = [] ## genes displayed always in same order
self.geneList = [] ## selected genes
self.motifList = [] ## selected motifs
self.valuesPresentInData = []
self.clusterPostProbThreshold = 0
# GUI
self.selValues = OWGUI.widgetBox(self.controlArea, "Values")
self.selcolorBy = OWGUI.widgetBox(self.controlArea, "Color By")
self.colorByCombo = OWGUI.comboBox(self.selcolorBy,
self,
"colorBy",
items=[],
callback=self.colorByChanged)
self.pvalThresholdCombo = OWGUI.comboBox(
self.selValues,
self,
"pvalThresholdIndex",
items=[],
callback=self.pvalThresholdChanged)
self.valuesQLB = QListWidget(self.selValues)
self.valuesQLB.setSelectionMode(QListWidget.MultiSelection)
self.connect(self.valuesQLB, SIGNAL("itemSelectionChanged()"),
self.valuesSelectionChange)
self.selValues.layout().addWidget(self.valuesQLB)
self.unselectAllQLB = OWGUI.button(self.selValues,
self,
"Unselect all",
callback=self.unselAll)
class OWDisplayMotifs(OWWidget):
settingsList = []
def __init__(self, parent=None, signalManager=None):
OWWidget.__init__(self, parent, signalManager, "&Display Motifs", 0)
# set default settings
self.colorBy = None
self.pvalThresholdIndex = None
self.pvalThreshold = None
#load settings
self.loadSettings()
# GUI
self.graph = OWGraph(self.mainArea)
self.graph.setYRlabels(None)
self.graph.enableGridXB(0)
self.graph.enableGridYL(1)
self.graph.setAxisMaxMinor(QwtPlot.xBottom, 10)
self.graph.setAxisMaxMajor(QwtPlot.xBottom, 10)
self.graph.setAxisAutoScale(QwtPlot.xBottom)
self.graph.setAxisScale(QwtPlot.xBottom, -1020, 0, 0)
self.mainArea.layout().addWidget(self.graph)
# inputs
# data and graph temp variables
self.inputs = [("Examples", ExampleTable, self.cdata, Default),
("Genes", list, self.newGeneList, Default),
("Motifs", list, self.newMotifList, Default)]
self.data = None
self.motifLines = []
self.visibleValues = []
self.valueToCurve = {}
self.allGenes = [] ## genes displayed always in same order
self.geneList = [] ## selected genes
self.motifList = [] ## selected motifs
self.valuesPresentInData = []
self.clusterPostProbThreshold = 0
# GUI
self.selValues = OWGUI.widgetBox(self.controlArea, "Values")
self.selcolorBy = OWGUI.widgetBox(self.controlArea, "Color By")
self.colorByCombo = OWGUI.comboBox(self.selcolorBy,
self,
"colorBy",
items=[],
callback=self.colorByChanged)
self.pvalThresholdCombo = OWGUI.comboBox(
self.selValues,
self,
"pvalThresholdIndex",
items=[],
callback=self.pvalThresholdChanged)
self.valuesQLB = QListWidget(self.selValues)
self.valuesQLB.setSelectionMode(QListWidget.MultiSelection)
self.connect(self.valuesQLB, SIGNAL("itemSelectionChanged()"),
self.valuesSelectionChange)
self.selValues.layout().addWidget(self.valuesQLB)
self.unselectAllQLB = OWGUI.button(self.selValues,
self,
"Unselect all",
callback=self.unselAll)
def unselAll(self):
self.valuesQLB.clearSelection()
def pvalThresholdChanged(self):
print self.pvalThresholdIndex
if self.pvalThresholdIndex:
self.pvalThreshold = float(
self.pvalThresholdCombo.text(self.pvalThresholdIndex))
else:
self.pvalThreshold = None
self.calcMotifsGraph()
self.updateMotifsGraph()
def valuesSelectionChange(self):
visibleOutcomes = []
for i in range(self.valuesQLB.count()):
item = self.valuesQLB.item(i)
if item.isSelected():
visibleOutcomes.append(str(item.text()))
self.visibleValues = visibleOutcomes
self.updateMotifsGraph()
def updateSelectionChange(self):
## make new colors only for those colorBy values present in data
colors = ColorPaletteHSV(len(self.valuesPresentInData))
for (i, v) in enumerate(self.valuesPresentInData):
curve = self.valueToCurve[v]
curve.color = colors[i]
self.setValuesNames(self.valuesPresentInData)
for i in range(self.valuesQLB.count()):
item = self.valuesQLB.item(i)
item.setSelected(str(item.text()) in self.visibleValues)
# else:
# self.valuesQLB.setSelected(i, 0)
def colorByChanged(self):
# self.graph.removeCurves()
self.graph.removeDrawingCurves()
self.valueToCurve = {}
if self.colorBy == None:
self.setValuesNames(None)
return
if self.potentialColorVariables:
var = self.potentialColorVariables[self.colorBy]
values = sorted(var.values)
# values.sort()
## generate colors for each colorby value (each color on its own curve)
colors = ColorPaletteHSV(len(values))
for (i, v) in enumerate(values):
## create curve in graph
curve = subBarQwtPlotCurve()
curve.color = colors[i]
curve.attach(self.graph)
# ckey = self.graph.insertCurve(curve)
curve.setStyle(QwtPlotCurve.UserCurve)
