def duplicate_sequence(chrSeq,
dupStart,
dupStop,
insertLoc,
numDup=1,
invert=False):
duplication = str(chrSeq[int(dupStart) - 1:int(dupStop)]) * int(numDup)
if invert == True:
MutableSeq.reverse(duplication)
begin = MutableSeq.__add__(chrSeq[:int(insertLoc)], duplication)
chrSeq = MutableSeq.__add__(begin, chrSeq[int(insertLoc):])
return chrSeq
def get_optimal_alignment(self):
"""Follow the traceback to get the optimal alignment."""
# intialize the two sequences which will return the alignment
align_seq1 = MutableSeq(array.array("c"),
Alphabet.Gapped(IUPAC.protein, GAP_CHAR))
align_seq2 = MutableSeq(array.array("c"),
Alphabet.Gapped(IUPAC.protein, GAP_CHAR))
# take care of the initial case with the bottom corner matrix
# item
current_cell = self.dpmatrix[(len(self.seq1), len(self.seq2))]
align_seq1.append(current_cell.seq1item)
align_seq2.append(current_cell.seq2item)
next_cell = current_cell.get_parent()
current_cell = next_cell
next_cell = current_cell.get_parent()
# keeping adding sequence until we reach (0, 0)
while next_cell:
# add the new sequence--three cases:
# 1. Move up diaganolly, add a new seq1 and seq2 to the
# aligned sequences
if ((next_cell.col_pos == current_cell.col_pos - 1) and
(next_cell.row_pos == current_cell.row_pos - 1)):
# print "case 1 -> seq1 %s, seq2 %s" % (
# current_cell.seq1item, current_cell.seq2item)
align_seq1.append(current_cell.seq1item)
align_seq2.append(current_cell.seq2item)
# 2. Move upwards, add a new seq2 and a gap in seq1
elif ((next_cell.col_pos == current_cell.col_pos) and
(next_cell.row_pos == current_cell.row_pos - 1)):
#print "case 2 -> seq2 %s" % current_cell.seq2item
align_seq1.append(GAP_CHAR)
align_seq2.append(current_cell.seq2item)
# 3. Move to the right, add a new seq1 and a gap in seq2
elif ((next_cell.col_pos == current_cell.col_pos - 1) and
(next_cell.row_pos == current_cell.row_pos)):
#print "case 3 -> seq1 % s" % current_cell.seq1item
align_seq1.append(current_cell.seq1item)
align_seq2.append(GAP_CHAR)
# now move on to the next sequence
current_cell = next_cell
next_cell = current_cell.get_parent()
# reverse the returned alignments since we are reading them in
# backwards
align_seq1.reverse()
align_seq2.reverse()
return align_seq1.toseq(), align_seq2.toseq()
class TestMutableSeq(unittest.TestCase):
def setUp(self):
self.s = Seq.Seq("TCAAAAGGATGCATCATG")
self.mutable_s = MutableSeq("TCAAAAGGATGCATCATG")
def test_mutableseq_creation(self):
"""Test creating MutableSeqs in multiple ways."""
mutable_s = MutableSeq("TCAAAAGGATGCATCATG")
self.assertIsInstance(mutable_s, MutableSeq, "Creating MutableSeq")
mutable_s = self.s.tomutable()
self.assertIsInstance(mutable_s, MutableSeq,
"Converting Seq to mutable")
array_seq = MutableSeq(array.array("u", "TCAAAAGGATGCATCATG"))
self.assertIsInstance(array_seq, MutableSeq,
"Creating MutableSeq using array")
def test_repr(self):
self.assertEqual("MutableSeq('TCAAAAGGATGCATCATG')",
repr(self.mutable_s))
def test_truncated_repr(self):
seq = "TCAAAAGGATGCATCATGTCAAAAGGATGCATCATGTCAAAAGGATGCATCATGTCAAAAGGA"
expected = (
"MutableSeq('TCAAAAGGATGCATCATGTCAAAAGGATGCATCATGTCAAAAGGATGCATCATG...GGA')"
)
self.assertEqual(expected, repr(MutableSeq(seq)))
def test_equal_comparison(self):
"""Test __eq__ comparison method."""
