def question2(): align_human = "HSGVNQLGGVFVNGRPLPDSTRQKIVELAHSGARPCDISRILQVSNGCVSKILGRYYETGSIRPRAIGGSKPRVATPEVVSKIAQYKRECPSIFAWEIRDRLLSEGVCTNDNIPSVSSINRVLRNLASEK-QQ".replace("-","") align_fruitfly = "HSGVNQLGGVFVGGRPLPDSTRQKIVELAHSGARPCDISRILQVSNGCVSKILGRYYETGSIRPRAIGGSKPRVATAEVVSKISQYKRECPSIFAWEIRDRLLQENVCTNDNIPSVSSINRVLRNLAAQKEQQ" consensus = read_protein(CONSENSUS_PAX_URL) scoring_matrix = read_scoring_matrix(PAM50_URL) alignment_matrix = compute_alignment_matrix(align_human, consensus, scoring_matrix, True) (score, align_human_consensus, align_consensus) = compute_global_alignment(align_human, consensus, scoring_matrix, alignment_matrix) print compare_sequence(align_human_consensus, align_consensus) print align_human_consensus print align_consensus print (score - 51.956) / 7.169 alignment_matrix = compute_alignment_matrix(align_fruitfly, consensus, scoring_matrix, True) (score, align_fruitfly_consensus, align_consensus) = compute_global_alignment(align_fruitfly, consensus, scoring_matrix, alignment_matrix) print compare_sequence(align_fruitfly_consensus, align_consensus) print align_fruitfly_consensus print align_consensus print (score - 51.956) / 7.169
def calculate_distance(checked_word, word, scoring_matrix): alignment_matrix = compute_alignment_matrix(checked_word, word, scoring_matrix, True) (score, _, _) = compute_global_alignment(checked_word, word, scoring_matrix, alignment_matrix) return len(checked_word) + len(word) - score
def test01(self): alphabet= "ACTG" matrix = build_scoring_matrix(alphabet, 10,4,-2) S = compute_alignment_matrix("AA", "TAAT", matrix, True) (score,x,y) = compute_global_alignment("AA", "TAAT", matrix, S) self.assertEqual(score,16) self.assertEquals(x,"-AA-") self.assertEquals(y,"TAAT")
def test01(self): alphabet = "ACTG" matrix = build_scoring_matrix(alphabet, 10, 4, -2) S = compute_alignment_matrix("AA", "TAAT", matrix, True) (score, x, y) = compute_global_alignment("AA", "TAAT", matrix, S) self.assertEqual(score, 16) self.assertEquals(x, "-AA-") self.assertEquals(y, "TAAT")
score_mat = seq_align.build_scoring_matrix(set(["A", "T", "G", "C"]), 10, -10, 0) # In[33]: seq_recs = SeqIO.parse("/Users/richard/Downloads/rosalind_lcsq.txt", "fasta") seq_x, seq_y = [str(seq.seq) for seq in seq_recs] # In[34]: align_mat = seq_align.compute_alignment_matrix(seq_x, seq_y, score_mat, True) # In[35]: _, align1, align2 = seq_align.compute_global_alignment(seq_x, seq_y, score_mat, align_mat) print align1 print align2 # In[36]: res = "".join([align1[i] for i in range(len(align1)) if align1[i] != "-" and align2[i] != "-"]) # In[37]: with open("/Users/richard/Downloads/output", "w") as file: file.write(res)