def question2():
scoring_matrix =read_scoring_matrix(PAM50_URL)
human = read_protein(HUMAN_EYELESS_URL)
fly = read_protein(FRUITFLY_EYELESS_URL)
# for question 3
# acids = 'ACBEDGFIHKMLNQPSRTWVYXZ'
# hlen = len(human)
# flen = len(fly)
# human_random, fly_random = '', ''
# for dummy_i in xrange(hlen):
# human_random = human_random + human[random.randint(1,23)]
# for dummy_i in xrange(flen):
# fly_random = fly_random + fly[random.randint(1,23)]
# human = human_random
# fly = fly_random
consensusPAX = read_protein(CONSENSUS_PAX_URL)
alignment_matrix = student.compute_alignment_matrix(human, fly, scoring_matrix, False)
local_result = student.compute_local_alignment(human, fly, scoring_matrix, alignment_matrix)
local_human = ''.join(local_result[1].split('-'))
local_fly = ''.join(local_result[2].split('-'))
human_P = student.compute_alignment_matrix(local_human,consensusPAX,scoring_matrix, True)
human_result = student.compute_global_alignment(local_human,consensusPAX, scoring_matrix, human_P)
fly_P = student.compute_alignment_matrix(local_fly,consensusPAX, scoring_matrix, True)
fly_result = student.compute_global_alignment(local_fly,consensusPAX, scoring_matrix, fly_P)
total = len(consensusPAX)
human_count, fly_count =0, 0
for dummy_i in xrange(total):
if human_result[1][dummy_i] == human_result[2][dummy_i]:
human_count += 1
if fly_result[1][dummy_i] ==fly_result[2][dummy_i]:
fly_count += 1
print human_count * 1.0 / total
print fly_count * 1.0 / total
def check_spelling(checked_word, dist, word_list):
alphabet = set('abcdefghijklmnopqrstuvwxyz')
scoring_matrix = student.build_scoring_matrix(alphabet, 2, 1, 0)
result = list()
for word in word_list:
align = student.compute_alignment_matrix(checked_word, word, scoring_matrix, True)
scores = student.compute_global_alignment(checked_word, word, scoring_matrix, align)
if (len(checked_word) + len(word) - scores[0]) <= dist:
result.append(word)
return result
def question2():
""" determine global alignment of consensusPAX
with local human and frfly sequences
"""
# load sequences and scoring matrix
score_matrix = read_scoring_matrix(PAM50_URL)
human_seq = "HSGVNQLGGVFVNGRPLPDSTRQKIVELAHSGARPCDISRILQVSNGCVSKILGRYYETGSIRPRAIGGSKPRVATPEVVSKIAQYKRECPSIFAWEIRDRLLSEGVCTNDNIPSVSSINRVLRNLASEKQQ"
frfly_seq = "HSGVNQLGGVFVGGRPLPDSTRQKIVELAHSGARPCDISRILQVSNGCVSKILGRYYETGSIRPRAIGGSKPRVATAEVVSKISQYKRECPSIFAWEIRDRLLQENVCTNDNIPSVSSINRVLRNLAAQKEQQ"
consensus_pax = read_protein(CONSENSUS_PAX_URL)
# compute human and fruitfly global alignment matrix with consensus pax
human_align_matrix = student.compute_alignment_matrix(human_seq, consensus_pax, score_matrix, True)
frfly_align_matrix = student.compute_alignment_matrix(frfly_seq, consensus_pax, score_matrix, True)
# compute human and fruitfly global alignment sequences
score_human, human_align, consensus_align = student.compute_global_alignment(human_seq, consensus_pax,
score_matrix, human_align_matrix)
score_fly, frfly_align, consensus_align_2 = student.compute_global_alignment(frfly_seq, consensus_pax,
score_matrix, frfly_align_matrix)
# compute percentages match for human and fruitfly
human_count = 0.0
for index in range(len(human_align)):
if human_align[index] == consensus_align[index]:
human_count += 1
frfly_count = 0.0
for index in range(len(frfly_align)):
if frfly_align[index] == consensus_align_2[index]:
frfly_count += 1
print "% Human: " + str(human_count / len(human_align) * 100)
