def execute(choices, galaxyFn=None, username=''):
gsuite = getGSuiteFromGalaxyTN(choices.gsuite)
bedRegions = choices.bedRegions
rp = RP(gsuite)
bedData = rp.openBedFile(bedRegions)
chrOrder, chrLength = rp.sortChrDict()
dataDict, dataDictLine, elementOrder, listResCopy, newDictRegions = rp.countMutations(
chrLength, bedData)
vg = visualizationGraphs()
tName = gsuite.allTrackTitles()
uniformDictList = OrderedDict() # expected values
observedDictList = OrderedDict() # observed values
seriesNameRegionUDL = OrderedDict()
seriesNameRegionODL = OrderedDict()
seriesNameRegion = OrderedDict()
GenerateDistributionOfPointsOfInterestTool.countRegionsForDistribution(
newDictRegions, observedDictList, rp, seriesNameRegion,
seriesNameRegionODL, seriesNameRegionUDL, tName, uniformDictList)
res = ''
for elK in uniformDictList.keys():
res += GenerateDistributionOfPointsOfInterestTool.drawDistribution(
elK, observedDictList, seriesNameRegion, seriesNameRegionODL,
seriesNameRegionUDL, uniformDictList, vg)
htmlCore = HtmlCore()
htmlCore.begin()
htmlCore.line(res)
htmlCore.end()
htmlCore.hideToggle(styleClass='debug')
print htmlCore
def visualizeResults(self, results):
globalResult = results.getGlobalResult()
res = OrderedDict([(x, globalResult[x]) for x in globalResult
if x not in ['Assembly_gap_coverage']])
dT = dataTransformer(res)
seriesName, categories, data = dT.changeDictIntoList()
vg = visualizationGraphs()
return vg.drawPieChart(data, seriesName=categories)
def visualizeResults(self, results):
globalResult = results.getGlobalResult()
res = OrderedDict([(x, globalResult[x]) for x in globalResult
if x not in ['Assembly_gap_coverage', 'Inclusions']
])
dT = dataTransformer(res)
seriesName, categories, data = dT.changeDictIntoListsByLevel()
vg = visualizationGraphs()
res = vg.drawColumnCharts(data, categories=categories)
return vg.visualizeResults(res)
def visualizeResults(self, results):
globalResult = results.getGlobalResult()
res = OrderedDict([(x, globalResult[x]) for x in globalResult
if x not in ['Assembly_gap_coverage', 'BinSize']])
dT = dataTransformer(res)
seriesName, categories, data = dT.changeDictIntoListByTrackString(
numStart=0, numEnd=len(res))
vg = visualizationGraphs()
res = vg.drawColumnChart(data, categories=categories)
return vg.visualizeResults(res)
def getInteractiveColumnChart(cls, distances, distCase, htmlCore):
htmlCore.divider()
htmlCore.header('Interactive distance plot')
htmlCore.line('To see the exact distance for the different points ' + distCase +
' tracks, hover over the bars of interest.')
htmlCore.divEnd() # End div set in execute to remove font settings
vg = visualizationGraphs()
lines = vg.drawColumnChart(
dataY=distances,
titleText='Smallest distances for all points ' + distCase + ' tracks',
yAxisTitle='Distances'
)
htmlCore.line(lines)
def visualizeResults(self, results):
globalResult = results.getGlobalResult()
res = OrderedDict([(x, globalResult[x]) for x in globalResult
if x not in ['Assembly_gap_coverage']])
dT = dataTransformer(res)
seriesName, categories, data = dT.changeDictIntoListsByNumber(
math.sqrt(len(res)))
vg = visualizationGraphs()
return vg.drawPieCharts(
data,
seriesName=categories,
addOptions='width: 50%; float:left; margin: 0 auto')
def execute(cls, choices, galaxyFn=None, username=''):
#gsuite
gsuite = getGSuiteFromGalaxyTN(choices.gsuite)
#all boxes
multiPlot = choices.multiPlot
#scale = choices.scale
#overlap = choices.overlap
overlap = 'no'
bps = int(choices.bps)
rp = RP(gsuite)
#get length of chromosomes and ordering
chrItems = GenomeInfo.getStdChrLengthDict(gsuite.genome)
chrOrder, chrLength = GenerateRainfallPlotTool.sortChrDict(chrItems)
dataDict, dataDictLine, elementOrder, listResCopy, listDataCountPerBin, newResBinSizeListSum, chrList = GenerateRainfallPlotTool.countMutations(
gsuite, chrLength, bps)
seriesType, newSeriesNameRes, newSeriesNameResOE, yAxisMultiVal = rp.getOptionsForPlot(
elementOrder, gsuite.allTrackTitles())
newResList, newResBinSizeList, newResBinSizeListSortedList = rp.generateBinSizeList(
elementOrder, listResCopy, listDataCountPerBin,
newResBinSizeListSum)
vg = visualizationGraphs()
res = ''
if multiPlot == 'Single':
res += GenerateRainfallPlotTool.drawSinglePlot(
vg, newResBinSizeListSortedList, chrLength, newResList,
newSeriesNameRes, newResBinSizeList, overlap, seriesType,
yAxisMultiVal)
else:
res += GenerateRainfallPlotTool.drawMultiPlot(
newResList, newSeriesNameRes, newResBinSizeList, vg,
seriesType, yAxisMultiVal)
htmlCore = HtmlCore()
htmlCore.begin()
htmlCore.line('Bin size: ' + str(bps))
htmlCore.line(res)
htmlCore.end()
htmlCore.hideToggle(styleClass='debug')
print htmlCore
def getInteractiveColumnChartWithLabels(cls, data, labels, htmlCore):
htmlCore.divider()
htmlCore.header('Interactive SNP frequency plot')
htmlCore.line('To see exact SNP counts for the different tracks, hover over the bars of interest.')