self.assertEqual(self.mutable_s, "TCAAAAGGATGCATCATG")
def test_not_equal_comparison(self):
"""Test __ne__ comparison method."""
self.assertNotEqual(self.mutable_s, "other thing")
def test_less_than_comparison(self):
"""Test __lt__ comparison method."""
self.assertLess(self.mutable_s[:-1], self.mutable_s)
def test_less_than_comparison_of_incompatible_types(self):
with self.assertRaises(TypeError):
self.mutable_s < 1
def test_less_than_comparison_without_alphabet(self):
self.assertLessEqual(self.mutable_s[:-1], "TCAAAAGGATGCATCATG")
def test_less_than_or_equal_comparison(self):
"""Test __le__ comparison method."""
self.assertLessEqual(self.mutable_s[:-1], self.mutable_s)
def test_less_than_or_equal_comparison_of_incompatible_types(self):
with self.assertRaises(TypeError):
self.mutable_s <= 1
def test_less_than_or_equal_comparison_without_alphabet(self):
self.assertLessEqual(self.mutable_s[:-1], "TCAAAAGGATGCATCATG")
def test_greater_than_comparison(self):
"""Test __gt__ comparison method."""
self.assertGreater(self.mutable_s, self.mutable_s[:-1])
def test_greater_than_comparison_of_incompatible_types(self):
with self.assertRaises(TypeError):
self.mutable_s > 1
def test_greater_than_comparison_without_alphabet(self):
self.assertGreater(self.mutable_s, "TCAAAAGGATGCATCAT")
def test_greater_than_or_equal_comparison(self):
"""Test __ge__ comparison method."""
self.assertGreaterEqual(self.mutable_s, self.mutable_s)
def test_greater_than_or_equal_comparison_of_incompatible_types(self):
with self.assertRaises(TypeError):
self.mutable_s >= 1
def test_greater_than_or_equal_comparison_without_alphabet(self):
self.assertGreaterEqual(self.mutable_s, "TCAAAAGGATGCATCATG")
def test_add_method(self):
"""Test adding wrong type to MutableSeq."""
with self.assertRaises(TypeError):
self.mutable_s + 1234
def test_radd_method(self):
self.assertEqual(
"TCAAAAGGATGCATCATGTCAAAAGGATGCATCATG",
self.mutable_s.__radd__(self.mutable_s),
)
def test_radd_method_incompatible_alphabets(self):
self.assertEqual(
"UCAAAAGGATCAAAAGGATGCATCATG",
self.mutable_s.__radd__(MutableSeq("UCAAAAGGA")),
)
def test_radd_method_using_seq_object(self):
self.assertEqual("TCAAAAGGATGCATCATGTCAAAAGGATGCATCATG",
self.mutable_s.__radd__(self.s))
def test_radd_method_wrong_type(self):
with self.assertRaises(TypeError):
self.mutable_s.__radd__(1234)
def test_as_string(self):
self.assertEqual("TCAAAAGGATGCATCATG", str(self.mutable_s))
def test_length(self):
self.assertEqual(18, len(self.mutable_s))
def test_converting_to_immutable(self):
self.assertIsInstance(self.mutable_s.toseq(), Seq.Seq)
def test_first_nucleotide(self):
self.assertEqual("T", self.mutable_s[0])
def test_setting_slices(self):
self.assertEqual(
MutableSeq("CAAA"),
self.mutable_s[1:5],
"Slice mutable seq",
)
self.mutable_s[1:3] = "GAT"
self.assertEqual(
MutableSeq("TGATAAAGGATGCATCATG"),
self.mutable_s,
"Set slice with string and adding extra nucleotide",
)
self.mutable_s[1:3] = self.mutable_s[5:7]