print "Hmn: " + human_align
print "PAX: " + consensus_align
print ""
print "% FrFly: " + str(frfly_count / len(frfly_align) * 100)
print "Fly: " + frfly_align
print "PAX: " + consensus_align_2
def q3() :
len_gen = len(seq_x)
seq_x = []
seq_y = []
for _ in range(len_gen) :
seq_x.append(random.choice("ACBEDGFIHKMLNQPSRTWVYXZ"))
seq_y.append(random.choice("ACBEDGFIHKMLNQPSRTWVYXZ"))
alignment_matrix = student.compute_alignment_matrix(seq_x, seq_y, scoring_matrix, False)
score, human_aligen, fruit_aligen = student.compute_local_alignment(seq_x, seq_y, scoring_matrix, alignment_matrix)
print score
print human_aligen.replace('-', '')
print fruit_aligen
human_aligen = human_aligen.replace('-', '')
fruit_aligen = fruit_aligen.replace('-', '')
pax = read_protein(CONSENSUS_PAX_URL)
alignment_matrix = student.compute_alignment_matrix(human_aligen, pax, scoring_matrix, False)
score, h1, h2 = student.compute_global_alignment(human_aligen, pax, scoring_matrix, alignment_matrix)
print len(h1), len(h2)
same = 0
for i in range(len(h1)) :
if h1[i] == h2[i] :
same += 1
print same * 1.0 / len(h1)
alignment_matrix = student.compute_alignment_matrix(fruit_aligen, pax, scoring_matrix, False)
score, f1, f2 = student.compute_global_alignment(fruit_aligen, pax, scoring_matrix, alignment_matrix)
print len(f1), len(f2)
same = 0
for i in range(len(f1)) :
if f1[i] == f2[i] :
same += 1
print same * 1.0 / len(f1)
def run_q2(origin_seq_x):
seq_x = origin_seq_x.replace('-', '')
seq_y = 'GHGGVNQLGGVFVNGRPLPDVVRQRIVELAHQGVRPCDISRQLRVSHGCVSKILGRYYETGSIKPGVIGGSKPKVATPKVVEKIAEYKRQNPTMFAWEIRDRLLAERVCDNDTVPSVSSINRIIR'
scoring_matrix = read_scoring_matrix(PAM50_URL)
alignment_matrix = student.compute_alignment_matrix(seq_x, seq_y, scoring_matrix, True)
score, aglin_x, aglin_y = student.compute_global_alignment(seq_x, seq_y, scoring_matrix, alignment_matrix)
assert len(aglin_x) == len(aglin_y)
length = len(aglin_y)
match = 0
print (len(seq_x), len(seq_y), len(aglin_x) , len(aglin_y))
for idx in range(length):
if aglin_x[idx] == aglin_y[idx]:
match += 1
return match * 1.0 / length
def run_q2(origin_seq_x):
seq_x = origin_seq_x.replace('-', '')
seq_y = 'GHGGVNQLGGVFVNGRPLPDVVRQRIVELAHQGVRPCDISRQLRVSHGCVSKILGRYYETGSIKPGVIGGSKPKVATPKVVEKIAEYKRQNPTMFAWEIRDRLLAERVCDNDTVPSVSSINRIIR'
scoring_matrix = read_scoring_matrix(PAM50_URL)
alignment_matrix = student.compute_alignment_matrix(
seq_x, seq_y, scoring_matrix, True)
score, aglin_x, aglin_y = student.compute_global_alignment(
seq_x, seq_y, scoring_matrix, alignment_matrix)
assert len(aglin_x) == len(aglin_y)
length = len(aglin_y)
match = 0
print(len(seq_x), len(seq_y), len(aglin_x), len(aglin_y))
for idx in range(length):
if aglin_x[idx] == aglin_y[idx]:
match += 1
return match * 1.0 / length
def question7(seq_x, seq_y):
""" determine scoring matrix of edit distance algorithm """
diag_score = 2
off_diag_score = 1
dash_score = 0
alphabet = "abcdefghijklmnopqrstuvwxyz"
score_matrix = student.build_scoring_matrix(alphabet, diag_score, off_diag_score, dash_score)
align_matrix = student.compute_alignment_matrix(seq_x, seq_y, score_matrix, True)
score, align_x, align_y = student.compute_global_alignment(seq_x, seq_y, score_matrix, align_matrix)
edit_distance = len(seq_x) + len(seq_y) - score
print "Edit distance: " + str(edit_distance)
print align_x
print align_y
def check_spelling(checked_word, dist, word_list):
"""