htmlCore.divEnd() # End div set in execute to remove font settings
vg = visualizationGraphs()
lines = vg.drawColumnChart(
dataY=data,
titleText='SNP frequencies in tracks',
yAxisTitle='SNP count',
categories=labels,
xAxisRotation=90
)
htmlCore.line(lines)
def visualizeResults(self, results):
globalResult = results.getGlobalResult()
res = OrderedDict([(x, globalResult[x]) for x in globalResult
if x not in ['Assembly_gap_coverage', 'BinSize']])
dT = dataTransformer(res)
seriesName, categories, data = dT.changeDictIntoListsByTrackString(
strNum="T", numStart=1, numEnd=int(math.sqrt(len(res) / 2)))
vg = visualizationGraphs()
res = vg.drawColumnCharts(
data,
categories=categories,
seriesName=seriesName,
addOptions='width: 50%; float:left; margin: 0 auto')
return res
def drawPlot(results, additionalResultsDict, title, columnInd=0):
dictIt = OrderedDict()
dictIt[title] = []
categoriesPart = []
for key0, it0 in results.iteritems():
dictIt[title].append(it0)
categoriesPart.append(key0)
for elC in categoriesPart:
if additionalResultsDict[elC]:
for key1, it1 in additionalResultsDict[elC].iteritems():
if key1 not in dictIt:
dictIt[key1] = []
dictIt[key1].append(it1)
plotName = dictIt.keys()
res = [it[1] for it in dictIt.items()]
categories = []
for i in range(0, len(res)):
categories.append(categoriesPart)
# table1 = generateHistogram('elementCount', ['Track', 'Histogram'], tableData1, plotType='columnChart')
from quick.webtools.restricted.visualization.visualizationGraphs import visualizationGraphs
vg = visualizationGraphs()
res = vg.drawColumnCharts(
res,
titleText=plotName,
categories=categories,
height=500,
xAxisRotation=270,
xAxisTitle='Track title',
yAxisTitle='',
marginTop=30,
addTable=True,
sortableAccordingToTableIndexWithTrackTitle=1 + int(columnInd),
sortableAccordingToTable=True,
plotOptions=True,
legend=False
)
return res
def visualizeResults(self, results):
globalResult = results.getGlobalResult()
res = OrderedDict([(x, globalResult[x]) for x in globalResult
if x not in ['Assembly_gap_coverage']])
dT = dataTransformer(res)
seriesName, categories, data = dT.changeDictIntoList()
vg = visualizationGraphs()
res = vg.drawColumnChart(data,
categories=categories,
extraScriptButton=[
OrderedDict({
'Use linear scale':
'linear',
'Use log10 scale':
'logarithmic'
}), 'yAxisType'
])
return vg.visualizeResults(res)
def execute(choices, galaxyFn=None, username=''):
file = choices.file
fileHeader = choices.fileHeader
title = choices.title
columnX = choices.columnX
columnY = choices.columnY
plot = choices.plot
plotSeries = choices.plotSeries
columnSorted = choices.columnSorted
columnFiltered = choices.columnFiltered
i = 0
with open(ExternalTrackManager.extractFnFromGalaxyTN(file.split(':')),
'r') as f:
dataX = []
for x in f.readlines():
if i == 0 and fileHeader == 'Yes':
pass
else:
el = x.strip('\n').split('\t')
nr = 0
l = []
for e in el:
if e != '':
try:
l.append(float(e))
except:
l.append(e)
nr += 1
dataX.append(l)
i += 1
f.closed
oryginalList = PlotLevelGSuite.returnList(columnX)
columnX = PlotLevelGSuite.returnList(columnX, True)
columnY = PlotLevelGSuite.returnList(columnY, True)
title = PlotLevelGSuite.returnList(title, True)
columnSortedList = columnSorted.strip(' ').split(',')
columnFiltered = columnFiltered.strip(' ').split(',')
for cNum in range(0, len(columnSortedList)):
columnSortedList[cNum] = int(columnSortedList[cNum])
dataX = sorted(dataX,
key=operator.itemgetter(*columnSortedList),
reverse=False)
#dataX = sorted(dataX, key=operator.itemgetter(3,4,0,1,2), reverse=False)
#prepare data for plotting
final = OrderedDict()
for dNum in range(0, len(dataX)):
columnFilteredList = ''
for eNum in columnFiltered:
columnFilteredList += str(dataX[dNum][int(eNum)]) + '-'
if not columnFilteredList in final:
final[columnFilteredList] = OrderedDict()
final[columnFilteredList]['title'] = ''
tit = ''
j = 0
for eNum in title:
if j < len(title) - 1:
tit += str(dataX[dNum][eNum]) + ' '
else:
tit += str(dataX[dNum][eNum])
j += 1
final[columnFilteredList]['title'] = tit
final[columnFilteredList]['categories'] = []
final[columnFilteredList]['data'] = OrderedDict()
cat = ''
j = 0
for eNum in columnX:
if j < len(columnX) - 1:
cat += str(dataX[dNum][eNum]) + ' '
else:
cat += str(dataX[dNum][eNum])
j += 1
final[columnFilteredList]['categories'].append(cat)
for eNum in columnY:
if not eNum in final[columnFilteredList]['data']:
final[columnFilteredList]['data'][eNum] = []
final[columnFilteredList]['data'][eNum].append(
dataX[dNum][eNum])
seriesName = []
data = []
categories = []
d = []
cat = []
title = []
plotLinesName = []
plotLines = []
pl = []
i = 0
for k1, v1 in final.iteritems():
# d=[]
for k2, v2 in v1['data'].iteritems():
# d.append(v2)
if plot == 'Single':
data += v2
seriesName.append([oryginalList[k2].split("--")[0]])
if plot == 'Single':
categories += v1['categories']
plotLinesName.append(k1)
if i == 0:
#plotLines.append([0, len(v1['categories'])])
plotLines.append(0)
else:
plotLines.append(plotLines[-1] + len(v1['categories']))
#plotLines.append([plotLines[-1][1], plotLines[-1][1]+len(v1['categories'])])
title.append(v1['title'])
if plot == 'Multi' and plotSeries == 'Single':
data.append([v2])
categories.append(v1['categories'])
if plot == 'Multi' and plotSeries == 'Multi':
if len(categories) > 0 and v1['categories'] != categories[
len(cat) - 1]:
data.append(d)
d = [v2]
plotLinesName.append(pl)
pl = [k1]
if not v1['categories'] in categories:
categories.append(v1['categories'])
else:
if not v1['categories'] in categories:
categories.append(v1['categories'])
d.append(v2)
pl.append(k1)
i += 1
if plot == 'Multi' and plotSeries == 'Multi':
data.append(d)
plotLinesName.append(pl)
vg = visualizationGraphs()
res = ''
if plot == 'Single':
res += vg.drawColumnChart(data,
categories=categories,
xAxisRotation=90,
marginTop=30,
height=300,
plotLines=plotLines,
plotLinesName=plotLinesName,
plotBandsColor=True,
showInLegend=False)
if plot == 'Multi':
if plotSeries == 'Multi':
res += vg.drawColumnCharts(data,
categories=categories,
xAxisRotation=90,
marginTop=30,
height=300,
seriesName=plotLinesName,
minY=0)
if plotSeries == 'Single':
res += vg.drawColumnCharts(
data,
categories=categories,
xAxisRotation=90,
marginTop=30,
height=300,
seriesName=seriesName,
minY=0,
titleText=title,
)
print res
def execute(cls, choices, galaxyFn=None, username=''):
#cls._setDebugModeIfSelected(choices)
# from config.DebugConfig import DebugConfig
# from config.DebugConfig import DebugModes
# DebugConfig.changeMode(DebugModes.RAISE_HIDDEN_EXCEPTIONS_NO_VERBOSE)
# DebugUtil.insertBreakPoint(5678, suspend=False)
choices_gsuite = choices.gsuite
selected_metadata = choices.cat