self.assertEqual(
MutableSeq("TAATAAAGGATGCATCATG"),
self.mutable_s,
"Set slice with MutableSeq",
)
self.mutable_s[1:3] = array.array("u", "GAT")
self.assertEqual(
MutableSeq("TGATTAAAGGATGCATCATG"),
self.mutable_s,
"Set slice with array",
)
def test_setting_item(self):
self.mutable_s[3] = "G"
self.assertEqual(MutableSeq("TCAGAAGGATGCATCATG"), self.mutable_s)
def test_deleting_slice(self):
del self.mutable_s[4:5]
self.assertEqual(MutableSeq("TCAAAGGATGCATCATG"), self.mutable_s)
def test_deleting_item(self):
del self.mutable_s[3]
self.assertEqual(MutableSeq("TCAAAGGATGCATCATG"), self.mutable_s)
def test_appending(self):
self.mutable_s.append("C")
self.assertEqual(MutableSeq("TCAAAAGGATGCATCATGC"), self.mutable_s)
def test_inserting(self):
self.mutable_s.insert(4, "G")
self.assertEqual(MutableSeq("TCAAGAAGGATGCATCATG"), self.mutable_s)
def test_popping_last_item(self):
self.assertEqual("G", self.mutable_s.pop())
def test_remove_items(self):
self.mutable_s.remove("G")
self.assertEqual(MutableSeq("TCAAAAGATGCATCATG"), self.mutable_s,
"Remove first G")
self.assertRaises(ValueError, self.mutable_s.remove, "Z")
def test_count(self):
self.assertEqual(7, self.mutable_s.count("A"))
self.assertEqual(2, self.mutable_s.count("AA"))
def test_index(self):
self.assertEqual(2, self.mutable_s.index("A"))
self.assertRaises(ValueError, self.mutable_s.index, "8888")
def test_reverse(self):
"""Test using reverse method."""
self.mutable_s.reverse()
self.assertEqual(MutableSeq("GTACTACGTAGGAAAACT"), self.mutable_s)
def test_reverse_with_stride(self):
"""Test reverse using -1 stride."""
self.assertEqual(MutableSeq("GTACTACGTAGGAAAACT"),
self.mutable_s[::-1])
def test_complement(self):
self.mutable_s.complement()
self.assertEqual("AGTTTTCCTACGTAGTAC", str(self.mutable_s))
def test_complement_rna(self):
seq = Seq.MutableSeq("AUGaaaCUG")
seq.complement()
self.assertEqual("UACuuuGAC", str(seq))
def test_complement_mixed_aphabets(self):
seq = Seq.MutableSeq("AUGaaaCTG")
with self.assertRaises(ValueError):
seq.complement()
def test_complement_rna_string(self):
seq = Seq.MutableSeq("AUGaaaCUG")
seq.complement()
self.assertEqual("UACuuuGAC", str(seq))
def test_complement_dna_string(self):
seq = Seq.MutableSeq("ATGaaaCTG")
seq.complement()
self.assertEqual("TACtttGAC", str(seq))
def test_reverse_complement(self):
self.mutable_s.reverse_complement()
self.assertEqual("CATGATGCATCCTTTTGA", str(self.mutable_s))
def test_extend_method(self):
self.mutable_s.extend("GAT")
self.assertEqual(MutableSeq("TCAAAAGGATGCATCATGGAT"), self.mutable_s)
def test_extend_with_mutable_seq(self):
self.mutable_s.extend(MutableSeq("TTT"))
self.assertEqual(MutableSeq("TCAAAAGGATGCATCATGTTT"), self.mutable_s)
def test_delete_stride_slice(self):
del self.mutable_s[4:6 - 1]
self.assertEqual(MutableSeq("TCAAAGGATGCATCATG"), self.mutable_s)
def test_extract_third_nucleotide(self):
"""Test extracting every third nucleotide (slicing with stride 3)."""
