def pictograph(options, vData, exonDict, bedRow, traits, region, vcfIDs):
'''Creates a plot based upon a set of options, vcf information, a list of exon tuples, a bed of UCSC genomes, and a list of traits.'''
start, stop = tuplesDomain((region[1], region[2]), options.introns, exonDict, bedRow)# change the region specified to basepair values
dimensions = (start, stop, options.ymin * -1, options.ymax)
exoncolors=(options.exoncolor1, options.exoncolor2)
plotSize = (options.width, options.height)
ax1, ax2, fig = SetupPlot(plotSize, dimensions, options.plotTitle, region[0], options.codons) # initialize the graph, with proper range and choices
vDataFiltered = [ vmarker for vmarker in vData if vmarker.checkFilter(options.filterList) ]
if options.MAF:
#a = max( [ vmarker.get_maf() for vmarker in vDataFiltered ] )
vDataFiltered = [ vmarker for vmarker in vDataFiltered if vmarker.get_maf() < options.MAF ]
#b = max( [ vmarker.get_maf() for vmarker in vDataFiltered ] )
#print a, '->', b
tableKeys = []
traitIDs = [ str(i) for i in traits[options.id] ]
# infoDict ={}
colorMap = {}
colorKeys = []
i = 0
if options.colorFlags:
colorKeys = options.colorFlags.split(',')
colorKeys.append(None)
for flag in colorKeys:
colorMap[flag] = options.palette[i%len(options.palette)]
i = i + 1
elif options.colorInfo:
colorKeys = set( [ gzutils.itemOrDefault( m.get_info(options.colorInfo), 0, "N/A") for m in vDataFiltered ] )
colorKeys = colorKeys - set(['N/A'])
colorKeys = sorted( list(colorKeys) )
colorKeys.append('N/A')
for key in colorKeys:
colorMap[key] = options.palette[i%len(options.palette)]
i = i + 1
if len(colorMap) > len(options.palette):
print "More levels than colors in palette. Recycling colors."
#print [(k, colorMap[k]) for k in colorKeys]
for marker in vDataFiltered:
# check to see if the gene is in the exon. If it is, create a cross table, draw the dots and add them to the graph
if (exonDict.has_key(int(marker.get_pos()))):
organizedList=CrossTable.cullList(vcfIDs, traitIDs, traits[options.groups])# organize the traits into a list, returning a list of case/control/None corresponding to the vcfIDs
xTable = CrossTable.xTable(organizedList, marker.get_genotypes())
if len( [ t for t in tableKeys if t != None ] ) < 2: # check for case/control elements in our data
tableKeys = [ k for k in xTable.getTable().keys() if k != None ]
if options.colorFlags:
markerInfo = marker.info_is_present(colorKeys)
elif options.colorInfo:
try:
markerInfo = marker.get_info(options.colorInfo)[0] ### better name later?
except IndexError:
markerInfo = 'N/A'
else:
markerInfo = 'N/A' ## marker.get_info()[0] ### better default later?
# if not infoDict.has_key(markerInfo): # if the info is not in our dict
# if len(infoDict)==len(options.palette): # check to see if we've used our whole palette
# print "No more colors in palette. Reusing colors."
# infoDict[markerInfo] = options.palette[len(infoDict)%len(options.palette)]
# tempColors = (infoDict[markerInfo], infoDict[markerInfo])
tempColors = (colorMap[markerInfo], colorMap[markerInfo])
if len(tableKeys) > 1:
if marker.is_indel(): # if this gene is an indel, draw triangles instead
drawings = patchPlot(xTable.getTable(), exonDict[int(marker.get_pos())], tempColors, "triangle", tableKeys)
else:
drawings = patchPlot(xTable.getTable(), exonDict[int(marker.get_pos())], tempColors, options.shape, tableKeys)
ax1.add_collection(drawings)
print "%s markers plotted after filtering."%len(vDataFiltered)
if tableKeys != None and len(tableKeys) > 1: ax1.set_ylabel("%s %s"%(tableKeys[0], tableKeys[-1]))# make y-axis label as needed
if not options.nolegend and (options.colorInfo or options.colorFlags):
# makeLegend(ax1, infoDict)
makeLegend(ax1, colorMap, colorKeys)
if bedRow!=[]:# as long as we're actually drawing exons (so a gene, not just a region)
exonRect = drawExon(bedRow.get_exons(), exonDict, exoncolors, options.introns) # draw the exons, adding them to the plot
ax2.add_collection(exonRect)
ax2.add_line(Line2D([-10000000000, 10000000000], [0, 0], linewidth=1, color='black'))
if options.png:
saveFile = graphName(options.prefix, "results", ".png")# if user has chosen to save graph as a png, save it
fig.savefig(saveFile)
print "Saved as %s\n"%saveFile
if options.pdf: # if user has chosen to save graph as a pdf, save it
saveFile = graphName(options.prefix, "results", ".pdf")
fig.savefig(saveFile)
print "Saved as %s\n"%saveFile
if options.graph: # if user has chosen to show the graph, then show it
plt.show()
def get_maf(self): tally = self.genotypeTally() af1 = 2 * itemOrDefault(tally,'0/0',0) + itemOrDefault(tally,'0/1',0) af2 = 2 * itemOrDefault(tally,'1/1',0) + itemOrDefault(tally,'0/1',0) return ( min([af1,af2]) / float(af1 + af2) )