input: word, target distance, and word list
output: return a subset of word list which the distance between input word < target distance
"""
result = set()
for item in word_list:
alignment_matrix = student.compute_alignment_matrix(
checked_word, item, scoring_matrix, True)
global_alignment = student.compute_global_alignment(
checked_word, item, scoring_matrix, alignment_matrix)
"""
print word_list[index]
print alignment_matrix
print global_alignment
"""
if (len(checked_word) + len(item) - global_alignment[0]) <= dist:
result = result.union(set([item]))
return result
def check_spelling(checked_word, dist, word_list):
diag_score = 2
off_diag_score = 1
dash_score = 0
chars = 'abcdefghijklmnopqrstuvwxyz'
alphabet = set([char for char in chars])
len_checkedword = len(checked_word)
scoring_matrix = student.build_scoring_matrix(alphabet, diag_score,
off_diag_score, dash_score)
similar_word_list = []
for word in word_list:
global_alignment_matrix = student.compute_alignment_matrix(
checked_word, word, scoring_matrix, True)
global_alignment_score = student.compute_global_alignment(
checked_word, word, scoring_matrix, global_alignment_matrix)[0]
edit_dist = len_checkedword + len(word) - global_alignment_score
if edit_dist <= dist:
similar_word_list.append(word)
return similar_word_list
def check_spelling(checked_word, dist, word_list):
""" helper function to determine all words edit distance away """
diag_score = 2
off_diag_score = 1
dash_score = 0
alphabet = "abcdefghijklmnopqrstuvwxyz"
score_matrix = student.build_scoring_matrix(alphabet, diag_score, off_diag_score, dash_score)
words = []
for word in word_list:
align_matrix = student.compute_alignment_matrix(checked_word, word, score_matrix, True)
score, align_x, align_y = student.compute_global_alignment(checked_word, word,
score_matrix, align_matrix)
edit_distance = len(checked_word) + len(word) - score
if edit_distance <= dist:
words.append(word)
return words
def check_spelling(checked_word, dist, word_list):
"""
input:
iterates through word_list and returns the set of all words
that are within edit distance dist of the string checked_word
output:
the set of all words that are within edit distance dist of
the string checked_word
"""
result_set = set([])
diag_score = 2
off_diag_score = 1
dash_score = 0
alphabet = set('abcdefghijklmnopqrstuvwxyz')
matrix_M = student.build_scoring_matrix(alphabet, diag_score, off_diag_score, dash_score)
for word in word_list:
matrix_S = student.compute_alignment_matrix(checked_word, word, matrix_M, True)
global_align_word = student.compute_global_alignment(checked_word, word, matrix_M, matrix_S)
if len(checked_word) + len(word) - global_align_word[0] <= dist:
result_set.add(word)
return result_set
hep_fep_local_alignment = alg_project4_solution.compute_local_alignment(hep, fep, scoring_matrix,
alg_project4_solution.compute_alignment_matrix(
hep, fep, scoring_matrix, False))
human_eyeless_fruitfly_local_alignment_score = hep_fep_local_alignment[0]
# question 1 answer
print "local alignment for human and fruitfly eyeless genome: " + str(hep_fep_local_alignment)
# question 2
cpd = alg_alignment.read_protein(CONSENSUS_PAX_URL)
hep_local_alignment = hep_fep_local_alignment[1]
fep_local_alignment = hep_fep_local_alignment[2]
hep_local_alignment_no_dashes = hep_local_alignment.replace('-', '')
hep_no_dashes_cpd_global_alignment = alg_project4_solution.compute_global_alignment(hep_local_alignment_no_dashes, cpd, scoring_matrix, alg_project4_solution.compute_alignment_matrix(
