def get_activation(sequences, concentrations, params):
model = nu.Model(material='dna',
celsius=params['temperature'],
sodium=params['sodium'],
magnesium=params['magnesium'])
# Define strands and sequences
probeF = nu.Strand(sequences['probeF'], name='probeF')
probeQ = nu.Strand(sequences['probeQ'], name='probeQ')
sink = nu.Strand(sequences['sink'], name='sink')
sinkC = nu.Strand(sequences['sinkC'], name='sinkC')
non_mut_target = nu.Strand(sequences['non_mut_target'],
name='non_mut_target')
mut_target = nu.Strand(sequences['mut_target'], name='mut_target')
# Define 3 tubes: one without target (initial), one with mutated target (mut), and one with non-mutated target (non_mut)
initial_state = nu.Tube(strands={
probeF: concentrations['probeF'],
probeQ: concentrations['probeQ'],
sink: concentrations['sink'],
sinkC: concentrations['sinkC']
},
complexes=nu.SetSpec(
max_size=2,
include=[[probeF, probeQ, sink, sinkC]]),
name='initial_state')
mut_state = nu.Tube(strands={
probeF: concentrations['probeF'],
probeQ: concentrations['probeQ'],
sink: concentrations['sink'],
sinkC: concentrations['sinkC'],
mut_target: concentrations['mut_target']
},
complexes=nu.SetSpec(
max_size=2,
include=[[probeF, probeQ, sink, sinkC,
mut_target]]),
name='mut_state')
non_mut_state = nu.Tube(strands={
probeF: concentrations['probeF'],
probeQ: concentrations['probeQ'],
sink: concentrations['sink'],
sinkC: concentrations['sinkC'],
non_mut_target: concentrations['non_mut_target']
},
complexes=nu.SetSpec(max_size=2,
include=[[
probeF, probeQ, sink,
sinkC, non_mut_target
]]),
name='non_mut_state')
# Compute proportion of probe which is active in each tube
result = nu.tube_analysis(tubes=[initial_state, mut_state, non_mut_state],
compute=['pairs', 'mfe'],
model=model)
initial_activation = parse_nupack_output(result, 'initial_state',
concentrations)
mut_activation = parse_nupack_output(result, 'mut_state', concentrations)
non_mut_activation = parse_nupack_output(result, 'non_mut_state',
concentrations)
return initial_activation, mut_activation, non_mut_activation
def analysis_all(self):
count = self.len_g1 + self.len_g2
strands = self.get_strands()
my_model = Model(material='dna', celsius=self.temp)
t1 = Tube(strands=strands,
complexes=SetSpec(max_size=count),
name='t1') # complexes defaults to [A, B]
tube_results = tube_analysis(tubes=[t1], model=my_model)
def get_strand_tube_all(self):
# 获取试管中只有两条基因片段的所有情况
strands = {}
for i in range(1, len(self.oligo) - 1):
strands[Strand(self.oligo[i][1],
name=self.oligo[i][0])] = self.oligo_conc
strands[Strand(self.oligo[0][1],
name=self.oligo[0][0])] = self.primer_conc
strands[Strand(self.oligo[-1][1],
name=self.oligo[-1][0])] = self.primer_conc
my_model = Model(material='dna', celsius=self.temp)
t = Tube(strands=strands, complexes=SetSpec(max_size=2),
name='t') # complexes defaults to [A, B]
tube_results = tube_analysis(tubes=[t], model=my_model)
all_conc = {}
for my_complex, conc in tube_results.tubes[
t].complex_concentrations.items():
all_conc[my_complex.name] = conc # 反应后每个试管中DNA的浓度
all_conc = sorted(all_conc.items(), key=lambda d: d[1],
reverse=True) # 排序
error = {}
for key, val in all_conc:
if key.count('+') == 1 and val > self.first_check:
tem_split = key[1:-1].split('+') # # 先去除括号，在根据+分割字符串
t1 = tem_split[0][1:]
t2 = tem_split[1][1:]
# print(t1, t2)
# print(t1.isdigit(), t2.isdigit())
if not t1.isdigit() or not t2.isdigit():
# 处理含有primer的片段，都是错配的
# primer+pirmer, primer+x , x+primer
error['{0}, {1}'.format(tem_split[0], tem_split[1])] = val
elif tem_split[0][0] == tem_split[1][0]: # 错配
# Rx+Rx ; Fx+Fx
error['{0}, {1}'.format(tem_split[0], tem_split[1])] = val
elif tem_split[0][0] == 'F' and int(t1) - int(t2) not in [
0, 1
]:
error['{0}, {1}'.format(tem_split[0], tem_split[1])] = val
elif tem_split[0][0] == 'R' and int(t1) - int(t2) not in [
0, -1
]:
error['{0}, {1}'.format(tem_split[0], tem_split[1])] = val
# 判断条件有待改进
elif val < self.first_check: #
break
print(error)
return error
def verification_two(self, list1):
# 验证错配的是否有问题
set1 = set()
strands = {}
for i in range(len(list1)):
for j in range(len(list1[i])):
if j == 0:
set1.add(list1[i][j])
strands[Strand(
self.gene_list[list1[i][j] - 1],
name="E:{1}:{0}".format(list1[i][j],
i))] = self.c_gene * 2 # 改正浓度
elif Strand(self.gene_list[list1[i][j] - 1],
name=str(list1[i][j])) in strands.keys():
strands[Strand(self.gene_list[list1[i][j] - 1],