choices_queryTrack = choices.query
#genome = 'hg19'
genome = choices.genome
queryTS = factory.getSingleTrackTS(genome, choices_queryTrack)
refTS = factory.getFlatTracksTS(genome, choices_gsuite)
categoricalTS = refTS.getSplittedByCategoryTS(selected_metadata)
fullTS = TrackStructureV2()
fullTS['query'] = queryTS
fullTS['reference'] = categoricalTS
spec = AnalysisSpec(SummarizedInteractionPerTsCatV2Stat)
parameter = 'minLqMedUqMax'
spec.addParameter('pairwiseStatistic', ObservedVsExpectedStat.__name__)
spec.addParameter('summaryFunc', parameter)
bins = UserBinSource('chr1', '*', genome=genome)
res = doAnalysis(spec, bins, fullTS)
tsRes = res.getGlobalResult()['Result']
htmlCore = HtmlCore()
htmlCore.begin()
if parameter == 'minAndMax':
htmlCore.tableHeader(['Track', 'min-max'],
sortable=False,
tableId='tab1')
for k, it in tsRes.iteritems():
htmlCore.tableLine([
k,
str("%.2f" % it.getResult()[0]) + '-' +
str("%.2f" % it.getResult()[1])
])
htmlCore.tableFooter()
if parameter == 'minLqMedUqMax':
dataList = []
categories = []
for keyE, itE in tsRes.iteritems():
categories.append(keyE)
dataList.append(list(itE.getResult()))
from quick.webtools.restricted.visualization.visualizationGraphs import \
visualizationGraphs
vg = visualizationGraphs()
res = vg.drawBoxPlotChart(dataList,
categories=categories,
seriesName=selected_metadata)
htmlCore.line(res)
htmlCore.end()
print htmlCore
def execute(choices, galaxyFn=None, username=''):
file = choices.file
columnX = choices.columnX
columnY = choices.columnY
plotType = choices.plotType
axesScaleX = choices.axesScaleX
axesScaleY = choices.axesScaleY
plotSeries = choices.plotSeries
if axesScaleX == 'linear':
plotRes = 'combine'
elif axesScaleX == 'log10':
plotRes = 'separate'
elif axesScaleX == 'no uniform scale (sorted values as labels)':
plotRes = 'separate'
inputFile = open(
ExternalTrackManager.extractFnFromGalaxyTN(file.split(':')), 'r')
dataS = OrderedDict()
dataS['xAxis'] = OrderedDict()
dataS['yAxis'] = OrderedDict()
i = 0
with inputFile as f:
for x in f.readlines():
if i == 0:
rowColumn = list(x.strip('\n').split('\t'))
else:
j = 0
for el in list(x.strip('\n').split('\t')):
# if columnX[rowColumn[j]] == 'True':
# if not rowColumn[j] in dataS['xAxis']:
# dataS['xAxis'][rowColumn[j]] = []
# dataS['xAxis'][rowColumn[j]].append(el)
if rowColumn[j] in columnX:
if not rowColumn[j] in dataS['xAxis']:
dataS['xAxis'][rowColumn[j]] = []
dataS['xAxis'][rowColumn[j]].append(el)
if rowColumn[j] in columnY and columnY[
rowColumn[j]] == 'True':
if not rowColumn[j] in dataS['yAxis']:
dataS['yAxis'][rowColumn[j]] = []
dataS['yAxis'][rowColumn[j]].append(float(el))
j += 1
i += 1
inputFile.close()
# this will be used just for x - values
# keysX = dataS['xAxis'].keys()
# if keysX == 1:
# plotSeries = 'Single'
# else:
# plotSeries = 'Multi'
#sorting categories values
categoriesNumber = False
sortedCat = None
categories = None
if columnX == 'line number':
categories = None
else:
#if columnX['xAxis'] in columnY.keys():
if columnX in columnY.keys():
categoriesBefore = [float(v) for v in dataS['xAxis'][columnX]]
if axesScaleX == 'log10':
for cbN in range(0, len(categoriesBefore)):
if categoriesBefore[cbN] != 0:
categoriesBefore[cbN] = math.log(
categoriesBefore[cbN], 10)
sortedCat = sorted(range(len(categoriesBefore)),
key=lambda k: categoriesBefore[k])
categories = []
for n in sortedCat:
categories.append(categoriesBefore[n])
categoriesNumber = True
else:
categories = dataS['xAxis'][columnX]
#dataS are sorted according to numerical values
seriesName = []
data = []
for key, it in columnY.iteritems():
if it == 'True':
dataPart = []
seriesName.append(key)
dataPart = []
for x in dataS['yAxis'][key]:
try:
if axesScaleY == 'log10':
if x != 0:
dataPart.append(math.log(float(x), 10))
else:
dataPart.append(0)
else:
dataPart.append(float(x))
except:
dataPart.append(x)
if sortedCat != None:
dataPartTemp = []
for n in sortedCat:
dataPartTemp.append(dataPart[n])
dataPart = dataPartTemp
data.append(dataPart)
label = ''
if len(seriesName) != 0:
label = '<b>{series.name}</b>: {point.x} {point.y}'
else:
label = '{point.x} {point.y}'
# 'Column', 'Scatter', 'Heatmap'
if axesScaleX == 'log10':
xAxisTitle = str(columnX) + ' (' + str(axesScaleX) + ')'
else:
xAxisTitle = str(columnX)
if axesScaleY == 'log10':
yAxisTitle = str('values') + ' (' + str(axesScaleY) + ')'
else:
yAxisTitle = str('values')
minFromList = min(min(d) for d in data)
if minFromList > 0:
minFromList = 0
#combain series with data
if plotRes == 'combine':
if categoriesNumber == True:
newData = []
for d in data:
newDataPart = []
for cN in range(0, len(categories)):
newDataPart.append([categories[cN], d[cN]])
newData.append(newDataPart)
data = newData
categories = None
vg = visualizationGraphs()
res = ''
if plotSeries == 'Single':
if plotType == 'Scatter':
res += vg.drawScatterChart(data,
categories=categories,
xAxisRotation=90,
marginTop=30,
xAxisTitle=xAxisTitle,
yAxisTitle=yAxisTitle,
height=500,
seriesName=seriesName,
label=label,
minY=minFromList)
if plotType == 'Column':
res += vg.drawColumnChart(data,
categories=categories,
xAxisRotation=90,
marginTop=30,
xAxisTitle=xAxisTitle,
yAxisTitle=yAxisTitle,
height=500,
seriesName=seriesName,
label=label,
minY=minFromList)
elif plotSeries == 'Multi':
if plotType == 'Scatter':
for nrD in range(0, len(data)):
if plotRes == 'combine':
data[nrD] = [data[nrD]]
res += vg.drawScatterChart(
data[nrD],
categories=categories,
xAxisRotation=90,
marginTop=30,
xAxisTitle=xAxisTitle,
yAxisTitle=yAxisTitle,
height=500,
seriesName=[seriesName[nrD]],
label=label,
minY=minFromList
# titleText = 'Plot',
)
if plotType == 'Column':
res += vg.drawColumnCharts(
data,
categories=[categories for x in range(0, len(data))],
xAxisRotation=90,
marginTop=30,
xAxisTitle=xAxisTitle,
yAxisTitle=yAxisTitle,
height=500,
seriesName=[[seriesName[elD]]
for elD in range(0, len(data))],
label=label,
minY=minFromList
# titleText = 'Plot',
)
htmlCore = HtmlCore()
htmlCore.begin()
htmlCore.divBegin(divId='results-page')
htmlCore.divBegin(divClass='results-section')
htmlCore.line(res)
htmlCore.divEnd()
htmlCore.divEnd()
htmlCore.end()
print htmlCore
def execute(choices, galaxyFn=None, username=''):
'''
Is called when execute-button is pushed by web-user. Should print
output as HTML to standard out, which will be directed to a results page
in Galaxy history. If getOutputFormat is anything else than HTML, the
output should be written to the file with path galaxyFn. If needed,
StaticFile can be used to get a path where additional files can be put
(e.g. generated image files). choices is a list of selections made by
web-user in each options box.
