def WillItPCR(self, amplicon, f_primer, r_primer):
for_wip = self.SWTm_WillItPCR_primer(amplicon, MB.Antisense(f_primer))
rev_wip = self.SWTm_WillItPCR_primer(amplicon, r_primer)
ret = {}
if for_wip['TmAB'] > 0:
ret['for_Tm'] = for_wip['TmAB']
ret['for_align_score'] = for_wip['align_score']
ret['for_match'] = for_wip['match_str']
ret['for_mis_matches'] = for_wip['mis_matches']
if rev_wip['TmAB'] > 0:
ret['rev_Tm'] = rev_wip['TmAB']
ret['rev_align_score'] = rev_wip['align_score']
ret['rev_match'] = rev_wip['match_str']
ret['rev_mis_matches'] = rev_wip['mis_matches']
return ret
def Score(
self,
scoreMatrix={
'HP': 1000,
'PD': 10,
'GC': 10000,
'rep': 10000,
'Tm': 100,
'CyclePenalty': 1000
}):
###score is from best to worst highest score is worst probe
score = 0
if 'Tm' in scoreMatrix:
score = score + abs(self.Params['TmMin'] -
self.Tm) * scoreMatrix['Tm']
if 'HP' in scoreMatrix:
score = score + self.HPScore * scoreMatrix['HP']
if 'PD' in scoreMatrix:
score = score + self.PDScore * scoreMatrix['PD']
if 'GC' in scoreMatrix:
score = score + self.GCScore * scoreMatrix['GC']
if 'rep' in scoreMatrix:
score = score + self.repScore * scoreMatrix['rep']
if 'PCRGC' in scoreMatrix:
gcpcr = MB.perGC(self.seq[-6:]) / 100 * 6
gcpcr = int(gcpcr)
gcpcrScore = 0
if gcpcr == 0:
gcpcrScore = 3
if gcpcr == 1 or gcpcr == 6:
gcpcrScore = 2
if gcpcr == 2 or gcpcr == 5:
gcpcrScore = 1
score = score + gcpcrScore * scoreMatrix['PCRGC']
##print self.seq + 'gcpcr is ' + str(gcpcr) + ' score = ' + str(score)
# if 'self-Anneal' in scoreMatrix:
# val = self.ComputeSelfAnneal()
# val = max(0, val -30000)
# score = score + val*scoreMatrix['self-Anneal']
if 'CyclePenalty' in scoreMatrix:
cycleIndex = max(
0, (self.SynthCycles - self.Params['MaxSynthCycles']))
score = score + cycleIndex * scoreMatrix['CyclePenalty']
self.score = score
return score
def PureSeqCompare(self, seqA, seqB):
hit = MB.SW(seqA,
seqB,
match=1,
MM=-1,
gapOpen=-2,
gapExtend=-1,
Verbose=Verbose,
DEBUG=0)
#You cannot allow gaps into this formula it does not support it yet.
