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_local_alignment("AA", "TAAT", matrix, S)
self.assertEqual(score, 20)
self.assertEquals(x, "AA")
self.assertEquals(y, "AA")
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_local_alignment("AA", "TAAT", matrix, S)
self.assertEqual(score,20)
self.assertEquals(x,"AA")
self.assertEquals(y,"AA")
def question1():
human_eyeless_protein = read_protein(HUMAN_EYELESS_URL)
fruitfly_eyeless_protein = read_protein(FRUITFLY_EYELESS_URL)
scoring_matrix = read_scoring_matrix(PAM50_URL)
alignment_matrix = compute_alignment_matrix(human_eyeless_protein, fruitfly_eyeless_protein, scoring_matrix, False)
(score, align_human, align_fruitfly) = compute_local_alignment(human_eyeless_protein, fruitfly_eyeless_protein, scoring_matrix, alignment_matrix)
print score
print align_human
print align_fruitfly
def generate_null_distribution(seq_x, seq_y, scoring_matrix, num_trials):
scoring_distributions = {}
for _ in range(0,num_trials):
l_seq_y = list(seq_y)
random.shuffle(l_seq_y)
alignment_matrix = compute_alignment_matrix(seq_x, l_seq_y, scoring_matrix, False)
(score, _, _) = compute_local_alignment(seq_x, l_seq_y, scoring_matrix, alignment_matrix)
if (score in scoring_distributions):
scoring_distributions[score] = scoring_distributions[score] + 1
else:
scoring_distributions[score] = 1
return scoring_distributions