self.valueToCurve[v] = curve
self.setValuesNames(values)
self.calcMotifsGraph()
def setValuesNames(self, values):
self.valuesQLB.clear()
if values == None:
return
for v in values:
self.valuesQLB.addItem(
QListWidgetItem(QIcon(ColorPixmap(self.valueToCurve[v].color)),
v))
self.valuesQLB.item(self.valuesQLB.count() - 1).setSelected(True)
## signal processing
def newGeneList(self, list):
self.geneList = []
if list is not None:
self.geneList = list
self.calcMotifsGraph()
self.updateMotifsGraph()
def newMotifList(self, list):
self.motifList = []
if list is not None:
self.motifList = list
self.calcMotifsGraph()
self.updateMotifsGraph()
def cdata(self, data):
self.data = data
self.motifLines = []
self.colorByCombo.clear()
if self.data == None:
self.colorBy = None
self.potentialColorVariables = []
self.colorByChanged()
self.graph.setYLlabels(None)
else:
self.potentialColorVariables = [v for v in self.data.domain.variables + self.data.domain.getmetas().values() \
if v.varType == orange.VarTypes.Discrete]
for var in self.potentialColorVariables:
self.colorByCombo.addItem(str(var.name))
## break motif info according to gene (sequenceID)
self.motifLines = defaultdict(list)
for e in self.data:
geneID = str(e['sequenceID'])
self.motifLines[geneID].append(e)
self.allGenes = sorted(self.motifLines.keys())
if self.potentialColorVariables:
self.colorBy = min(
len(self.potentialColorVariables) - 1, self.colorBy or 0)
else:
self.colorBy = None
self.colorByChanged()
if len(self.potentialColorVariables) > 0:
self.colorByCombo.setCurrentIndex(0)
## update graph
def calcMotifsGraph(self):
graphData = {}
for (colorKey, curve) in self.valueToCurve.iteritems():
graphData[colorKey] = [[], []]
lineCn = 0
yVals = []
self.colorByValuesPresentInData = []
self.valuesPresentInData = []
for lineKey in self.geneList:
## if (self.geneList <> None) and (self.geneList <> []) and (lineKey not in self.geneList): continue
yVals.append(lineKey)
for e in self.motifLines[lineKey]:
motifName = str(e['motifName']) #.value
if self.motifList is not None and self.motifList != [] and motifName not in self.motifList:
continue
motifDistToEnd = -int(e['distToEnd']) #.value)
postProb = int(round(float(e['pvalue']) * 100))
dir = str(e['direction'])
if 1 or (
postProb >= self.clusterPostProbThreshold
): ## and (chiSquare >= self.motifChiSquareThreshold):
colorAttr = self.potentialColorVariables[self.colorBy]
colorKey = str(e[colorAttr])
if colorKey not in self.valuesPresentInData:
self.valuesPresentInData.append(colorKey)
# print motifNumber, colorKey
# set the point x values
graphData[colorKey][0].append(motifDistToEnd)
graphData[colorKey][0].append(motifDistToEnd + 5.0)
# set the point y values
if dir == "1":
graphData[colorKey][1].append(lineCn + 0.0)
graphData[colorKey][1].append(lineCn + 0.30)
elif dir == "-1":
graphData[colorKey][1].append(lineCn - 0.30)
graphData[colorKey][1].append(lineCn + 0.0)
else:
graphData[colorKey][1].append(lineCn - 0.30)
graphData[colorKey][1].append(lineCn + 0.30)
lineCn += 1
vals = reduce(list.__add__, [val[0] for val in graphData.itervalues()],
[])
minX = min(vals or [0]) - 5.0
maxX = max(vals or [0]) + 5.0
self.graph.setYLlabels(yVals)
self.graph.setAxisScale(QwtPlot.yLeft, -0.5, len(yVals) - 0.5, 1)
self.graph.setAxisScale(QwtPlot.xBottom, minX, maxX)
for (colorKey, curve) in self.valueToCurve.iteritems():
curve.setData(graphData[colorKey][0], graphData[colorKey][1])
curve.setVisible(colorKey in self.visibleValues)
self.graph.replot()
self.valuesPresentInData.sort()
self.visibleValues = [v for v in self.valuesPresentInData]
self.updateSelectionChange()
def updateMotifsGraph(self):
for (colorKey, curve) in self.valueToCurve.items():
curve.setVisible(colorKey in self.visibleValues)
self.graph.replot()
def __init__(self,
parent=None,
signalManager=None,
name="Normalize Expression Array"):
OWWidget.__init__(self, parent, signalManager, name, wantGraph=True)
self.inputs = [("Expression array", ExampleTable, self.setData)]
self.outputs = [("Normalized expression array", ExampleTable, Default),
("Filtered expression array", ExampleTable)]
self.selectedGroup = 0
self.selectedCenterMethod = 0
self.selectedMergeMethod = 0
self.zCutoff = 1.96
self.appendZScore = False
self.appendRIValues = False
self.autoCommit = False
self.loadSettings()
## GUI
self.infoBox = OWGUI.widgetLabel(
OWGUI.widgetBox(self.controlArea, "Info", addSpace=True),
"No data on input.")