name=str(list1[i][j]))] = self.c_gene * 2
else:
strands[Strand(self.gene_list[list1[i][j] - 1],
name=str(list1[i][j]))] = self.c_gene
tube = Tube(strands=strands,
complexes=SetSpec(max_size=len(list1)),
name="test")
my_model = Model(material='dna', celsius=self.temp)
tube_results = tube_analysis(tubes=[tube], model=my_model)
all_conc = {}
# print(tube_results)
# print("____________-")
for my_complex, conc in tube_results.tubes[
tube].complex_concentrations.items():
all_conc[my_complex.name] = conc
name = my_complex.name[1:-1]
# if name.count("E") == 2: #
if name.count("E") == len(list1) and conc > self.second_check: #
name_list = name.split("+")
set_t = set()
for i in range(len(list1)):
set_t.add(name_list[i][2])
if len(set_t) == len(list1) and set_t == set1: # 只关注错配的那几条
# print(name, conc)
return False
# print(name, conc)
new_conc = sorted(all_conc.items(), key=lambda d: d[1], reverse=True)
def analysis_two(self):
my_model = Model(material='dna', celsius=self.temp) # 温度
tubes = self.get_strands_tube_tow() # 得到每个试管中都有两条DNA单链
tube_results = tube_analysis(tubes=tubes, model=my_model)
all_conc = {}
for t in tubes:
for my_complex, conc in tube_results.tubes[
t].complex_concentrations.items():
all_conc[my_complex.name] = conc # 反应后每个试管中DNA的浓度
all_conc = sorted(all_conc.items(), key=lambda d: d[1],
reverse=True) # 排序
error = {} # 怀疑是错配的
# 验证
for k, v in all_conc:
if k.count("+") == 1 and v > self.first_check: # 将浓度换成输入的浓度
# 根据：分割k， 然后根据名字具有顺序关系，然后确定是不是正确的配对
tem_split = k.split('+')
t1 = int(tem_split[0].split(':')[1][1:]) # 单链序号
t2 = int(tem_split[1].split(':')[1][1:-1])
if t1 > t2:
t1, t2 = t2, t1
if t2 - t1 - self.len_g1 not in [-1, 0]: # 错配
ste = '{0},{1}'.format(t1, t2)
if ste in error and v < error[ste]:
continue
else:
error[ste] = v
elif v < self.first_check: #
break
# 找出那两个的相邻的放到一起，然后反应，看下最后的结果
# error_end = [] # 经过校验后还是错配的
# for enu in error:
# str = enu.split(',')
# tem_err_list = [self.get_tube(int(str[0])), self.get_tube(int(str[1]))]
# if self.verification_two(tem_err_list):
# error_end.append(enu)
tem_info = {}
for key, val in error.items():
arr = key.split(',')
arr = [int(i) for i in arr]
if arr[0] >= self.len_g1:
str1 = 'R{0}'.format(arr[0] - self.len_g1)
else:
str1 = 'F{0}'.format(arr[0])
if arr[1] >= self.len_g1:
str2 = 'R{0}'.format(arr[1] - self.len_g1)
else:
str2 = 'F{0}'.format(arr[1])
tem_info[str1 + ',' + str2] = val
# print(len(tem_info), tem_info)
# print("目标{0},list1:{1},list2:{2}".format(self.len1, self.len_g1, self.len_g2))
# print("出错的{0},{1}".format(len(error), error))
# print("最终检测还是出错的{0}".format(error_end))
# print('总数{0}'.format(len(all_conc)))
return tem_info
def analysis_three(self):
my_model = Model(material='dna', celsius=self.temp)
tubes = self.get_strands_tube_three() # 得到每个试管中都有两条DNA单链
start = time.time()
tube_results = tube_analysis(tubes=tubes, model=my_model)
print("analysis time:{0}".format(time.time() - start))
all_conc = {} # 记录结果
for t in tubes:
for my_complex, conc in tube_results.tubes[
t].complex_concentrations.items():
all_conc[my_complex.name] = conc # 反应后每个试管中DNA的浓度
all_conc = sorted(all_conc.items(), key=lambda d: d[1],
reverse=True) # 排序
error = {} # 怀疑是错配的
k_cou = 0 # 记录浓度大于某个值的
for k, v in all_conc:
if k.count("+") == 2 and v > self.first_check: # 将浓度换成输入的浓度
k_cou += 1
# 根据：分割k， 然后根据名字具有顺序关系，然后确定是不是正确的配对
tem_split = k.split('+')
t1 = int(tem_split[0].split(':')[1][1:])
t2 = int(tem_split[1].split(':')[1][1:])
t3 = int(tem_split[2].split(':')[1][1:-1])
set_t = {abs(t1 - t2), abs(t1 - t3), abs(t2 - t3)}
if set_t != {1, self.len_g1, self.len_g1 - 1}:
tem_arr = [t1, t2, t3]
tem_arr.sort()
key = ''
for i in tem_arr:
if i >= self.len_g1:
key = key + 'R{0},'.format(i - self.len_g1)
else:
key = key + 'F{0},'.format(i)
key = key[:-1]
if key in error and v < error[key]:
continue
else:
error[key] = v
elif v < self.first_check: #
break
# second check
error_end = [] # 经过校验后还是错配的
# 添加验证
# print("验证:{0},{1},{2}".format(t1, t2, t3))
# tem_err_list = self.get_tube(t1)
# tem_err_list.extend(self.get_tube(t2))
# tem_err_list.extend(self.get_tube(t3))
# if self.verification_two(tem_err_list):
# error_end.append(k)
# print("目标:{0},list1:{1},list2:{2}".format(int(self.len1 / 2), self.len_g1, self.len_g2))
print("出错的:{0},{1}".format(len(error), error))
# print("最终检测还是出错的{0}".format(error_end))
# print("浓度大于1e-9数:{0}".format(k_cou))
# print('总数:{0}'.format(len(all_conc)))
return error