update

bioinfo/sum.py

@@ -0,0 +1,54 @@
+import numpy as np
+from jaxtyping import Float, Array
+
+def needleman_wunsch(seq1: str, seq2: str,
+                     match_score: int = 1,
+                     mismatch_penalty: int = -1,
+                     gap_penalty: int = -2) -> tuple[str, str, Float[Array, "len_seq1+1 len_seq2+1"]]:
+    # 初始化矩阵
+    len_seq1, len_seq2 = len(seq1), len(seq2)
+    score_matrix: Float[Array, "len_seq1+1 len_seq2+1"] = np.zeros((len_seq1 + 1, len_seq2 + 1))
+
+    # 初始化第一行和第一列
+    for i in range(len_seq1 + 1):
+        score_matrix[i][0] = i * gap_penalty
+    for j in range(len_seq2 + 1):
+        score_matrix[0][j] = j * gap_penalty
+
+    # 填充得分矩阵
+    for i in range(1, len_seq1 + 1):
+        for j in range(1, len_seq2 + 1):
+            match = score_matrix[i - 1][j - 1] + (match_score if seq1[i - 1] == seq2[j - 1] else mismatch_penalty)
+            delete = score_matrix[i - 1][j] + gap_penalty
+            insert = score_matrix[i][j - 1] + gap_penalty
+            score_matrix[i][j] = max(match, delete, insert)
+
+    # 回溯得到比对结果
+    align1, align2 = '', ''
+    i, j = len_seq1, len_seq2
+    while i > 0 or j > 0:
+        current_score = score_matrix[i][j]
+        if i > 0 and j > 0 and (current_score == score_matrix[i - 1][j - 1] + (match_score if seq1[i - 1] == seq2[j - 1] else mismatch_penalty)):
+            align1 = seq1[i - 1] + align1
+            align2 = seq2[j - 1] + align2
+            i -= 1
+            j -= 1
+        elif i > 0 and (current_score == score_matrix[i - 1][j] + gap_penalty):
+            align1 = seq1[i - 1] + align1
+            align2 = '-' + align2
+            i -= 1
+        else:
+            align1 = '-' + align1
+            align2 = seq2[j - 1] + align2
+            j -= 1
+
+    return align1, align2, score_matrix
+
+# 测试示例
+seq1 = "GATTACA"
+seq2 = "GCATGCU"
+alignment = needleman_wunsch(seq1, seq2)
+print("Aligned Sequences:")
+print(alignment[0])
+print(alignment[1])
+print("Alignment Score:", alignment[2])