box = OWGUI.widgetBox(self.controlArea, "Split by", addSpace=True)
self.groupCombo = OWGUI.comboBox(box,
self,
"selectedGroup",
callback=self.onGroupSelection)
self.centerCombo = OWGUI.comboBox(
self.controlArea,
self,
"selectedCenterMethod",
box="Center Fold-change Using",
items=[name for name, _ in self.CENTER_METHODS],
callback=self.onCenterMethodChange,
addSpace=True)
self.mergeCombo = OWGUI.comboBox(
self.controlArea,
self,
"selectedMergeMethod",
box="Merge Replicates",
items=[name for name, _ in self.MERGE_METHODS],
tooltip="Select the method for replicate merging",
callback=self.onMergeMethodChange,
addSpace=True)
box = OWGUI.doubleSpin(self.controlArea,
self,
"zCutoff",
0.0,
3.0,
0.01,
box="Z-Score Cutoff",
callback=[self.replotMA, self.commitIf])
OWGUI.separator(self.controlArea)
box = OWGUI.widgetBox(self.controlArea, "Ouput")
OWGUI.checkBox(box,
self,
"appendZScore",
"Append Z-Scores",
tooltip="Append calculated Z-Scores to output",
callback=self.commitIf)
OWGUI.checkBox(
box,
self,
"appendRIValues",
"Append Log Ratio and Intensity values",
tooltip=
"Append calculated Log Ratio and Intensity values to output data",
callback=self.commitIf)
cb = OWGUI.checkBox(box,
self,
"autoCommit",
"Commit on change",
tooltip="Commit data on any change",
callback=self.commitIf)
b = OWGUI.button(box, self, "Commit", callback=self.commit)
OWGUI.setStopper(self, b, cb, "changedFlag", callback=self.commit)
self.connect(self.graphButton, SIGNAL("clicked()"), self.saveGraph)
OWGUI.rubber(self.controlArea)
self.graph = OWGraph(self.mainArea)
self.graph.setAxisTitle(QwtPlot.xBottom,
"Intensity: log<sub>10</sub>(R*G)")
self.graph.setAxisTitle(QwtPlot.yLeft,
"Log ratio: log<sub>2</sub>(R/G)")
self.graph.showFilledSymbols = True
self.mainArea.layout().addWidget(self.graph)
self.groups = []
self.split_data = None, None
self.merged_splits = None, None
self.centered = None, None
self.changedFlag = False
self.data = None
self.resize(800, 600)
class OWMAPlot(OWWidget):
settingsList = ["appendZScore", "appendRIValues"]
contextHandlers = {
"": DomainContextHandler("", ["selectedGroup", "zCutoff"])
}
CENTER_METHODS = [("Average", obiExpression.MA_center_average),
("Lowess (fast - interpolated)",
obiExpression.MA_center_lowess_fast),
("Lowess", obiExpression.MA_center_lowess)]
MERGE_METHODS = [("Average", numpy.ma.average),
("Median", numpy.ma.median),
("Geometric mean", obiExpression.geometric_mean)]
def __init__(self,
parent=None,
signalManager=None,
name="Normalize Expression Array"):
OWWidget.__init__(self, parent, signalManager, name, wantGraph=True)
self.inputs = [("Expression array", ExampleTable, self.setData)]
self.outputs = [("Normalized expression array", ExampleTable, Default),
("Filtered expression array", ExampleTable)]
self.selectedGroup = 0
self.selectedCenterMethod = 0
self.selectedMergeMethod = 0
self.zCutoff = 1.96
self.appendZScore = False
self.appendRIValues = False
self.autoCommit = False
self.loadSettings()
## GUI
self.infoBox = OWGUI.widgetLabel(
OWGUI.widgetBox(self.controlArea, "Info", addSpace=True),
"No data on input.")
box = OWGUI.widgetBox(self.controlArea, "Split by", addSpace=True)
self.groupCombo = OWGUI.comboBox(box,
self,
"selectedGroup",
callback=self.onGroupSelection)
self.centerCombo = OWGUI.comboBox(
self.controlArea,
self,
"selectedCenterMethod",
box="Center Fold-change Using",
items=[name for name, _ in self.CENTER_METHODS],
callback=self.onCenterMethodChange,
addSpace=True)
self.mergeCombo = OWGUI.comboBox(
self.controlArea,
self,
"selectedMergeMethod",
box="Merge Replicates",
items=[name for name, _ in self.MERGE_METHODS],
tooltip="Select the method for replicate merging",
callback=self.onMergeMethodChange,
addSpace=True)
box = OWGUI.doubleSpin(self.controlArea,
self,
"zCutoff",
0.0,
3.0,
0.01,
box="Z-Score Cutoff",
callback=[self.replotMA, self.commitIf])
OWGUI.separator(self.controlArea)
box = OWGUI.widgetBox(self.controlArea, "Ouput")
OWGUI.checkBox(box,
self,
"appendZScore",
"Append Z-Scores",
tooltip="Append calculated Z-Scores to output",
callback=self.commitIf)
OWGUI.checkBox(
box,
self,
"appendRIValues",
"Append Log Ratio and Intensity values",
tooltip=
"Append calculated Log Ratio and Intensity values to output data",
callback=self.commitIf)
cb = OWGUI.checkBox(box,
self,
"autoCommit",
"Commit on change",
tooltip="Commit data on any change",
callback=self.commitIf)
b = OWGUI.button(box, self, "Commit", callback=self.commit)
OWGUI.setStopper(self, b, cb, "changedFlag", callback=self.commit)
self.connect(self.graphButton, SIGNAL("clicked()"), self.saveGraph)