'''
# from gold.application.LogSetup import setupDebugModeAndLogging
#setupDebugModeAndLogging()
# targetTrackNames, targetTrackCollection, targetTrackGenome = getGSuiteDataFromGalaxyTN(choices.gSuiteFirst)
# targetTracksDict = OrderedDict(zip(targetTrackNames, targetTrackCollection))
# refTrackNames, refTrackCollection, refTrackCollectionGenome = getGSuiteDataFromGalaxyTN(choices.gSuiteSecond)
# refTracksDict = OrderedDict(zip(refTrackNames, refTrackCollection))
#
targetGSuite = getGSuiteFromGalaxyTN(choices.gSuiteFirst)
refGSuite = getGSuiteFromGalaxyTN(choices.gSuiteSecond)
regSpec, binSpec = UserBinMixin.getRegsAndBinsSpec(choices)
if choices.intraOverlap == TrackCollectionsAnalysis.MERGE_INTRA_OVERLAPS:
analysisDef = 'dummy -> RawOverlapStat'
else:
analysisDef = 'dummy [withOverlaps=yes] -> RawOverlapAllowSingleTrackOverlapsStat'
results = OrderedDict()
# for targetTrackName, targetTrack in targetTracksDict.iteritems():
# for refTrackName, refTrack in refTracksDict.iteritems():
for targetTrack in targetGSuite.allTracks():
targetTrackName = targetTrack.title
for refTrack in refGSuite.allTracks():
refTrackName = refTrack.title
if targetTrack.trackName == refTrack.trackName:
result = TrackCollectionsAnalysis.handleSameTrack(targetTrack.trackName, regSpec, binSpec,
choices.genome, galaxyFn)
else:
result = GalaxyInterface.runManual([targetTrack.trackName, refTrack.trackName],
analysisDef, regSpec, binSpec,
choices.genome, galaxyFn,
printRunDescription=False,
printResults=False).getGlobalResult()
if targetTrackName not in results :
results[targetTrackName] = OrderedDict()
results[targetTrackName][refTrackName] = result
stat = choices.statistic
statIndex = STAT_LIST_INDEX[stat]
title = 'Screening track collections (' + stat + ')'
processedResults = []
headerColumn = []
for targetTrackName in targetGSuite.allTrackTitles():
resultRowDict = processRawResults(results[targetTrackName])
resultColumn = []
headerColumn = []
for refTrackName, statList in resultRowDict.iteritems():
resultColumn.append(statList[statIndex])
headerColumn.append(refTrackName)
processedResults.append(resultColumn)
transposedProcessedResults = [list(x) for x in zip(*processedResults)]
tableHeader = ['Track names'] + targetGSuite.allTrackTitles()
htmlCore = HtmlCore()
htmlCore.begin()
htmlCore.header(title)
htmlCore.divBegin('resultsDiv')
htmlCore.tableHeader(tableHeader, sortable=True, tableId='resultsTable')
for i, row in enumerate(transposedProcessedResults):
line = [headerColumn[i]] + [strWithStdFormatting(x) for x in row]
htmlCore.tableLine(line)
htmlCore.tableFooter()
htmlCore.divEnd()
# #hicharts can't handle strings that contain ' or " as input for series names
targetTrackNames = [x.replace('\'', '').replace('"','') for x in targetGSuite.allTrackTitles()]
refTrackNames = [x.replace('\'', '').replace('"','') for x in refGSuite.allTrackTitles()]
#
# '''
# addColumnPlotToHtmlCore(htmlCore, targetTrackNames, refTrackNames,
# stat, title + ' plot',
# processedResults, xAxisRotation = -45, height=800)
# '''
# '''
# addPlotToHtmlCore(htmlCore, targetTrackNames, refTrackNames,
# stat, title + ' plot',
# processedResults, xAxisRotation = -45, height=400)
# '''
#
from quick.webtools.restricted.visualization.visualizationGraphs import visualizationGraphs
vg = visualizationGraphs()
result = vg.drawColumnChart(processedResults,
height=600,
yAxisTitle=stat,
categories=refTrackNames,
xAxisRotation=90,
seriesName=targetTrackNames,
shared=False,
titleText=title + ' plot',
overMouseAxisX=True,
overMouseLabelX = ' + this.value.substring(0, 10) +')
htmlCore.line(result)
#htmlCore.line(vg.visualizeResults(result, htmlCore))
htmlCore.hideToggle(styleClass='debug')
htmlCore.end()
print htmlCore
def execute(choices, galaxyFn=None, username=''):
#data from choices
gSuite = choices.gSuite
plotType = choices.plotType
columnX = choices.columnX
columnY = choices.columnY
plotSeries = choices.plotSeries
axesScaleX = choices.axesScaleX
axesScaleY = choices.axesScaleY
#'linear', 'log10', 'no uniform scale (sorted values as labels)'
if axesScaleX == 'linear':
#plotRes = choices.plotRes
plotRes = 'combine'
elif axesScaleX == 'log10':
plotRes = 'separate'
elif axesScaleX == 'no uniform scale (sorted values as labels)':
plotRes = 'separate'
#unpack gsuite
gSuite = getGSuiteFromGalaxyTN(gSuite)
#full list of attributes (meta-data)
attributeList = gSuite.attributes
#fill list of attributes plus title
attributeList = [TITLE_COL] + attributeList
#dictNum - include numerical values which can be presented in y-axes
#need to do that because pie can have only one chocie and then it is not returing dict
from quick.gsuite.GSuiteUtils import attributesType
attribute = attributesType(gSuite)
dictNum=OrderedDict()
for key, it in attribute.iteritems():
if it == True:
dictNum[key] = False
#check if it is dict or not
if not isinstance(columnY, dict):
tempDict={}
tempDict[columnY] = 'True'
columnY=tempDict
seriesName=[]
#check if user selected categoriesNumber and it is possible to use combinate
categoriesNumber = False
sortedCat=None
categories=None
if columnX == TITLE_COL:
categories = gSuite.allTrackTitles()
elif columnX == 'line number':
categories = None
else:
if columnX in dictNum.keys():
categoriesBefore = [float(v) for v in gSuite.getAttributeValueList(columnX)]
if axesScaleX == 'log10':
for cbN in range(0, len(categoriesBefore)):
if categoriesBefore[cbN]!=0:
categoriesBefore[cbN]=math.log(categoriesBefore[cbN], 10)
sortedCat = sorted(range(len(categoriesBefore)), key=lambda k: categoriesBefore[k])
categories=[]
for n in sortedCat:
categories.append(categoriesBefore[n])
categoriesNumber=True
else:
categories = gSuite.getAttributeValueList(columnX)
#data are sorted according to numerical values
data=[]
for key, it in columnY.iteritems():
if it == 'True':
dataPart=[]
seriesName.append(key)
dataPart = []
for x in gSuite.getAttributeValueList(key):
try:
if axesScaleY == 'log10':
if x!=0:
dataPart.append(math.log(float(x), 10))
else:
dataPart.append(0)
else:
dataPart.append(float(x))
except:
# need to support None in heatmap
if plotType == 'Heatmap':
dataPart.append(0)
else:
dataPart.append(x)
if sortedCat!=None:
dataPartTemp=[]
for n in sortedCat:
dataPartTemp.append(dataPart[n])
dataPart = dataPartTemp
data.append(dataPart)
label=''
if len(seriesName)!=0:
label = '<b>{series.name}</b>: {point.x} {point.y}'
else:
label = '{point.x} {point.y}'
vg = visualizationGraphs()
# 'Column', 'Scatter', 'Heatmap'
if axesScaleX == 'log10':
xAxisTitle = str(columnX) + ' (' + str(axesScaleX) + ')'
else:
xAxisTitle = str(columnX)
if axesScaleY == 'log10':
yAxisTitle = str('values') + ' (' + str(axesScaleY) + ')'
else:
yAxisTitle = str('values')
minFromList = min(min(d) for d in data)
if minFromList > 0:
minFromList = 0
#combain series with data
if plotRes == 'combine':
if categoriesNumber == True:
newData=[]
for d in data:
newDataPart=[]
for cN in range(0, len(categories)):
newDataPart.append([categories[cN], d[cN]])
newData.append(newDataPart)
data=newData
categories=None
res=''
if plotSeries == 'Single':
if plotType == 'Scatter':
res += vg.drawScatterChart(
data,
categories = categories,
xAxisRotation = 90,
marginTop = 30,
xAxisTitle = xAxisTitle,
yAxisTitle = yAxisTitle,
height = 500,
seriesName = seriesName,
label = label,
minY=minFromList
# titleText = 'Plot',
)
if plotType == 'Pie':
res += vg.drawPieChart(
data[0],
seriesName = categories,
height = 400,
titleText = seriesName[0],
)
if plotType == 'Column':
res += vg.drawColumnChart(
data,
categories = categories,
xAxisRotation = 90,
marginTop = 30,
xAxisTitle = xAxisTitle,
yAxisTitle = yAxisTitle,
height = 500,
seriesName = seriesName,
label = label,
minY=minFromList
# titleText = 'Plot',
)
if plotType == 'Line':
res += vg.drawLineChart(
data,
categories = categories,
xAxisRotation = 90,
marginTop = 30,
xAxisTitle = xAxisTitle,
yAxisTitle = yAxisTitle,
height = 500,
seriesName = seriesName,
label = label,
minY=minFromList
# titleText = 'Plot',
)
if plotType == 'Heatmap':
res += vg.drawHeatmapSmallChart(
data,
categories = categories,
xAxisRotation = 90,
marginTop = 30,
xAxisTitle = xAxisTitle,
yAxisTitle = yAxisTitle,
height = 500,
seriesName = seriesName,
label = label,
# titleText = 'Plot',
)
elif plotSeries == 'Multi':
if plotType == 'Scatter':
for nrD in range(0, len(data)):
if plotRes == 'combine':
data[nrD]=[data[nrD]]
res += vg.drawScatterChart(
data[nrD],
categories = categories,
xAxisRotation = 90,
marginTop = 30,
xAxisTitle = xAxisTitle,
yAxisTitle = yAxisTitle,
height = 500,
seriesName = [seriesName[nrD]],
label = label,
minY=minFromList
# titleText = 'Plot',
)
if plotType == 'Column':
res += vg.drawColumnCharts(
data,
categories = [categories for x in range(0, len(data))],
xAxisRotation = 90,
marginTop = 30,
xAxisTitle = xAxisTitle,
yAxisTitle = yAxisTitle,
height = 500,
seriesName = [[seriesName[elD]] for elD in range(0, len(data))],
label = label,
minY=minFromList
# titleText = 'Plot',
)
if plotType == 'Line':
for nrD in range(0, len(data)):
if plotRes == 'combine':
data[nrD]=[data[nrD]]
res += vg.drawLineChart(
data[nrD],
categories = categories,
xAxisRotation = 90,
marginTop = 30,
xAxisTitle = xAxisTitle,
yAxisTitle = yAxisTitle,
height = 500,
seriesName = [seriesName[nrD]],
label = label,
minY=minFromList
# titleText = 'Plot',
)
htmlCore = HtmlCore()
htmlCore.begin()
htmlCore.divBegin(divId='results-page')
htmlCore.divBegin(divClass='results-section')
htmlCore.line(res)
htmlCore.divEnd()
htmlCore.divEnd()
htmlCore.end()
print htmlCore
def execute(cls, choices, galaxyFn=None, username=''):
cls._setDebugModeIfSelected(choices)
genome = choices.genome
genomicRegions = choices.genomicRegions
genomicRegionsTracks = choices.genomicRegionsTracks
sourceTfs = choices.sourceTfs
sourceTfsDetails = choices.sourceTfsDetails
tfTracks = choices.tfTracks
# Get Genomic Region track name:
if genomicRegions == cls.REGIONS_FROM_HISTORY:
galaxyTN = genomicRegionsTracks.split(':')
genElementTrackName = ExternalTrackManager.getPreProcessedTrackFromGalaxyTN(
genome, galaxyTN)
#queryGSuite = getGSuiteFromGalaxyTN(genomicRegionsTracks)
#queryTrackList = [Track(x.trackName, x.title) for x in queryGSuite.allTracks()]
elif genomicRegions == 'Hyperbrowser repository':
selectedGenRegTrack = TfbsTrackNameMappings.getTfbsTrackNameMappings(
genome)[genomicRegionsTracks]
if isinstance(selectedGenRegTrack, dict):
genElementTrackName = selectedGenRegTrack.values()
else:
genElementTrackName = selectedGenRegTrack
elif genomicRegions == 'Hyperbrowser repository (cell-type-specific)':
genElementTrackName = ['Private', 'Antonio'
] + genomicRegionsTracks.split(':')
else:
return
# Get TF track names:
if isinstance(tfTracks, dict):
selectedTfTracks = [
key for key, val in tfTracks.iteritems() if val == 'True'
]
else:
selectedTfTracks = [tfTracks]
queryTrackTitle = '--'.join(genElementTrackName)
trackTitles = [queryTrackTitle]
tracks = [Track(genElementTrackName, trackTitle=queryTrackTitle)]
for i in selectedTfTracks:
if sourceTfs == 'Hyperbrowser repository':
tfTrackName = TfTrackNameMappings.getTfTrackNameMappings(
genome)[sourceTfsDetails] + [i]
tracks.append(
Track(tfTrackName,
trackTitle=tfTrackName[len(tfTrackName) - 1]))
trackTitles.append(tfTrackName[len(tfTrackName) - 1])
else:
tfTrackName = i.split(':')
queryGSuite = getGSuiteFromGalaxyTN(sourceTfsDetails)
for x in queryGSuite.allTracks():
selectedTrackNames = (':'.join(x.trackName))
if i == selectedTrackNames:
tracks.append(Track(x.trackName, x.title))
trackTitles.append(x.trackName[-1])
# queryGSuite = getGSuiteFromGalaxyTN(sourceTfsDetails)
# tfTrackName = [x.trackName for x in queryGSuite.allTracks()] + [i]
# tracks += [Track(x.trackName, x.title) for x in queryGSuite.allTracks()]
# trackTitles += tfTrackName
# print tfTrackName
# print tracks
# print trackTitles
trackTitlesForStat = trackTitles
trackTitles = CommonConstants.TRACK_TITLES_SEPARATOR.join(trackTitles)
##first statistic for Q2
resultsForStatistics = OrderedDict()
similarityFunc = [ #GSuiteStatUtils.T7_RATIO_OF_OBSERVED_TO_EXPECTED_OVERLAP,
GSuiteStatUtils.T5_RATIO_OF_OBSERVED_TO_EXPECTED_OVERLAP
]
for similarityStatClassName in similarityFunc:
regSpec, binSpec = UserBinMixin.getRegsAndBinsSpec(choices)
analysisBins = GalaxyInterface._getUserBinSource(regSpec,
binSpec,
genome=genome)
mcfdrDepth = AnalysisDefHandler(
REPLACE_TEMPLATES['$MCFDR$']).getOptionsAsText().values()[0][0]
analysisDefString = REPLACE_TEMPLATES[
'$MCFDR$'] + ' -> GSuiteSimilarityToQueryTrackRankingsAndPValuesWrapperStat'
analysisSpec = AnalysisDefHandler(analysisDefString)
analysisSpec.setChoice('MCFDR sampling depth', mcfdrDepth)
analysisSpec.addParameter('assumptions',
'PermutedSegsAndIntersegsTrack_')
analysisSpec.addParameter(
'rawStatistic', GSuiteStatUtils.
