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d_neighbours.py
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d_neighbours.py
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def Neighbours(pattern,d):
if d==0:
return pattern
if len(pattern)==1:
return {'A','C','G','T'}
Neighborhood=set()
total_neighbours=set()
SuffixNeighbors=Neighbours(pattern[1:],d)
for x in SuffixNeighbors:
if HammingDistance(pattern[1:],x)<d:
for z in 'ACGT':
Neighborhood.add(z+x)
else:
Neighborhood.add(pattern[0]+x)
return Neighborhood
def HammingDistance(pattern1,pattern2):
cn=0
for u in range(len(pattern1)):
if pattern1[u]!=pattern2[u]:
cn+=1
return cn
def reverse_compliment(dna):
s=''
dic={'A':'T','T':'A','C':'G','G':'C'}
for i in reversed(range(len(dna))):
s+=dic[dna[i]]
return s
if __name__ == "__main__":
text=raw_input()
k,d=raw_input().split()
k,d=int(k),int(d)
possible_k_mers=[]
y=len(text)-k+1
maxi=0
for i in range(y):
possible_k_mers.extend(list(Neighbours(text[i:i+k],d)))
count_k_mer_frequency=dict([(k_mer,0) for k_mer in possible_k_mers])
for k_mer in possible_k_mers:
reverse_mer=reverse_compliment(k_mer)
count_k_mer_frequency[reverse_mer]=0
for i in range(y):
for k_mer in Neighbours(text[i:i+k],d):
count_k_mer_frequency[k_mer]+=1
for k_mer in possible_k_mers:
reverse_mer=reverse_compliment(k_mer)
count_k_mer_frequency[k_mer]+=count_k_mer_frequency[reverse_mer]
count_k_mer_frequency[reverse_mer]=count_k_mer_frequency[k_mer]
max_frequency=max(count_k_mer_frequency.values())
frequent_words=[]
for k_mer in count_k_mer_frequency:
if count_k_mer_frequency[k_mer]==max_frequency:
frequent_words.append(k_mer)
for key in frequent_words:
print key,