OWGUI.rubber(self.controlArea)
self.graph = OWGraph(self.mainArea)
self.graph.setAxisTitle(QwtPlot.xBottom,
"Intensity: log<sub>10</sub>(R*G)")
self.graph.setAxisTitle(QwtPlot.yLeft,
"Log ratio: log<sub>2</sub>(R/G)")
self.graph.showFilledSymbols = True
self.mainArea.layout().addWidget(self.graph)
self.groups = []
self.split_data = None, None
self.merged_splits = None, None
self.centered = None, None
self.changedFlag = False
self.data = None
self.resize(800, 600)
def onFinished(self, status):
self.setEnabled(True)
def onUnhandledException(self, ex_info):
self.setEnabled(True)
print >> sys.stderr, "Unhandled exception in non GUI thread"
ex_type, ex_val, tb = ex_info
if ex_type == numpy.linalg.LinAlgError and False:
self.error(0, "Linear algebra error: %s" % repr(ex_val))
else:
sys.excepthook(*ex_info)
def onGroupSelection(self):
if self.data:
self.updateInfoBox()
self.splitData()
self.runNormalization()
def onCenterMethodChange(self):
if self.data:
self.runNormalization()
def onMergeMethodChange(self):
if self.data:
self.splitData()
self.runNormalization()
def proposeGroups(self, data):
col_labels = [
attr.attributes.items() for attr in data.domain.attributes
]
col_labels = sorted(reduce(set.union, col_labels, set()))
col_labels = [(key, value, 1) for key, value in col_labels]
attrs = [attr for attr in data.domain.variables + data.domain.getmetas().values() \
if attr.varType == orange.VarTypes.Discrete]
row_labels = [(attr.name, value, 0) for attr in attrs
for value in attr.values]
def filterSingleValues(labels):
ret = []
for name, value, axis in labels:
match = [(n, v, a) for n, v, a in labels if n == name]
if len(match) > 1:
ret.append((name, value, axis))
return ret
col_labels = filterSingleValues(col_labels)
row_labels = filterSingleValues(row_labels)
return col_labels + row_labels
def setData(self, data):
self.closeContext("")
self.data = data
self.error([0, 1])
if data is not None:
self.infoBox.setText("%i genes on input" % len(data))
self.groups = self.proposeGroups(data)
self.groupCombo.clear()
self.groupCombo.addItems(
["%s: %s" % (key, value) for key, value, axis in self.groups])
if not self.groups:
self.error(
1,
"Input data has no class attribute or attribute labels!")
self.clear()
return
self.openContext("", data)
self.selectedGroup = min(self.selectedGroup, len(self.groups) - 1)
self.updateInfoBox()
self.splitData()
self.runNormalization()
else:
self.clear()
def clear(self):
self.groups = []
self.data = None
self.centered = None, None
self.split_data = None, None
self.merged_splits = None, None
self.graph.removeDrawingCurves()
self.infoBox.setText("No data on input")
self.send("Normalized expression array", None)
self.send("Filtered expression array", None)
def updateInfoBox(self):
genes = self.getGeneNames()
self.infoBox.setText("%i genes on input" % len(self.data))
def getSelectedGroup(self):
return self.groups[self.selectedGroup]
def getSelectedGroupSplit(self):
key, value, axis = self.getSelectedGroup()
other_values = [
v for k, v, a in self.groups
if k == key and a == axis and v != value
]
return [(key, value), (key, other_values)], axis
def getGeneNames(self):
key, value, axis = self.getSelectedGroup()
if axis == 0:
genes = [str(ex[key]) for ex in self.data]
else:
genes = [attr.name for attr in self.data.domain.attributes]
return genes
def splitData(self):
groups, axis = self.getSelectedGroupSplit()
self.split_ind = [
obiExpression.select_indices(self.data, key, value, axis)
for key, value in groups
]
self.split_data = obiExpression.split_data(self.data, groups, axis)
def getMerged(self):
split1, split2 = self.split_data
(array1, _, _), (array2, _, _) = split1.toNumpyMA(), split2.toNumpyMA()
_, _, axis = self.getSelectedGroup()
merge_function = self.MERGE_METHODS[self.selectedMergeMethod][1]
merged1 = obiExpression.merge_replicates(array1,
axis,
merge_function=merge_function)
merged2 = obiExpression.merge_replicates(array2,
axis,
merge_function=merge_function)
self.merged_splits = merged1, merged2
return self.merged_splits
def runNormalization(self):
self.progressBarInit()
self.progressBarSet(0.0)
G, R = self.getMerged()
self.progressBarSet(5.0)
center_method = self.CENTER_METHODS[self.selectedCenterMethod][1]
# TODO: progess bar , lowess can take a long time
if self.selectedCenterMethod in [1, 2]: #Lowess
Gc, Rc = center_method(G,
R,
f=1. / min(500.,
len(G) / 100),
iter=1)
else:
Gc, Rc = center_method(G, R)
self.progressBarSet(70.0)
self.centered = Gc, Rc
self.z_scores = obiExpression.MA_zscore(Gc, Rc, 1. / 3.)