if Verbose:
sA = hit[0]
sB = hit[1]
matchLst = []
for i in range(len(sA)):
if sA[i] == hit[1][i]:
matchLst.append('|')
else:
matchLst.append('x')
print('PureSeqComparison:\t%s\n%s\n%s\n%s\n' %
(seqA, sA, ''.join(matchLst), sB))
return hit
TM = ThermoVals()
if __name__ == '__main__':
Verbose = 1
s = 'GATCGTAGCTGATCGTAGCTAT'
print('\n\n\nSequenceSimilarity start:' + s)
r = TM.SWTm_SequenceSimilarity('GATCGTAGCTGATCGTAGCTAT',
'GATCGTAGCTTCGTAGCTAT')
print('r is :' + str(r) + '\n\n\n')
t = TM.AreTheySimilar('GATCGTAGCTGATCGTAGCTAT',
'GATCGTAGGGTTCGTAGCTAT',
DNAConc=None,
dTm=10.0)
print('AreTheySimilar: %s' % str(t))
s = 'GATCGTAGCTGATCGTAGCTAT'
print('\n\n\nWillItHyb start:' + s)
r = TM.SWTm_WillItHyb('GATCGTAGCTGATCGTAGCTAT', 'ATAGCTACGA-CAGCTACGATC')
print('r is :' + str(r) + '\n\n\n')
t = TM.MMHybTm(s, Antisense(s), DNAConc=None)
print('MMHybTm: %.2f' % t)
seq = 'CGGGGCGGAAGgactgctccgctccgcgttgacatca'
r = TM.SecStructTm(seq, windowSize=15)
print(str(r))
sTm = MB.HairpinTm(
seq, MinAnneal=4) #This version does not see gaps or mismatches
print(str(sTm))
def InitializeProbeObjectFromFAObj(self):
if Verbose: print(' InitializeProbeObjectFromFAObj():')
self.probeLst = [
self.probeLst[0], self.probeLst[1], self.probeLst[2],
MB.Tm(self.probeLst[1]), 0, 0, 'No_LabelRoot', 'No_OrigFASTALabel'
]
def Antisense(self):
self.label = self.label + '|as'
self.seq = MB.Antisense(self.seq)
def CharacterizeProbe(probeSeq, filtparams={}):
"""CharacterizeProbe
|(probeObj, FilterParams = None, returnLabel = None, Verbose = 1)
|probe object needs to be of the form [label, seq, len, anything else, , , ]
|
|"""
Limits = DefaultProbeFilterParameters
Limits.update(
filtparams) ##this is if you have a special set of conditions
#['ProbeGood','HP','PD','repeatNum','GC','HPstruct','PDstruct','failreason']
MaxHPTm = float(Limits['MaxHPTm'])
MaxPalindrome = float(Limits['MaxPalindrome'])
MaxRepeats = int(Limits['MaxRepeats'])
MaxGC = float(Limits['MaxGC'])
MinGC = float(Limits['MinGC'])
if 'MaxSynthCycles' in Limits:
MaxSynthCycles = int(Limits['MaxSynthCycles'])
else:
MaxSynthCycles = 160
failreason = 'good'
ProbeGood = 1
for base in probeSeq:
if not (base in 'GATCgatc'):
ProbeGood = 0
failreason = 'badBase'
break
if failreason == 'badBase':
return [0, 0, 0, 0, 0, 0, 0, 0, 0]
probeSeqSSLst = MB.SecStruct(probeSeq, MinAnneal=4)
HPLst = []
PDLst = []
for obj in probeSeqSSLst:
if obj[2] > 0:
HPLst.append(obj)
else:
PDLst.append(obj)
PDobj = MB.StabSecStruct(PDLst, Pal=1, OutType=1)
PD = PDobj[0]
PDstruct = PDobj[1]
HPobj = MB.StabSecStruct(HPLst, OutType=1)
HP = HPobj[0]
HPstruct = HPobj[1]
if PD > MaxPalindrome:
ProbeGood = 0
failreason = 'PD > ' + str(MaxPalindrome)
if HP > MaxHPTm:
ProbeGood = 0
failreason = 'HP > ' + str(MaxHPTm)
GC = MB.perGC(probeSeq)
if GC > MaxGC:
ProbeGood = 0
failreason = '%GC > ' + str(MaxGC)
if GC < MinGC:
ProbeGood = 0
failreason = '%GC < ' + str(MinGC)
repeatNum = MB.repeats(probeSeq)
repeatType = int((repeatNum - math.floor(repeatNum)) * 10)
if repeatNum > MaxRepeats:
ProbeGood = 0
failreason = 'repeats > ' + str(MaxRepeats) + '-' + str(repeatType)
SynthCycles = CyclesToSynth(probeSeq)
if SynthCycles > MaxSynthCycles:
ProbeGood = 0
failreason = 'SynthCycles %i>%i(max)' % (SynthCycles, MaxSynthCycles)
probeObj = [
SynthCycles, ProbeGood, HP, PD, repeatNum, GC, HPstruct, PDstruct,
failreason
]
#print str(probeObj)
return probeObj