frequent_pattern.py

def hamming_distance(sequence_1, sequence_2):
   """Count the number of differences between equal length strings sequence_1 and sequence_2"""
   diffs = 0
   for character_1, character_2 in zip(sequence_1, sequence_2):
       if character_1 != character_2:
           diffs += 1
   return diffs

def most_frequent_pattern(dna, block_size, mistmaches_allowed):
    num_sequences = len(dna) - 10
    matchings = {}
    for i in xrange(num_sequences):
        matchings[i] = []
        pattern = dna[i:i + block_size]
        for j in range(num_sequences):
            if i == j:
                break
            sequence = dna[j:j + block_size]
            distance = hamming_distance(pattern, sequence)
            if distance <= mistmaches_allowed:
                matchings[i].append(pattern)

    z = sorted(matchings, key=lambda m: len(matchings[m]))
    # print(dna[z[-1]:z[-1] + block_size])
    # result = matchings[z[-1]]
    result = dna[z[-1]:z[-1] + block_size]
    return result

if __name__ == '__main__':
    dna = 'CACAGTAGGCGCCGGCACACACAGCCCCGGGCCCCGGGCCGCCCCGGGCCGGCGGCCGCCGGCGCCGGCACACCGGCACAGCCGTACCGGCACAGTAGTACCGGCCGGCCGGCACACCGGCACACCGGGTACACACCGGGGCGCACACACAGGCGGGCGCCGGGCCCCGGGCCGTACCGGGCCGCCGGCGGCCCACAGGCGCCGGCACAGTACCGGCACACACAGTAGCCCACACACAGGCGGGCGGTAGCCGGCGCACACACACACAGTAGGCGCACAGCCGCCCACACACACCGGCCGGCCGGCACAGGCGGGCGGGCGCACACACACCGGCACAGTAGTAGGCGGCCGGCGCACAGCC'
    block_size = 10
    mistmaches_allowed = 2
    frequent_pattern = most_frequent_pattern(dna, block_size, mistmaches_allowed)
    print("Result: {}".format(frequent_pattern))
    # result: GCGCACACAC