self.progressBarSet(100.0)
self.plotMA(Gc, Rc, self.z_scores, self.zCutoff)
self.progressBarFinished()
def runNormalizationAsync(self):
""" Run MA centering and z_score estimation in a separate thread
"""
self.error(0)
self.progressBarInit()
self.progressBarSet(0.0)
G, R = self.getMerged()
# self.progressBarSet(5.0)
center_method = self.CENTER_METHODS[self.selectedCenterMethod][1]
use_lowess = self.selectedCenterMethod in [1, 2]
def run(progressCallback=lambda value: None
): # the function to run in a thread
# progressCallback(5.0)
if use_lowess:
Gc, Rc = center_method(
G,
R,
f=2. / 3.,
iter=1,
progressCallback=lambda val: progressCallback(val / 2))
else:
Gc, Rc = center_method(G, R)
progressCallback(50)
z_scores = obiExpression.MA_zscore(
Gc,
Rc,
1. / 3.,
progressCallback=lambda val: progressCallback(50 + val / 2))
return Gc, Rc, z_scores
self.progressDiscard = ProgressBarDiscard(self, self)
async = self.asyncCall(run,
name="Normalization",
onResult=self.onResults,
onError=self.onUnhandledException)
self.connect(async, SIGNAL("progressChanged(float)"),
self.progressDiscard.progressBarSet, Qt.QueuedConnection)
self.setEnabled(False)
async .__call__(progressCallback=async .emitProgressChanged)
## comment out this line if threading creates any problems
runNormalization = runNormalizationAsync
def onResults(self, (Gc, Rc, z_scores)):
""" Handle the results of centering and z-scoring
"""
assert (QThread.currentThread() is self.thread())
self.setEnabled(True)
qApp.processEvents()
self.progressBarFinished()
self.centered = Gc, Rc
self.z_scores = z_scores
self.plotMA(Gc, Rc, z_scores, self.zCutoff)
self.commit()
class OWDisplayMotifs(OWWidget):
settingsList = []
def __init__(self,parent=None, signalManager = None):
OWWidget.__init__(self, parent, signalManager, "&Display Motifs", 0)
# set default settings
self.colorBy = None
self.pvalThresholdIndex = None
self.pvalThreshold = None
#load settings
self.loadSettings()
# GUI
self.graph = OWGraph(self.mainArea)
self.graph.setYRlabels(None)
self.graph.enableGridXB(0)
self.graph.enableGridYL(1)
self.graph.setAxisMaxMinor(QwtPlot.xBottom, 10)
self.graph.setAxisMaxMajor(QwtPlot.xBottom, 10)
self.graph.setAxisAutoScale(QwtPlot.xBottom)
self.graph.setAxisScale(QwtPlot.xBottom, -1020, 0, 0)
self.mainArea.layout().addWidget(self.graph)
# inputs
# data and graph temp variables
self.inputs = [("Examples", ExampleTable, self.cdata, Default), ("Genes", list, self.newGeneList, Default), ("Motifs", list, self.newMotifList, Default)]
self.data = None
self.motifLines = []
self.visibleValues = []
self.valueToCurve = {}
self.allGenes = [] ## genes displayed always in same order
self.geneList = [] ## selected genes
self.motifList = [] ## selected motifs
self.valuesPresentInData = []
self.clusterPostProbThreshold = 0
# GUI
self.selValues = OWGUI.widgetBox(self.controlArea, "Values")
self.selcolorBy = OWGUI.widgetBox(self.controlArea, "Color By")
self.colorByCombo = OWGUI.comboBox(self.selcolorBy, self, "colorBy",
items=[],
callback=self.colorByChanged)
self.pvalThresholdCombo = OWGUI.comboBox(self.selValues, self, "pvalThresholdIndex",
items=[],
callback=self.pvalThresholdChanged)
self.valuesQLB = QListWidget(self.selValues)
self.valuesQLB.setSelectionMode(QListWidget.MultiSelection)
self.connect(self.valuesQLB, SIGNAL("itemSelectionChanged()"), self.valuesSelectionChange)
self.selValues.layout().addWidget(self.valuesQLB)
self.unselectAllQLB = OWGUI.button(self.selValues, self, "Unselect all",
callback = self.unselAll)
def unselAll(self):
self.valuesQLB.clearSelection()
def pvalThresholdChanged(self):
print self.pvalThresholdIndex
if self.pvalThresholdIndex:
self.pvalThreshold = float(self.pvalThresholdCombo.text(self.pvalThresholdIndex))
else:
self.pvalThreshold = None
self.calcMotifsGraph()
self.updateMotifsGraph()
def valuesSelectionChange(self):
visibleOutcomes = []
for i in range(self.valuesQLB.count()):
item = self.valuesQLB.item(i)
if item.isSelected():
visibleOutcomes.append(str(item.text()))
self.visibleValues = visibleOutcomes
self.updateMotifsGraph()
def updateSelectionChange(self):
## make new colors only for those colorBy values present in data
colors = ColorPaletteHSV(len(self.valuesPresentInData))
for (i, v) in enumerate(self.valuesPresentInData):
curve = self.valueToCurve[v]
curve.color = colors[i]
self.setValuesNames(self.valuesPresentInData)
for i in range(self.valuesQLB.count()):
item = self.valuesQLB.item(i)
item.setSelected(str(item.text()) in self.visibleValues)
# else:
# self.valuesQLB.setSelected(i, 0)
def colorByChanged(self):
# self.graph.removeCurves()
self.graph.removeDrawingCurves()
self.valueToCurve = {}
if self.colorBy == None:
self.setValuesNames(None)
return
if self.potentialColorVariables:
var = self.potentialColorVariables[self.colorBy]
