DNA序列局部比对（Smith–Waterman algorithm）

生物信息原理作业第三弹：DNA序列局部比对，利用Smith–Waterman算法，python3.6代码实现。

实例以及原理均来自https://en.wikipedia.org/wiki/Smith%E2%80%93Waterman_algorithm。

DNA序列局部比对

转载请保留出处！

 import numpy as np
 import pandas as pd
 sequence1 = 'TGTTACGG'
 sequence2 = 'GGTTGACTA'
 s1 = ''
 s2 = ''
 gap = -2
 score_matrix = pd.read_excel('score.xlsx')      #匹配得分
 print(score_matrix)
 best_matrix = np.empty(shape= (len(sequence2)+1,len(sequence1)+1),dtype = int)
 def get_match_score(s1,s2):
     score = score_matrix[s1][s2]
     return score

 def get_matrix_max(matrix):                    #得到最大分数下标
     Max = matrix.max()
     for i in range(len(sequence2)+1):
         for j in range(len(sequence1)+1):
             if matrix[i][j] == Max:
                 return (i,j)

 for i in range(len(sequence2)+1):
     for j in range(len(sequence1)+1):
         if i == 0 or j == 0:
             best_matrix[i][j] = 0
         else:
             match = get_match_score(sequence2[i-1],sequence1[j-1])
             gap1_score = best_matrix[i-1][j] + gap
             gap2_score = best_matrix[i][j-1] + gap
             match_score = best_matrix[i-1][j-1]+match
             score = max(gap1_score,gap2_score,match_score)
             if score>0:
                 best_matrix[i][j] = score
             else:
                 best_matrix[i][j] = 0
 print(best_matrix)

 #traceback
 i,j = get_matrix_max(best_matrix)
 while(best_matrix[i][j]!= 0):
     match = get_match_score(sequence2[i-1],sequence1[j-1])
     if i>0 and j>0 and best_matrix[i][j] == best_matrix[i-1][j-1]+match:
         s1 += sequence1[j-1]
         s2 += sequence2[i-1]
         i-=1;j-=1
     elif i>0 and best_matrix[i,j] == best_matrix[i-1,j]+gap:
         s1+='-'
         s2+=sequence2[i-1]
         i-=1
     else:
         s1+=sequence1[j-1]
         s2+='-'
         j-=1
 print(s1[::-1]+'\n'+s2[::-1])

感觉我的得分矩阵写成Excel不必要，等我熟悉一下Numpy和Python命令行之后会修改的。