self.assertEqual(MutableSeq("TAGTAA"), self.mutable_s[0::3])
self.assertEqual(MutableSeq("CAGGTT"), self.mutable_s[1::3])
self.assertEqual(MutableSeq("AAACCG"), self.mutable_s[2::3])
def test_set_wobble_codon_to_n(self):
"""Test setting wobble codon to N (set slice with stride 3)."""
self.mutable_s[2::3] = "N" * len(self.mutable_s[2::3])
self.assertEqual(MutableSeq("TCNAANGGNTGNATNATN"), self.mutable_s)
def viterbi(self, sequence, state_alphabet):
"""Calculate the most probable state path using the Viterbi algorithm.
This implements the Viterbi algorithm (see pgs 55-57 in Durbin et
al for a full explanation -- this is where I took my implementation
ideas from), to allow decoding of the state path, given a sequence
of emissions.
Arguments:
o sequence -- A Seq object with the emission sequence that we
want to decode.
o state_alphabet -- The alphabet of the possible state sequences
that can be generated.
"""
# calculate logarithms of the initial, transition, and emission probs
log_initial = self._log_transform(self.initial_prob)
log_trans = self._log_transform(self.transition_prob)
log_emission = self._log_transform(self.emission_prob)
viterbi_probs = {}
pred_state_seq = {}
state_letters = state_alphabet.letters
# --- recursion
# loop over the training squence (i = 1 .. L)
# NOTE: My index numbers are one less than what is given in Durbin
# et al, since we are indexing the sequence going from 0 to
# (Length - 1) not 1 to Length, like in Durbin et al.
for i in range(0, len(sequence)):
# loop over all of the possible i-th states in the state path
for cur_state in state_letters:
# e_{l}(x_{i})
emission_part = log_emission[(cur_state, sequence[i])]
max_prob = 0
if i == 0:
# for the first state, use the initial probability rather
# than looking back to previous states
max_prob = log_initial[cur_state]
else:
# loop over all possible (i-1)-th previous states
possible_state_probs = {}
for prev_state in self.transitions_to(cur_state):
# a_{kl}
trans_part = log_trans[(prev_state, cur_state)]
# v_{k}(i - 1)
viterbi_part = viterbi_probs[(prev_state, i - 1)]
cur_prob = viterbi_part + trans_part
possible_state_probs[prev_state] = cur_prob
# calculate the viterbi probability using the max
max_prob = max(possible_state_probs.values())
# v_{k}(i)
viterbi_probs[(cur_state, i)] = (emission_part + max_prob)
if i > 0:
# get the most likely prev_state leading to cur_state
for state in possible_state_probs:
if possible_state_probs[state] == max_prob:
pred_state_seq[(i - 1, cur_state)] = state
break
# --- termination
# calculate the probability of the state path
# loop over all states
all_probs = {}
for state in state_letters:
# v_{k}(L)
all_probs[state] = viterbi_probs[(state, len(sequence) - 1)]
state_path_prob = max(all_probs.values())
# find the last pointer we need to trace back from
last_state = ''
for state in all_probs:
if all_probs[state] == state_path_prob:
last_state = state
assert last_state != '', "Didn't find the last state to trace from!"
# --- traceback
traceback_seq = MutableSeq('', state_alphabet)
loop_seq = range(1, len(sequence))
loop_seq.reverse()
# last_state is the last state in the most probable state sequence.
# Compute that sequence by walking backwards in time. From the i-th
# state in the sequence, find the (i-1)-th state as the most
# probable state preceding the i-th state.
state = last_state
traceback_seq.append(state)
for i in loop_seq:
state = pred_state_seq[(i - 1, state)]
traceback_seq.append(state)
# put the traceback sequence in the proper orientation
traceback_seq.reverse()
return traceback_seq.toseq(), state_path_prob
def viterbi(self, sequence, state_alphabet):
"""Calculate the most probable state path using the Viterbi algorithm.