values = sorted(var.values)
# values.sort()
## generate colors for each colorby value (each color on its own curve)
colors = ColorPaletteHSV(len(values))
for (i, v) in enumerate(values):
## create curve in graph
curve = subBarQwtPlotCurve()
curve.color = colors[i]
curve.attach(self.graph)
# ckey = self.graph.insertCurve(curve)
curve.setStyle(QwtPlotCurve.UserCurve)
self.valueToCurve[v] = curve
self.setValuesNames(values)
self.calcMotifsGraph()
def setValuesNames(self, values):
self.valuesQLB.clear()
if values == None:
return
for v in values:
self.valuesQLB.addItem(QListWidgetItem(QIcon(ColorPixmap(self.valueToCurve[v].color)), v))
self.valuesQLB.item(self.valuesQLB.count() - 1).setSelected(True)
## signal processing
def newGeneList(self, list):
self.geneList = []
if list is not None:
self.geneList = list
self.calcMotifsGraph()
self.updateMotifsGraph()
def newMotifList(self, list):
self.motifList = []
if list is not None:
self.motifList = list
self.calcMotifsGraph()
self.updateMotifsGraph()
def cdata(self, data):
self.data = data
self.motifLines = []
self.colorByCombo.clear()
if self.data == None:
self.colorBy = None
self.potentialColorVariables = []
self.colorByChanged()
self.graph.setYLlabels(None)
else:
self.potentialColorVariables = [v for v in self.data.domain.variables + self.data.domain.getmetas().values() \
if v.varType == orange.VarTypes.Discrete]
for var in self.potentialColorVariables:
self.colorByCombo.addItem(str(var.name))
## break motif info according to gene (sequenceID)
self.motifLines = defaultdict(list)
for e in self.data:
geneID = str(e['sequenceID'])
self.motifLines[geneID].append(e)
self.allGenes = sorted(self.motifLines.keys())
if self.potentialColorVariables:
self.colorBy = min(len(self.potentialColorVariables) - 1, self.colorBy or 0)
else:
self.colorBy = None
self.colorByChanged()
if len(self.potentialColorVariables) > 0:
self.colorByCombo.setCurrentIndex(0)
## update graph
def calcMotifsGraph(self):
graphData = {}
for (colorKey, curve) in self.valueToCurve.iteritems():
graphData[colorKey] = [[], []]
lineCn = 0
yVals = []
self.colorByValuesPresentInData = []
self.valuesPresentInData = []
for lineKey in self.geneList:
## if (self.geneList <> None) and (self.geneList <> []) and (lineKey not in self.geneList): continue
yVals.append( lineKey)
for e in self.motifLines[lineKey]:
motifName = str(e['motifName'])#.value
if self.motifList is not None and self.motifList != [] and motifName not in self.motifList:
continue
motifDistToEnd = -int(e['distToEnd']) #.value)
postProb = int(round(float(e['pvalue']) * 100))
dir = str(e['direction'])
if 1 or (postProb >= self.clusterPostProbThreshold): ## and (chiSquare >= self.motifChiSquareThreshold):
colorAttr = self.potentialColorVariables[self.colorBy]
colorKey = str(e[colorAttr])
if colorKey not in self.valuesPresentInData:
self.valuesPresentInData.append(colorKey)
# print motifNumber, colorKey
# set the point x values
graphData[colorKey][0].append(motifDistToEnd)
graphData[colorKey][0].append(motifDistToEnd + 5.0)
# set the point y values
if dir == "1":
graphData[colorKey][1].append(lineCn + 0.0)
graphData[colorKey][1].append(lineCn + 0.30)
elif dir == "-1":
graphData[colorKey][1].append(lineCn - 0.30)
graphData[colorKey][1].append(lineCn + 0.0)
else:
graphData[colorKey][1].append(lineCn - 0.30)
graphData[colorKey][1].append(lineCn + 0.30)
lineCn += 1
vals = reduce(list.__add__, [val[0] for val in graphData.itervalues()], [])
minX = min(vals or [0]) - 5.0
maxX = max(vals or [0]) + 5.0
self.graph.setYLlabels(yVals)
self.graph.setAxisScale(QwtPlot.yLeft, -0.5, len(yVals) - 0.5, 1)
self.graph.setAxisScale(QwtPlot.xBottom, minX, maxX)
for (colorKey, curve) in self.valueToCurve.iteritems():
curve.setData(graphData[colorKey][0], graphData[colorKey][1])
curve.setVisible(colorKey in self.visibleValues)
self.graph.replot()
self.valuesPresentInData.sort()
self.visibleValues = [v for v in self.valuesPresentInData]
self.updateSelectionChange()
def updateMotifsGraph(self):
for (colorKey, curve) in self.valueToCurve.items():
curve.setVisible(colorKey in self.visibleValues)
self.graph.replot()
def __init__(self, parent=None, signalManager=None, name="Normalize Expression Array"):
OWWidget.__init__(self, parent, signalManager, name, wantGraph=True)
self.inputs = [("Expression array", ExampleTable, self.setData)]
self.outputs = [("Normalized expression array", ExampleTable, Default), ("Filtered expression array", ExampleTable)]
self.selectedGroup = 0
self.selectedCenterMethod = 0
self.selectedMergeMethod = 0
self.zCutoff = 1.96
self.appendZScore = False
self.appendRIValues = False
self.autoCommit = False
self.loadSettings()
## GUI
self.infoBox = OWGUI.widgetLabel(OWGUI.widgetBox(self.controlArea, "Info", addSpace=True),
"No data on input.")
