def load(self):
orderedList, totalSequences = run_clustal.clustalw(
directory='./Sequences').runSetup()
paramsList = []
identityList = []
for element in orderedList:
paramsListElement, identity, loopIndexElement, alpha, beta = run_clustal.sequences(
element).runAnalysis()
paramsList.append(paramsListElement)
identityList.append(identity)
self.paramsList = paramsList
self.identityList = identityList
self.loopIndexElement = loopIndexElement
self.alpha = alpha
self.beta = beta
self.totalSequences = totalSequences
cutOff = 40
newParams, mutationalityList, loopIndexElement, alpha, beta = run_clustal.sortParams(
self.paramsList, self.identityList, self.loopIndexElement,
self.alpha, self.beta, cutOff, 1, self.totalSequences)
try:
delete(analyse)
except:
pass
self.analyse = run_clustal.analysis(newParams, 1, mutationalityList,
loopIndexElement, alpha, beta)
self.onInfo("Sequences Loaded.")
self.runButton.destroy()
self.initUI()
def onUpdate(self, cutOff): newParams, mutationalityList = run_clustal.sortParams(self.paramsList, self.identityList, cutOff, 1, self.totalSequences) try: delete(analyse) except: pass self.analyse = run_clustal.analysis(newParams, 1, mutationalityList, None, None, None, None) self.mutationalityListCut = mutationalityList print len(newParams), "sequences to be included into the plot."
def load(self):
orderedList, totalSequences = run_clustal.clustalw(
directory='./Sequences').runSetup()
paramsList = []
identityList = []
mutationDistribution = []
for element in orderedList:
paramsListElement, identity, loopIndexElement, alpha, beta, custom = run_clustal.sequences(
element, self.groupUserDefined).runAnalysis()
paramsList.append(paramsListElement)
identityList.append(identity)
mutationOccurence = {}
for sequence in identityList:
numberOfMutations = len(sequence) - np.sum(sequence)
# print "This sequence has", numberOfMutations
# print mutationOccurence
if numberOfMutations in mutationOccurence:
mutationOccurence[numberOfMutations] += 1
else:
mutationOccurence[numberOfMutations] = 1
# print mutationOccurence
###########################################################################################
for residues in range(len(identityList[0])):
mutationDistribution.append(0)
for sequence in range(len(identityList)):
for residue in range(len(identityList[sequence])):
if identityList[sequence][residue] == 0:
# print "Mutation found in", sequence, residue
mutationDistribution[residue] += 1
############################################################################################
self.paramsList = paramsList
self.identityList = identityList
self.loopIndexElement = loopIndexElement
self.alpha = alpha
self.beta = beta
self.totalSequences = totalSequences
self.mutationOccurence = mutationOccurence
self.mutationDistribution = mutationDistribution
cutOff = 60
newParams, mutationalityList, loopIndexElement, alpha, beta = run_clustal.sortParams(
self.paramsList, self.identityList, self.loopIndexElement,
self.alpha, self.beta, cutOff, 1, self.totalSequences)
try:
delete(analyse)
except:
pass
self.analyse = run_clustal.analysis(newParams, 1, mutationalityList,
loopIndexElement, alpha, beta,
self.groupUserDefined)
self.onInfo("Sequences Loaded.")
self.runButton.destroy()
self.initUI()
def onUpdate(self, cutOff):
newParams, mutationalityList, loopIndexElement, alpha, beta = run_clustal.sortParams(
self.paramsList, self.identityList, self.loopIndexElement,
self.alpha, self.beta, cutOff, 1, self.totalSequences)
try:
delete(analyse)
except:
pass
self.analyse = run_clustal.analysis(newParams, 1, mutationalityList,
loopIndexElement, alpha, beta)
print len(newParams)