This implements the Viterbi algorithm (see pgs 55-57 in Durbin et
al for a full explanation -- this is where I took my implementation
ideas from), to allow decoding of the state path, given a sequence
of emissions.
Arguments:
o sequence -- A Seq object with the emission sequence that we
want to decode.
o state_alphabet -- The alphabet of the possible state sequences
that can be generated.
"""
# calculate logarithms of the initial, transition, and emission probs
log_initial = self._log_transform(self.initial_prob)
log_trans = self._log_transform(self.transition_prob)
log_emission = self._log_transform(self.emission_prob)
viterbi_probs = {}
pred_state_seq = {}
state_letters = state_alphabet.letters
# --- recursion
# loop over the training squence (i = 1 .. L)
# NOTE: My index numbers are one less than what is given in Durbin
# et al, since we are indexing the sequence going from 0 to
# (Length - 1) not 1 to Length, like in Durbin et al.
for i in range(0, len(sequence)):
# loop over all of the possible i-th states in the state path
for cur_state in state_letters:
# e_{l}(x_{i})
emission_part = log_emission[(cur_state, sequence[i])]
max_prob = 0
if i == 0:
# for the first state, use the initial probability rather
# than looking back to previous states
max_prob = log_initial[cur_state]
else:
# loop over all possible (i-1)-th previous states
possible_state_probs = {}
for prev_state in self.transitions_to(cur_state):
# a_{kl}
trans_part = log_trans[(prev_state, cur_state)]
# v_{k}(i - 1)
viterbi_part = viterbi_probs[(prev_state, i - 1)]
cur_prob = viterbi_part + trans_part
possible_state_probs[prev_state] = cur_prob
# calculate the viterbi probability using the max
max_prob = max(possible_state_probs.values())
# v_{k}(i)
viterbi_probs[(cur_state, i)] = (emission_part + max_prob)
if i > 0:
# get the most likely prev_state leading to cur_state
for state in possible_state_probs:
if possible_state_probs[state] == max_prob:
pred_state_seq[(i - 1, cur_state)] = state
break
# --- termination
# calculate the probability of the state path
# loop over all states
all_probs = {}
for state in state_letters:
# v_{k}(L)
all_probs[state] = viterbi_probs[(state, len(sequence) - 1)]
state_path_prob = max(all_probs.values())
# find the last pointer we need to trace back from
last_state = ''
for state in all_probs:
if all_probs[state] == state_path_prob:
last_state = state
assert last_state != '', "Didn't find the last state to trace from!"
# --- traceback
traceback_seq = MutableSeq('', state_alphabet)
loop_seq = list(range(1, len(sequence)))
loop_seq.reverse()