box = OWGUI.widgetBox(self.controlArea, "Split by", addSpace=True)
self.groupCombo = OWGUI.comboBox(box, self, "selectedGroup",
callback=self.onGroupSelection
)
self.centerCombo = OWGUI.comboBox(self.controlArea, self, "selectedCenterMethod",
box="Center Fold-change Using",
items=[name for name, _ in self.CENTER_METHODS],
callback=self.onCenterMethodChange,
addSpace=True
)
self.mergeCombo = OWGUI.comboBox(self.controlArea, self, "selectedMergeMethod",
box="Merge Replicates",
items=[name for name, _ in self.MERGE_METHODS],
tooltip="Select the method for replicate merging",
callback=self.onMergeMethodChange,
addSpace=True
)
box = OWGUI.doubleSpin(self.controlArea, self, "zCutoff", 0.0, 3.0, 0.01,
box="Z-Score Cutoff",
callback=[self.replotMA, self.commitIf])
OWGUI.separator(self.controlArea)
box = OWGUI.widgetBox(self.controlArea, "Ouput")
OWGUI.checkBox(box, self, "appendZScore", "Append Z-Scores",
tooltip="Append calculated Z-Scores to output",
callback=self.commitIf
)
OWGUI.checkBox(box, self, "appendRIValues", "Append Log Ratio and Intensity values",
tooltip="Append calculated Log Ratio and Intensity values to output data",
callback=self.commitIf
)
cb = OWGUI.checkBox(box, self, "autoCommit", "Commit on change",
tooltip="Commit data on any change",
callback=self.commitIf
)
b = OWGUI.button(box, self, "Commit", callback=self.commit)
OWGUI.setStopper(self, b, cb, "changedFlag", callback=self.commit)
self.connect(self.graphButton, SIGNAL("clicked()"), self.saveGraph)
OWGUI.rubber(self.controlArea)
self.graph = OWGraph(self.mainArea)
self.graph.setAxisTitle(QwtPlot.xBottom, "Intensity: log<sub>10</sub>(R*G)")
self.graph.setAxisTitle(QwtPlot.yLeft, "Log ratio: log<sub>2</sub>(R/G)")
self.graph.showFilledSymbols = True
self.mainArea.layout().addWidget(self.graph)
self.groups = []
self.split_data = None, None
self.merged_splits = None, None
self.centered = None, None
self.changedFlag = False
self.data = None
self.resize(800, 600)
class OWMAPlot(OWWidget):
settingsList = ["appendZScore", "appendRIValues"]
contextHandlers = {"": DomainContextHandler("", ["selectedGroup", "zCutoff"])}
CENTER_METHODS = [("Average", obiExpression.MA_center_average),
("Lowess (fast - interpolated)", obiExpression.MA_center_lowess_fast),
("Lowess", obiExpression.MA_center_lowess)]
MERGE_METHODS = [("Average", numpy.ma.average),
("Median", numpy.ma.median),
("Geometric mean", obiExpression.geometric_mean)]
def __init__(self, parent=None, signalManager=None, name="Normalize Expression Array"):
OWWidget.__init__(self, parent, signalManager, name, wantGraph=True)
self.inputs = [("Expression array", ExampleTable, self.setData)]
self.outputs = [("Normalized expression array", ExampleTable, Default), ("Filtered expression array", ExampleTable)]
self.selectedGroup = 0
self.selectedCenterMethod = 0
self.selectedMergeMethod = 0
self.zCutoff = 1.96
self.appendZScore = False
self.appendRIValues = False
self.autoCommit = False
self.loadSettings()
## GUI
self.infoBox = OWGUI.widgetLabel(OWGUI.widgetBox(self.controlArea, "Info", addSpace=True),
"No data on input.")
box = OWGUI.widgetBox(self.controlArea, "Split by", addSpace=True)
self.groupCombo = OWGUI.comboBox(box, self, "selectedGroup",
callback=self.onGroupSelection
)
self.centerCombo = OWGUI.comboBox(self.controlArea, self, "selectedCenterMethod",
box="Center Fold-change Using",
items=[name for name, _ in self.CENTER_METHODS],
callback=self.onCenterMethodChange,
addSpace=True
)
self.mergeCombo = OWGUI.comboBox(self.controlArea, self, "selectedMergeMethod",
box="Merge Replicates",
items=[name for name, _ in self.MERGE_METHODS],
tooltip="Select the method for replicate merging",
callback=self.onMergeMethodChange,
addSpace=True
)
box = OWGUI.doubleSpin(self.controlArea, self, "zCutoff", 0.0, 3.0, 0.01,
box="Z-Score Cutoff",
callback=[self.replotMA, self.commitIf])
OWGUI.separator(self.controlArea)
box = OWGUI.widgetBox(self.controlArea, "Ouput")
OWGUI.checkBox(box, self, "appendZScore", "Append Z-Scores",
tooltip="Append calculated Z-Scores to output",
callback=self.commitIf
)
OWGUI.checkBox(box, self, "appendRIValues", "Append Log Ratio and Intensity values",
tooltip="Append calculated Log Ratio and Intensity values to output data",
callback=self.commitIf
)
cb = OWGUI.checkBox(box, self, "autoCommit", "Commit on change",
tooltip="Commit data on any change",
callback=self.commitIf
)
b = OWGUI.button(box, self, "Commit", callback=self.commit)
OWGUI.setStopper(self, b, cb, "changedFlag", callback=self.commit)
self.connect(self.graphButton, SIGNAL("clicked()"), self.saveGraph)
OWGUI.rubber(self.controlArea)
self.graph = OWGraph(self.mainArea)
self.graph.setAxisTitle(QwtPlot.xBottom, "Intensity: log<sub>10</sub>(R*G)")
self.graph.setAxisTitle(QwtPlot.yLeft, "Log ratio: log<sub>2</sub>(R/G)")
self.graph.showFilledSymbols = True
self.mainArea.layout().addWidget(self.graph)
self.groups = []
self.split_data = None, None
self.merged_splits = None, None
self.centered = None, None
self.changedFlag = False
self.data = None
self.resize(800, 600)
def onFinished(self, status):
self.setEnabled(True)
def onUnhandledException(self, ex_info):
self.setEnabled(True)
print >> sys.stderr, "Unhandled exception in non GUI thread"
ex_type, ex_val, tb = ex_info
if ex_type == numpy.linalg.LinAlgError and False:
self.error(0, "Linear algebra error: %s" % repr(ex_val))
else:
sys.excepthook(*ex_info)
def onGroupSelection(self):
if self.data:
self.updateInfoBox()
self.splitData()
self.runNormalization()
def onCenterMethodChange(self):
if self.data:
self.runNormalization()
def onMergeMethodChange(self):
if self.data:
self.splitData()
self.runNormalization()
def proposeGroups(self, data):
col_labels = [attr.attributes.items() for attr in data.domain.attributes]
col_labels = sorted(reduce(set.union, col_labels, set()))
col_labels = [(key, value, 1) for key, value in col_labels]
attrs = [attr for attr in data.domain.variables + data.domain.getmetas().values() \
if attr.varType == orange.VarTypes.Discrete]
row_labels = [(attr.name, value, 0) for attr in attrs for value in attr.values]
def filterSingleValues(labels):
ret = []
for name, value, axis in labels:
match = [(n, v, a) for n, v, a in labels if n == name]
if len(match) > 1:
ret.append((name, value, axis))
return ret
col_labels = filterSingleValues(col_labels)
row_labels = filterSingleValues(row_labels)
return col_labels + row_labels
def setData(self, data):
self.closeContext("")
self.data = data
self.error([0 ,1])
if data is not None:
self.infoBox.setText("%i genes on input" % len(data))
self.groups = self.proposeGroups(data)
self.groupCombo.clear()
self.groupCombo.addItems(["%s: %s" % (key, value) for key, value, axis in self.groups])
if not self.groups:
self.error(1, "Input data has no class attribute or attribute labels!")