PAIRWISE_STAT_LABEL_TO_CLASS_MAPPING[similarityStatClassName])
analysisSpec.addParameter(
'pairwiseStatistic', GSuiteStatUtils.
PAIRWISE_STAT_LABEL_TO_CLASS_MAPPING[similarityStatClassName]
) #needed for call of non randomized stat for assertion
analysisSpec.addParameter('tail', 'more')
analysisSpec.addParameter('trackTitles',
trackTitles) #that need to be string
analysisSpec.addParameter('queryTracksNum', str(len(tracks)))
results = doAnalysis(analysisSpec, analysisBins,
tracks).getGlobalResult()
if not similarityStatClassName in resultsForStatistics:
resultsForStatistics[similarityStatClassName] = {}
resultsForStatistics[similarityStatClassName] = results
keyTitle = [
#'Normalized ratio of observed to expected overlap (normalized Forbes similarity measure)',
'Ratio of observed to expected overlap (Forbes similarity measure)'
]
# 'Normalized Forbes coefficient: ratio of observed to expected overlap normalized in relation to the reference GSuite',
# 'Forbes coefficient: ratio of observed to expected overlap'
keyTitle = [
#GSuiteStatUtils.T7_RATIO_OF_OBSERVED_TO_EXPECTED_OVERLAP,
GSuiteStatUtils.T5_RATIO_OF_OBSERVED_TO_EXPECTED_OVERLAP
]
resultDict = AllTfsOfRegions.countStatistics(similarityFunc, choices,
genome, tracks,
trackTitlesForStat)
resultDictShow = AllTfsOfRegions.countStatisticResults(
resultDict, keyTitle, trackTitlesForStat)
# print resultsForStatistics
'''selectedTrackNames = []
if sourceTfs == 'History (user-defined)':
if selectedTfTracks.split(":")[1] == "gsuite":
gSuite = getGSuiteFromGalaxyTN(selectedTfTracks)
for track in gSuite.allTracks():
selectedTrackNames.append(track.trackName)
else:
galaxyTN = selectedTfTracks.split(':')
gRegTrackName = ExternalTrackManager.getPreProcessedTrackFromGalaxyTN(genome, galaxyTN)
selectedTrackNames.append(gRegTrackName)
else:'''
tfNameList = []
#Intersection between TF Tracks and selected region (Table 1):
n = 0
allTargetBins = []
alltfNames = []
table1 = []
for i in selectedTfTracks:
n = n + 1
#newGalaxyFn = galaxyFn.split(".")[0] + str(n) + "." + "dat"
if sourceTfs == 'Hyperbrowser repository':
tfTrackName = TfTrackNameMappings.getTfTrackNameMappings(
genome)[sourceTfsDetails] + [i]
else:
tfTrackName = i.split(':')
tfTrackName.pop(0)
#tfIntersection.expandReferenceTrack(upFlankSize, downFlankSize)
tfIntersection = TrackIntersection(genome, genElementTrackName,
tfTrackName, galaxyFn, str(n))
regFileNamer = tfIntersection.getIntersectedRegionsStaticFileWithContent(
)
targetBins = tfIntersection.getIntersectedReferenceBins()
#regSpec, targetBins = UserBinSelector.getRegsAndBinsSpec(choices)
tfHits = [i] * len(targetBins)
fixedTargetBins = [str(a).split(" ")[0] for a in targetBins]
extendedTargetBins = [
list(a) for a in zip(fixedTargetBins, tfHits)
]
allTargetBins = allTargetBins + extendedTargetBins
tfName = i
alltfNames = alltfNames + [tfName]
# Save output table:
tfNameList.append(tfName)
line = [tfName] + [len(targetBins)] + [
regFileNamer.getLink('Download bed-file')
] + [
regFileNamer.getLoadToHistoryLink('Send bed-file to History')
]
table1 = table1 + [line]
# Computing totals:
fullCase = ','.join(alltfNames)
firstColumn = [item[0] for item in allTargetBins]
uniqueAllTargetBins = list(set(firstColumn))
# Group TFs by bound region:
d1 = defaultdict(list)
for k, v in allTargetBins:
d1[k].append(v)
allTFTargetBins = dict((k, ','.join(v)) for k, v in d1.iteritems())
allTFTargetList = []
fullCaseTFTargetList = []
for key, value in allTFTargetBins.iteritems():
allTFTargetList = allTFTargetList + [[key, value]]
if value == fullCase:
fullCaseTFTargetList = fullCaseTFTargetList + [[key, value]]
analysis3 = TrackIntersection.getFileFromTargetBins(
allTFTargetList, galaxyFn, str(3))
analysis4 = TrackIntersection.getFileFromTargetBins(
fullCaseTFTargetList, galaxyFn, str(4))
# Print output to table:
title = 'TF targets and co-occupancy of ' + genElementTrackName[
-1] + ' genomic regions'
htmlCore = HtmlCore()
pf = plotFunction(tableId='resultsTable')
htmlCore.begin()
htmlCore.header(title)
htmlCore.divBegin('resultsDiv')
htmlCore.line(pf.createButton(bText='Show/Hide more results'))
# htmlCore.tableHeader(['Transcription Factor', 'Normalized ratio of observed to expected overlap (normalized Forbes similarity measure) -- Similarity to genomic regions track', 'Normalized ratio of observed to expected overlap (normalized Forbes similarity measure) -- p-value','Ratio of observed to expected overlap (Forbes similarity measure) -- Similarity to genomic regions track', 'Ratio of observed to expected overlap (Forbes similarity measure) -- p-value', 'Number of TF-Target Track Regions', 'File of TF Target Regions', 'File of TF Target Regions', 'Number of TF-co-occupied Regions', 'File of TF co-occupied Regions', 'File of TF co-occupied Regions', 'Rank of TF co-occupancy motifs', 'Rank of TF co-occupancy motifs'], sortable=True, tableId='resultsTable')
#previous ordering
# htmlCore.tableHeader(['Transcription Factor', 'Normalized Forbes index --overlap score',
# 'Normalized Forbes index --p-value',
# 'Forbes index --overlap score', 'Forbes index --p-value',
# 'Number of TF-Target Track Regions', 'File of TF Target Regions',
# 'File of TF Target Regions', 'Number of target track regions occupied by this TF',
# 'File of TF co-occupied Regions', 'File of TF co-occupied Regions',
# 'Rank of TF co-occupancy motifs', 'Rank of TF co-occupancy motifs'],
# sortable=True, tableId='resultsTable')
htmlCore.tableHeader(
[
'Transcription Factor',
'Number of TF-Target Track Regions',
'File of TF Track Regions',
'Number of target track regions occupied by this TF',
'File of TF Target Regions',
'Forbes index --overlap score',
'Forbes index --p-value',
#'Normalized Forbes index --overlap score', 'Normalized Forbes index --p-value',
'File of TF co-occupied Regions',
'Rank of TF co-occupancy motifs'
],
sortable=True,
tableId='resultsTable')
# Adding co-occupancy results to table:
n = 1000
genRegionNumElements = [
int(x) for x in getTrackRelevantInfo.getNumberElements(