hep_local_alignment_no_dashes, cpd, scoring_matrix, True))
fep_local_alignment_no_dashes = fep_local_alignment.replace('-', '')
fep_no_dashes_cpd_global_alignment = alg_project4_solution.compute_global_alignment(fep_local_alignment_no_dashes, cpd, scoring_matrix,
alg_project4_solution.compute_alignment_matrix(fep_local_alignment_no_dashes, cpd, scoring_matrix, True))
print hep_no_dashes_cpd_global_alignment
print fep_no_dashes_cpd_global_alignment
# compute the percentage of elements in these two sequences that agree
hndga = hep_no_dashes_cpd_global_alignment[1]
hndgacpd = hep_no_dashes_cpd_global_alignment[2]
human_consensus_match_count = 0
for idx, elem in enumerate(hndga):
False))
human_eyeless_fruitfly_local_alignment_score = hep_fep_local_alignment[0]
# question 1 answer
print "local alignment for human and fruitfly eyeless genome: " + str(
hep_fep_local_alignment)
# question 2
cpd = alg_alignment.read_protein(CONSENSUS_PAX_URL)
hep_local_alignment = hep_fep_local_alignment[1]
fep_local_alignment = hep_fep_local_alignment[2]
hep_local_alignment_no_dashes = hep_local_alignment.replace('-', '')
hep_no_dashes_cpd_global_alignment = alg_project4_solution.compute_global_alignment(
hep_local_alignment_no_dashes, cpd, scoring_matrix,
alg_project4_solution.compute_alignment_matrix(
hep_local_alignment_no_dashes, cpd, scoring_matrix, True))
fep_local_alignment_no_dashes = fep_local_alignment.replace('-', '')
fep_no_dashes_cpd_global_alignment = alg_project4_solution.compute_global_alignment(
fep_local_alignment_no_dashes, cpd, scoring_matrix,
alg_project4_solution.compute_alignment_matrix(
fep_local_alignment_no_dashes, cpd, scoring_matrix, True))
print hep_no_dashes_cpd_global_alignment
print fep_no_dashes_cpd_global_alignment
# compute the percentage of elements in these two sequences that agree
hndga = hep_no_dashes_cpd_global_alignment[1]
hndgacpd = hep_no_dashes_cpd_global_alignment[2]
student.compute_local_alignment(HUMAN_EYELESS, FRUITFLY_EYELESS,\
SCORING_MATRIX, ALIGNMENT_MATRIX)
# Question 2 ##################################################################
PAX = read_protein(CONSENSUS_PAX_URL)
loc_score, loc_human, loc_fly = student.compute_local_alignment(HUMAN_EYELESS,\
FRUITFLY_EYELESS,\
SCORING_MATRIX,\
ALIGNMENT_MATRIX)
for align in (loc_human, loc_fly):
align = align.replace('-', '')
alignment_matrix = student.compute_alignment_matrix(
align, PAX, SCORING_MATRIX, True)
score, alignment, cons = student.compute_global_alignment(
align, PAX, SCORING_MATRIX, alignment_matrix)
print sum([alignment[i] == cons[i]
for i in range(len(alignment))]) / float(len(alignment))
# Question 4 ##################################################################
def generate_null_distribution(seq_x, seq_y, scoring_matrix, num_trials):
scoring_distribution = {}
list_y = list(seq_y)
for trial in range(num_trials):
temp_y = list_y
random.shuffle(temp_y)
rand_y = ''.join(temp_y)
alignment_matrix = student.compute_alignment_matrix(
seq_x, rand_y, scoring_matrix, False)
def score(x, y):
alignment_matrix = student.compute_alignment_matrix(
x, y, scoring_matrix, True)
return student.compute_global_alignment(x, y, scoring_matrix,
alignment_matrix)[0]
def find_local_align():
score_matrix = read_scoring_matrix(PAM50_URL)
seq_human = read_protein(HUMAN_EYELESS_URL)
