def printClusterPlots(cls, correlationMatrix, linkageMatrix, galaxyFn, distanceMeasure, labels, htmlCore):
from numpy import amax, amin, isnan
maxVal = amax(correlationMatrix)
minVal = amin(correlationMatrix)
seabornFile = GalaxyRunSpecificFile(['Image', distanceMeasure + 'seabornHeatmap.pdf'], galaxyFn)
dendrogramFile = GalaxyRunSpecificFile(['Image', distanceMeasure + 'dendrogram.pdf'], galaxyFn)
if minVal < 0 or isnan(minVal):
MatplotlibPlots.seabornHeatmapPlot(
correlationMatrix,
labels,
max=maxVal if maxVal >= 1 else 1,
min=minVal if minVal <= -1 else -1,
fileName=seabornFile,
cmap="RdBu_r"
)
else:
MatplotlibPlots.seabornHeatmapPlot(
correlationMatrix,
labels,
max=maxVal if maxVal >= 1 else 1,
min=minVal if minVal <= 0 else 0,
fileName=seabornFile
)
MatplotlibPlots.dendrogramClusteringPlot(linkageMatrix, labels, dendrogramFile)
htmlCore.line(seabornFile.getEmbeddedImage())
htmlCore.link('PDF of similarity matrix', seabornFile.getURL())
htmlCore.line(dendrogramFile.getEmbeddedImage())
htmlCore.link('PDF of dendrogram', dendrogramFile.getURL())
def plotDistances(cls, distances, galaxyFn, bins, r2, htmlCore):
distanceBins, occurrences = cls.standardizeLineGraph(distances)
distFile = GalaxyRunSpecificFile(['distancegraph.pdf'], galaxyFn)
MatplotlibPlots.pointGraph(x=distanceBins[1:], y=occurrences, fileLocation=distFile,
xlabel='Distances between SNP pairs in LD', ylabel='LD-pair count')
dist = sorted(distances)
histFile = GalaxyRunSpecificFile(['histogram.pdf'], galaxyFn)
MatplotlibPlots.histogramPlot(dist, bins, histFile, 'Distances between SNP pairs in LD')
htmlCore.divider(True)
htmlCore.header('Line plot with distribution of distances between LD pairs, r<sup>2</sup> >= ' + str(r2))
htmlCore.line(distFile.getEmbeddedImage())
htmlCore.link('PDF of distances between tracks here', distFile.getURL())
htmlCore.divider(True)
htmlCore.header('Histogram with distribution of distances between LD pairs, r<sup>2</sup> >= ' + str(r2))
htmlCore.line(histFile.getEmbeddedImage())
htmlCore.link('PDF histogram of distances here', histFile.getURL())
def getSNPFrequencyStats(cls, bins, gSuite, galaxyFn, htmlCore):
rsIDs = set()
snpCount = []
analysisSpec = AnalysisSpec(UniquePointTrackStat)
trackLabels = []
for gSuiteTrack in gSuite.allTracks():
track = Track(gSuiteTrack.trackName)
trackLabels.append(gSuiteTrack.title)
result = doAnalysis(analysisSpec, bins, [track])
if 'Result' in result.getGlobalResult():
observations = result.getGlobalResult()['Result']
snpCount.append(len(observations))
rsIDs.update(observations)
snpcountFile = GalaxyRunSpecificFile(['snpfrequencies.pdf'], galaxyFn)
MatplotlibPlots.pointGraphY(snpCount, snpcountFile, ylabel='SNP counts',
xticks=trackLabels)
snpdistributionFile = GalaxyRunSpecificFile(['snpfreqhistogram.pdf'], galaxyFn)
MatplotlibPlots.histogramRugPlot(snpCount, 10, snpdistributionFile, 'SNP counts')
totalSNPCount = sum(snpCount)
cls.printStats(snpCount, 'track', htmlCore)
htmlCore.line('Total number of SNPs: ' + str(totalSNPCount))
htmlCore.line('Unique SNPs: ' + str(len(rsIDs)))
htmlCore.line('Overlapping rsIDs: ' + str(totalSNPCount - len(rsIDs)))