self.clear()
return
self.openContext("", data)
self.selectedGroup = min(self.selectedGroup, len(self.groups) - 1)
self.updateInfoBox()
self.splitData()
self.runNormalization()
else:
self.clear()
def clear(self):
self.groups = []
self.data = None
self.centered = None, None
self.split_data = None, None
self.merged_splits = None, None
self.graph.removeDrawingCurves()
self.infoBox.setText("No data on input")
self.send("Normalized expression array", None)
self.send("Filtered expression array", None)
def updateInfoBox(self):
genes = self.getGeneNames()
self.infoBox.setText("%i genes on input" % len(self.data))
def getSelectedGroup(self):
return self.groups[self.selectedGroup]
def getSelectedGroupSplit(self):
key, value, axis = self.getSelectedGroup()
other_values = [v for k, v, a in self.groups if k == key and a == axis and v != value]
return [(key, value), (key, other_values)], axis
def getGeneNames(self):
key, value, axis = self.getSelectedGroup()
if axis == 0:
genes = [str(ex[key]) for ex in self.data]
else:
genes = [attr.name for attr in self.data.domain.attributes]
return genes
def splitData(self):
groups, axis = self.getSelectedGroupSplit()
self.split_ind = [obiExpression.select_indices(self.data, key, value, axis) for key, value in groups]
self.split_data = obiExpression.split_data(self.data, groups, axis)
def getMerged(self):
split1, split2 = self.split_data
(array1, _, _), (array2, _, _) = split1.toNumpyMA(), split2.toNumpyMA()
_, _, axis = self.getSelectedGroup()
merge_function = self.MERGE_METHODS[self.selectedMergeMethod][1]
merged1 = obiExpression.merge_replicates(array1, axis, merge_function=merge_function)
merged2 = obiExpression.merge_replicates(array2, axis, merge_function=merge_function)
self.merged_splits = merged1, merged2
return self.merged_splits
def runNormalization(self):
self.progressBarInit()
self.progressBarSet(0.0)
G, R = self.getMerged()
self.progressBarSet(5.0)
center_method = self.CENTER_METHODS[self.selectedCenterMethod][1]
# TODO: progess bar , lowess can take a long time
if self.selectedCenterMethod in [1, 2]: #Lowess
Gc, Rc = center_method(G, R, f = 1./min(500., len(G)/100), iter=1)
else:
Gc, Rc = center_method(G, R)
self.progressBarSet(70.0)
self.centered = Gc, Rc
self.z_scores = obiExpression.MA_zscore(Gc, Rc, 1./3.)
self.progressBarSet(100.0)
self.plotMA(Gc, Rc, self.z_scores, self.zCutoff)
self.progressBarFinished()
def runNormalizationAsync(self):
""" Run MA centering and z_score estimation in a separate thread
"""
self.error(0)
self.progressBarInit()
self.progressBarSet(0.0)
G, R = self.getMerged()
# self.progressBarSet(5.0)
center_method = self.CENTER_METHODS[self.selectedCenterMethod][1]
use_lowess = self.selectedCenterMethod in [1, 2]
def run(progressCallback = lambda value: None): # the function to run in a thread
# progressCallback(5.0)
if use_lowess:
Gc, Rc = center_method(G, R, f=2./3., iter=1, progressCallback=lambda val: progressCallback(val/2))
else:
Gc, Rc = center_method(G, R)
progressCallback(50)
z_scores = obiExpression.MA_zscore(Gc, Rc, 1./3., progressCallback= lambda val: progressCallback(50 + val/2))
return Gc, Rc, z_scores
self.progressDiscard = ProgressBarDiscard(self, self)
async = self.asyncCall(run, name="Normalization",
onResult=self.onResults,
onError=self.onUnhandledException)
self.connect(async, SIGNAL("progressChanged(float)"), self.progressDiscard.progressBarSet, Qt.QueuedConnection)
self.setEnabled(False)
async.__call__(progressCallback=async.emitProgressChanged)
## comment out this line if threading creates any problems
runNormalization = runNormalizationAsync
def onResults(self, (Gc, Rc, z_scores)):
""" Handle the results of centering and z-scoring
"""
assert(QThread.currentThread() is self.thread())
self.setEnabled(True)
qApp.processEvents()
self.progressBarFinished()
self.centered = Gc, Rc
self.z_scores = z_scores
self.plotMA(Gc, Rc, z_scores, self.zCutoff)
self.commit()