seq_fly = read_protein(FRUITFLY_EYELESS_URL)
local_alignment_matrix = student.compute_alignment_matrix(
seq_human, seq_fly, score_matrix, False)
score, seq_loc_human, seq_loc_fly = student.compute_local_alignment(
seq_human, seq_fly, score_matrix, local_alignment_matrix)
length = len(seq_loc_fly)
agree = 0
for idx in range(length):
if seq_loc_fly[idx] == seq_loc_human[idx]:
agree += 1
print 'Question 1:\n'
print 'score:', score, '\nhuman:', seq_loc_human, '\nfly: ', seq_loc_fly
print 'Agree percentage: %.2f' % (100 * float(agree) / length)
"""
Question 1:
local alignment score: 875
human: HSGVNQLGGVFVNGRPLPDSTRQKIVELAHSGARPCDISRILQVSNGCVSKILGRYYETGSIRPRAIGGSKPRVATPEVVSKIAQYKRECPSIFAWEIRDRLLSEGVCTNDNIPSVSSINRVLRNLASEK-QQ
fly: HSGVNQLGGVFVGGRPLPDSTRQKIVELAHSGARPCDISRILQVSNGCVSKILGRYYETGSIRPRAIGGSKPRVATAEVVSKISQYKRECPSIFAWEIRDRLLQENVCTNDNIPSVSSINRVLRNLAAQKEQQ
Agree percentage: 93.98%
"""
### Question 2 ###
print '\nQuestion 2:\n'
seq_loc_human = seq_loc_human.replace('-', '')
seq_loc_fly = seq_loc_fly.replace('-', '')
seq_pax = read_protein(CONSENSUS_PAX_URL) #Q2
# seq_pax = 'ACBEDGFIHKMLNQPSRTWVYXZ' #Q3
for idx in range(2):
if idx == 0:
seq = seq_loc_human
type = 'human'
else:
seq = seq_loc_fly
type = 'fly'
global_alignment_matrix = student.compute_alignment_matrix(
seq, seq_pax, score_matrix, True)
score, x_glbl, pax_glbl = student.compute_global_alignment(
seq, seq_pax, score_matrix, global_alignment_matrix)
length = len(x_glbl)
agree = 0
for idx in range(length):
if x_glbl[idx] == pax_glbl[idx]:
agree += 1
print 'score:', score, '\n' + type, x_glbl, '\nPAX: ', pax_glbl
print type + ' agree percentage: %.2f' % (100 * float(agree) / length)
"""
Question 2:
human score: 613
human: -HSGVNQLGGVFVNGRPLPDSTRQKIVELAHSGARPCDISRILQVSNGCVSKILGRYYETGSIRPRAIGGSKPRVATPEVVSKIAQYKRECPSIFAWEIRDRLLSEGVCTNDNIPSVSSINRVLRNLASEKQQ
PAX: GHGGVNQLGGVFVNGRPLPDVVRQRIVELAHQGVRPCDISRQLRVSHGCVSKILGRYYETGSIKPGVIGGSKPKVATPKVVEKIAEYKRQNPTMFAWEIRDRLLAERVCDNDTVPSVSSINRIIR--------
human agree percentage: 72.93
flyscore: 586
fly: -HSGVNQLGGVFVGGRPLPDSTRQKIVELAHSGARPCDISRILQVSNGCVSKILGRYYETGSIRPRAIGGSKPRVATAEVVSKISQYKRECPSIFAWEIRDRLLQENVCTNDNIPSVSSINRVLRNLAAQKEQQ
PAX: GHGGVNQLGGVFVNGRPLPDVVRQRIVELAHQGVRPCDISRQLRVSHGCVSKILGRYYETGSIKPGVIGGSKPKVATPKVVEKIAEYKRQNPTMFAWEIRDRLLAERVCDNDTVPSVSSINRIIR---------
fly agree percentage: 70.15
"""
"""
# Q2
TempHumanSeq = result_Q1[1]
FruitflySeq = result_Q1[2]
HumanSeq = TempHumanSeq[:len(TempHumanSeq) -
3] + TempHumanSeq[len(TempHumanSeq) - 2:]
ConsensusPAXDomain = read_protein(CONSENSUS_PAX_URL)
alignment_matrix_Q2_Human = student.compute_alignment_matrix(
HumanSeq, ConsensusPAXDomain, PAM50, True)
alignment_matrix_Q2_Fruitfly = student.compute_alignment_matrix(
FruitflySeq, ConsensusPAXDomain, PAM50, True)
result_Q2_Human = student.compute_global_alignment(HumanSeq,
ConsensusPAXDomain, PAM50,
alignment_matrix_Q2_Human)
result_Q2_Fruitfly = student.compute_global_alignment(
FruitflySeq, ConsensusPAXDomain, PAM50, alignment_matrix_Q2_Fruitfly)
def calculate_score(seq1, seq2):
if len(seq1) != len(seq2):
print "Wrong!"
return
else:
num_equal = 0
for dummy_idx in range(len(seq1)):
if seq1[dummy_idx] == seq2[dummy_idx]:
num_equal += 1
return (float(num_equal) / float(len(seq1)) * 100)
def score(x, y):
alignment_matrix = student.compute_alignment_matrix(x, y, scoring_matrix, True)
return student.compute_global_alignment(x, y, scoring_matrix, alignment_matrix)[0]
