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)