htmlCore.divider(True)
htmlCore.header('Graph of SNP frequencies in GSuite tracks')
htmlCore.line(snpcountFile.getEmbeddedImage())
htmlCore.link('PDF of SNP frequency graph', snpcountFile.getURL())
htmlCore.divider(True)
htmlCore.header('Histogram of SNP frequencies in GSuite tracks')
htmlCore.line(snpdistributionFile.getEmbeddedImage())
htmlCore.link('PDF of SNP frequency histogram', snpdistributionFile.getURL())
cls.getInteractiveColumnChartWithLabels(snpCount, trackLabels, htmlCore)
def plotDistances(cls, distances, galaxyFn, distCase, htmlCore):
# Plot distance graph
xdata, ydata = cls.standardizeLineGraph(distances)
distFile = GalaxyRunSpecificFile(['distancegraph.pdf'], galaxyFn)
MatplotlibPlots.pointGraph(xdata[1:], ydata, distFile, 'Smallest distance for each point',
'Distance point count')
# Write distance graph
htmlCore.divider(True)
htmlCore.header('Graph of smallest distances for all points ' + distCase + ' tracks in GSuite')
htmlCore.line(distFile.getEmbeddedImage())
htmlCore.link('PDF of distance graph', distFile.getURL())
# Plot distance histograms
dist = sorted(distances)
bins = 20
histFile = GalaxyRunSpecificFile(['histogram.pdf'], galaxyFn)
loghistFile = GalaxyRunSpecificFile(['loghistogram.pdf'], galaxyFn)
MatplotlibPlots.histogramRugPlot(dist, bins, histFile, 'Distances')
MatplotlibPlots.histogramRugPlot(log(dist), bins, loghistFile, 'Log of distances')
helperText = 'The rugs/vertical lines at the bottom show the distribution of point distances.'
# Write distance histograms
htmlCore.divider(True)
htmlCore.header('Histogram of smallest distances for all points ' + distCase +
' tracks in GSuite')
htmlCore.line(helperText)
htmlCore.line(histFile.getEmbeddedImage())
htmlCore.link('PDF of distance histogram', histFile.getURL())
htmlCore.header('Histogram of log of smallest distances for all points ' + distCase +
' tracks in GSuite')
htmlCore.line(helperText)
htmlCore.line(loghistFile.getEmbeddedImage())
htmlCore.link('PDF of log distance histogram', loghistFile.getURL())
# Plot and write interactive bar chart
cls.getInteractiveColumnChart(dist, distCase, htmlCore)
def getLDDistancesOfMultipleRsquares(cls, ldGraphTrack, rSquareThresholds, galaxyFn, htmlCore):
graph = LDExpansions.createRSquareGraph(ldGraphTrack, 0)
positions = LDExpansions.createPositionDict(ldGraphTrack)
ldDistances = []
rSquareLabels = []
bins = []
for rSquare, isSet in rSquareThresholds.items():
if not isSet:
continue
rSquareLabels.append(rSquare)
rSquare = float(rSquare)
distances = cls.findAllDistancesInLD(graph, positions, rSquare, htmlCore)
bins, ldPairCount = cls.standardizeLineGraph(distances)
ldDistances.append(ldPairCount)
graphFile = GalaxyRunSpecificFile(['multipleLines.pdf'], galaxyFn)
MatplotlibPlots.multipleLineGraph(
bins[1:],
ldDistances,
rSquareLabels,
graphFile,
'Distance',
'LD-pair count'
)
if len(bins) == 0:
return
htmlCore.divider(True)
htmlCore.header('Distribution of distances between LD pairs with different thresholds of r<sup>2</sup>')
htmlCore.line(graphFile.getEmbeddedImage())
htmlCore.link('PDF of distances between tracks here', graphFile.getURL())