genome, genElementTrackName)
]
for key0, it0 in resultsForStatistics.iteritems():
for el in tfNameList:
if el not in it0:
resultsForStatistics[key0][el] = [None, None]
resultsPlotDict = {}
resultPlotCat = []
resultsPlot = []
resultsForStatisticsProper = {}
for key0, it0 in resultsForStatistics.iteritems():
if not key0 in resultsPlotDict:
resultsPlotDict[key0] = {}
resultsPlotPart = []
for key1, it1 in it0.iteritems():
resultsPlotPart.append(it1[0])
if not key1 in resultsForStatisticsProper:
resultsForStatisticsProper[key1] = []
if not key1 in resultsPlotDict[key0]:
resultsPlotDict[key0][key1] = None
for el in it1:
resultsForStatisticsProper[key1].append(el)
resultsPlotDict[key0][key1] = it1[0]
resultPlotCat.append(tfNameList)
resultPlotCat.append(tfNameList)
#resultPlotCatPart = tfNameList
# print resultPlotCatPart
for key0, it0 in resultsPlotDict.iteritems():
resultsPlotPart = []
for el in tfNameList:
if el in it0:
resultsPlotPart.append(it0[el])
else:
resultsPlotPart.append(None)
resultsPlot.append(resultsPlotPart)
for i in table1:
thisCaseTFTargetList = []
for key, value in allTFTargetList:
if i[0] in value and ',' in value:
thisCaseTFTargetList = thisCaseTFTargetList + [[
key, value
]]
n = n + 1
thisAnalysis = TrackIntersection.getFileFromTargetBins(
thisCaseTFTargetList, galaxyFn, str(n))
thisCaseCoCountsList = []
thing = [x[1] for x in thisCaseTFTargetList]
for k in list(set(thing)):
thisCount = thing.count(k)
thisCaseCoCountsList = thisCaseCoCountsList + \
[[k, thisCount, 100*float(thisCount)/float(sum(genRegionNumElements)), 100*float(thisCount)/float(len(thisCaseTFTargetList))]]
thisCaseCoCountsList.sort(key=lambda x: x[2], reverse=True)
n = n + 1
thisCoCountsAnalysis = TrackIntersection.getOccupancySummaryFile(
thisCaseCoCountsList, galaxyFn, str(n))
thisLine = [len(thisCaseTFTargetList)] + \
[thisAnalysis.getLink('Download file')] + [thisAnalysis.getLoadToHistoryLink('Send file to History')] + \
[thisCoCountsAnalysis.getLink('Download file')] + [thisCoCountsAnalysis.getLoadToHistoryLink('Send file to History')]
newLineI = []
tfName = i[0]
newLineI.append(tfName)
for el in resultsForStatisticsProper[tfName]:
newLineI.append(el)
for elN in range(1, len(i)):
newLineI.append(i[elN])
# htmlCore.tableLine(i + thisLine)
# htmlCore.tableHeader(['Transcription Factor', 'Normalized Forbes index --overlap score',
# 'Normalized Forbes index --p-value',
# 'Forbes index --overlap score', 'Forbes index --p-value',
# 'Number of TF-Target Track Regions', 'File of TF Target Regions',
# 'File of TF Target Regions', 'Number of target track regions occupied by this TF',
# 'File of TF co-occupied Regions', 'File of TF co-occupied Regions',
# 'Rank of TF co-occupancy motifs', 'Rank of TF co-occupancy motifs'],
# sortable=True, tableId='resultsTable')
# htmlCore.tableHeader(['Transcription Factor', 'Number of TF-Target Track Regions', 'File of TF Track Regions',
# 'Number of target track regions occupied by this TF', 'File of TF Target Regions',
# 'Forbes index --overlap score', 'Forbes index --p-value',
# 'Normalized Forbes index --overlap score', 'Normalized Forbes index --p-value',
# 'File of TF co-occupied Regions', 'Rank of TF co-occupancy motifs'],
# sortable=True, tableId='resultsTable')
tl = newLineI + thisLine
# previous ordering tl - 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
# actual ordering - 0, 5, 7, 8, 7, 3, 4, 1, 2, 9, 11
#ordering = [0, 5, 7, 8, 10, 3, 4, 1, 2, 10, 12]
ordering = [0, 3, 5, 6, 8, 1, 2, 8, 10]
#1, 2, => delete
eoList = []
for eo in ordering:
eoList.append(tl[eo])
htmlCore.tableLine(eoList)
totalCoOccupancyTargetList = []
n = 2000
for key, value in allTFTargetList:
n = n + 1
if ',' in value:
totalCoOccupancyTargetList = totalCoOccupancyTargetList + [[
key, value
]]
#newGalaxyFn = galaxyFn.split(".")[0] + str(n) + "." + "dat"
totalCoOccupancyAnalysis = TrackIntersection.getFileFromTargetBins(
totalCoOccupancyTargetList, galaxyFn, str(n))
#line = ['Total reported regions'] + [len(allTargetBins)] + [''] + [''] + [''] + [''] + ['']
#line = ['Full co-occupancy of ' + fullCase] + ['-'] + ['-'] + ['-'] + ['-'] + ['-'] + ['-'] + ['-'] + [len(fullCaseTFTargetList)] + [analysis4.getLink('Download file')] + [analysis4.getLoadToHistoryLink('Send file to History')] + ['-'] + ['-']
line = ['Full co-occupancy of ' + fullCase] + \
['-'] + \
['-'] + \
[len(fullCaseTFTargetList)] + \
['-'] + \
['-'] + \
['-'] + \
[analysis4.getLoadToHistoryLink('Send file to History')] + \
['-']
htmlCore.tableLine(line)
#line = ['Total unique regions'] + ['-'] + ['-'] + ['-'] + ['-'] + [len(allTFTargetList)] + [analysis3.getLink('Download bed-file')] + [analysis3.getLoadToHistoryLink('Send bed-file to History')] + [len(totalCoOccupancyTargetList)] + [totalCoOccupancyAnalysis.getLink('Download file')] + [totalCoOccupancyAnalysis.getLoadToHistoryLink('Send file to History')] + ['-'] + ['-']
line = ['Total unique regions'] + \
[len(allTFTargetList)] + \
['-'] + \
[len(totalCoOccupancyTargetList)] + \
[analysis3.getLoadToHistoryLink('Send bed-file to History')] + \
['-'] +\
['-'] + \
[totalCoOccupancyAnalysis.getLoadToHistoryLink('Send file to History')] + \
['-']
htmlCore.tableLine(line)
htmlCore.tableFooter()
htmlCore.divEnd()
# htmlCore.line(pf.hideColumns(indexList=[2, 4]))
#
sumRes = 0
for r in resultsPlot[0]:
if r != None:
sumRes += r
if sumRes != 0:
vg = visualizationGraphs()
result = vg.drawColumnCharts(
[resultsPlot[0]],
height=300,
categories=resultPlotCat,
legend=False,
addOptions='width: 90%; float:left; margin: 0 4%;',
#titleText=['Overlap between TFs and genomic region using normalized Forbes', 'Overlap between TFs and genomic region using Forbes'],
titleText=[
'Overlap between TFs and genomic region using Forbes'
],
xAxisRotation=90,
xAxisTitle='TF',
yAxisTitle='value')
htmlCore.line(result)
for key0, it0 in resultDictShow.iteritems():
htmlCore.divBegin('resultsDiv' + str(key0))
htmlCore.header(key0)
htmlCore.tableHeader(it0[0],
sortable=True,
tableId='resultsTable' + str(key0))
for elN in range(1, len(it0)):
htmlCore.tableLine(it0[elN])
htmlCore.tableFooter()
htmlCore.divEnd()
htmlCore.hideToggle(styleClass='debug')
htmlCore.end()
print htmlCore
def execute(cls, choices, galaxyFn=None, username=''):
cls._setDebugModeIfSelected(choices)
targetGSuite = getGSuiteFromGalaxyTN(choices.gSuiteFirst)
refGSuite = getGSuiteFromGalaxyTN(choices.gSuiteSecond)
regSpec, binSpec = UserBinMixin.getRegsAndBinsSpec(choices)
analysisDef = 'dummy -> RawOverlapStat'
# analysisDef = 'dummy [withOverlaps=yes] -> RawOverlapAllowSingleTrackOverlapsStat'
results = OrderedDict()
for targetTrack in targetGSuite.allTracks():
targetTrackName = targetTrack.title
for refTrack in refGSuite.allTracks():
refTrackName = refTrack.title
if targetTrack.trackName == refTrack.trackName:
# print targetTrack.title
# print targetTrack.trackName
result = DetermineSuiteTracksCoincidingWithAnotherSuite.handleSameTrack(
targetTrack.trackName, regSpec, binSpec,
targetGSuite.genome, galaxyFn)
else:
result = GalaxyInterface.runManual(
[targetTrack.trackName, refTrack.trackName],
analysisDef,
regSpec,
binSpec,
targetGSuite.genome,
galaxyFn,
printRunDescription=False,
printResults=False,
printProgress=False).getGlobalResult()
if targetTrackName not in results:
results[targetTrackName] = OrderedDict()
results[targetTrackName][refTrackName] = result
stat = STAT_OVERLAP_COUNT_BPS
statIndex = STAT_LIST_INDEX[stat]
title = ''
processedResults = []
headerColumn = []
for targetTrackName in targetGSuite.allTrackTitles():
resultRowDict = processRawResults(results[targetTrackName])
resultColumn = []
headerColumn = []
for refTrackName, statList in resultRowDict.iteritems():
resultColumn.append(statList[statIndex])
headerColumn.append(refTrackName)
processedResults.append(resultColumn)
outputTable = {}
for elN in range(0, len(headerColumn)):
outputTable[elN] = {}
outputTable[elN]['id'] = headerColumn[elN]
transposedProcessedResults = [list(x) for x in zip(*processedResults)]
# second question sumSecondgSuite
# first question numSecondgSuite
# fifth question numSecondgSuitePercentage
for i in range(0, len(transposedProcessedResults)):
outputTable[i]['sumSecondgSuite'] = sum(
transposedProcessedResults[i])
if not 'numSecondgSuite' in outputTable[i]:
outputTable[i]['numSecondgSuite'] = 0
for j in range(0, len(transposedProcessedResults[i])):
if transposedProcessedResults[i][j] >= 1:
outputTable[i]['numSecondgSuite'] += 1
else:
outputTable[i]['numSecondgSuite'] += 0
outputTable[i]['numSecondgSuitePercentage'] = float(
outputTable[i]['numSecondgSuite']) / float(
targetGSuite.numTracks()) * 100
from gold.statistic.CountSegmentStat import CountSegmentStat
from gold.statistic.CountPointStat import CountPointStat
from gold.description.TrackInfo import TrackInfo
from gold.statistic.CountStat import CountStat
# third question numPairBpSecondgSuite
# fourth question numFreqBpSecondgSuite
i = 0
for refTrack in refGSuite.allTracks():
formatName = TrackInfo(refTrack.genome,
refTrack.trackName).trackFormatName
analysisDef = CountStat
analysisBins = GalaxyInterface._getUserBinSource(
regSpec, binSpec, refTrack.genome)
results = doAnalysis(AnalysisSpec(analysisDef), analysisBins,
[PlainTrack(refTrack.trackName)])
resultDict = results.getGlobalResult()
if len(resultDict) == 0:
outputTable[i]['numPairBpSecondgSuite'] = None
outputTable[i]['numFreqBpSecondgSuite'] = None
outputTable[i]['numFreqUniqueBpSecondgSuite'] = None
else:
outputTable[i]['numPairBpSecondgSuite'] = resultDict['Result']
if outputTable[i]['numPairBpSecondgSuite'] != 0:
outputTable[i]['numFreqBpSecondgSuite'] = float(
outputTable[i]['sumSecondgSuite']) / float(
outputTable[i]['numPairBpSecondgSuite'])
else:
outputTable[i]['numFreqBpSecondgSuite'] = None
if outputTable[i]['sumSecondgSuite'] != 0:
outputTable[i]['numFreqUniqueBpSecondgSuite'] = float(
outputTable[i]['numPairBpSecondgSuite']) / float(
outputTable[i]['sumSecondgSuite'])
else:
outputTable[i]['numFreqUniqueBpSecondgSuite'] = None
i += 1
# sortTable
outputTableLine = []
for key, item in outputTable.iteritems():
line = [
item['id'], item['numSecondgSuite'], item['sumSecondgSuite'],
item['numPairBpSecondgSuite'], item['numFreqBpSecondgSuite'],
item['numFreqUniqueBpSecondgSuite'],
item['numSecondgSuitePercentage']
]
outputTableLine.append(line)
import operator
outputTableLineSort = sorted(outputTableLine,
key=operator.itemgetter(1),
reverse=True)
tableHeader = [
'Region ID ', 'Number of cases with at least one event ',
'Total number of events', 'Genome coverage (unique bp)',
'Number of events per unique bp', 'Number of unique bp per event',
'Percentage of cases with at least one event'
]
htmlCore = HtmlCore()
htmlCore.begin()
htmlCore.line(
"<b>Identification of genomic elements with high event recurrence</b> "
)
htmlCore.header(title)
htmlCore.divBegin('resultsDiv')
htmlCore.tableHeader(tableHeader,
sortable=True,
tableId='resultsTable')
for line in outputTableLineSort:
htmlCore.tableLine(line)
plotRes = []
plotXAxis = []
for lineInx in range(1, len(outputTableLineSort[0])):
plotResPart = []
plotXAxisPart = []
for lineInxO in range(0, len(outputTableLineSort)):
# if outputTableLineSort[lineInxO][lineInx]!=0 and
# if outputTableLineSort[lineInxO][lineInx]!=None:
plotResPart.append(outputTableLineSort[lineInxO][lineInx])
plotXAxisPart.append(outputTableLineSort[lineInxO][0])
plotRes.append(plotResPart)
plotXAxis.append(plotXAxisPart)
htmlCore.tableFooter()
htmlCore.divEnd()
htmlCore.divBegin('plot', style='padding-top:20px;margin-top:20px;')
vg = visualizationGraphs()
res = vg.drawColumnCharts(
plotRes,
titleText=tableHeader[1:],
categories=plotXAxis,
height=500,
xAxisRotation=270,
xAxisTitle='Ragion ID',
yAxisTitle='Number of cases with at least one event',
marginTop=30,
addTable=True,
sortableAccordingToTable=True,
legend=False)
htmlCore.line(res)
htmlCore.divEnd()
htmlCore.hideToggle(styleClass='debug')
htmlCore.end()
print htmlCore