# last_state is the last state in the most probable state sequence.
# Compute that sequence by walking backwards in time. From the i-th
# state in the sequence, find the (i-1)-th state as the most
# probable state preceding the i-th state.
state = last_state
traceback_seq.append(state)
for i in loop_seq:
state = pred_state_seq[(i - 1, state)]
traceback_seq.append(state)
# put the traceback sequence in the proper orientation
traceback_seq.reverse()
return traceback_seq.toseq(), state_path_prob
mutable_seq = my_seq.tomutable()
mutable_seq
new_seq = mutable_seq.toseq()
new_seq
from Bio.Seq import MutableSeq
from Bio.Alphabet import IUPAC
mutable_seq = MutableSeq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna)
mutable_seq
mutable_seq[5] = "C"
mutable_seq
mutable_seq.remove("T")
mutable_seq
mutable_seq.reverse()
mutable_seq
# UnknownSeq objects
from Bio.Seq import UnknownSeq
unk = UnknownSeq(20)
unk
print(unk)
len(unk)
from Bio.Seq import UnknownSeq
from Bio.Alphabet import IUPAC
unk_dna = UnknownSeq(20, alphabet=IUPAC.ambiguous_dna)
unk_dna
print(unk_dna)
"AATCGTGGCTATTACTGGGATGGAGGTCACTGGCGCGACCACGGCTGGTGGAAACAACAT" +
"TATGAATGGCGAGGCAATCGCTGGCACCTACACGGACCGCCGCCACCGCCGCGCCACCAT" +
"AAGAAAGCTCCTCATGATCATCACGGCGGTCATGGTCCAGGCAAACATCACCGCTAA",
generic_dna)
print(gene.translate(table="Bacterial"))
print(gene.translate(table="Bacterial", cds=True))
##查看密码子表
from Bio.Data import CodonTable
standard_table = CodonTable.unambiguous_dna_by_name["Standard"]
mito_table = CodonTable.unambiguous_dna_by_id[2]
print(standard_table)
print(mito_table.start_codons)
print(mito_table.stop_codons)
print(mito_table.forward_table["ACG"])
##可变对象
from Bio.Seq import MutableSeq
mutable_seq = MutableSeq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna)
print(mutable_seq)
mutable_seq[5] = "C"
print(mutable_seq)
mutable_seq.remove("T")
print(mutable_seq)
mutable_seq.reverse()
print(mutable_seq)
new_seq = mutable_seq.toseq()
print(new_seq)
from Bio.Seq import Seq
from Bio.Seq import MutableSeq
from Bio.Alphabet import IUPAC
my_seq = MutableSeq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna)
# my_seq[6] = "C"
my_seq.remove("T")
my_seq.reverse()
print(repr(my_seq))
non_mutable_seq = my_seq.toseq()
#print gene
#YAAX = yaaX.translate(table='Bacterial', cds=True, to_stop=True)
#print YAAX
#playing with codon usage tables
#from Bio.Data import CodonTable
#standard_table = CodonTable.unambiguous_dna_by_name["Standard"]
#mito_table = CodonTable.unambiguous_dna_by_name["Vertebrate Mitochondrial"]
#print standard_table
#mutable seq objects
from Bio.Seq import Seq
from Bio.Seq import MutableSeq
from Bio.Alphabet import IUPAC
#my_seq = Seq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna)
#mutable_seq = my_seq.tomutable()
#Or just create a mutable seq!
my_seq = MutableSeq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna)
print my_seq
#my_seq_div = my_seq
#my_seq_div[5:8] = 'tag' #how to do insertions???????? only can replace as many characters as indicated. wait it works now.
#why 5:8?
#print my_seq #why does this print as my_seq_div with SNP?
#print my_seq_div
#my_seq_del = my_seq_div.remove("T")
#print my_seq_del
my_seq_rev = my_seq.reverse() #should be able to do my_seq.reverse_complement() as well
print my_seq_rev #this should be working, but it returning None
fin_seq = my_seq_div.toseq() #converts back to immutable Seq Object
def viterbi(self, sequence, state_alphabet):
"""Calculate the most probable state path using the Viterbi algorithm.
This implements the Viterbi algorithm (see pgs 55-57 in Durbin et
al for a full explanation -- this is where I took my implementation
ideas from), to allow decoding of the state path, given a sequence
of emissions.
Arguments:
o sequence -- A Seq object with the emission sequence that we
want to decode.
o state_alphabet -- The alphabet of the possible state sequences
that can be generated.
"""
# calculate logarithms of the transition and emission probs
log_trans = self._log_transform(self.transition_prob)
log_emission = self._log_transform(self.emission_prob)
viterbi_probs = {}
pred_state_seq = {}
state_letters = state_alphabet.letters
# --- initialization
#
# NOTE: My index numbers are one less than what is given in Durbin
# et al, since we are indexing the sequence going from 0 to
# (Length - 1) not 1 to Length, like in Durbin et al.
#
# v_{0}(0) = 1
viterbi_probs[(state_letters[0], -1)] = 1
# v_{k}(0) = 0 for k > 0
for state_letter in state_letters[1:]:
viterbi_probs[(state_letter, -1)] = 0
# --- recursion
# loop over the training squence (i = 1 .. L)
for i in range(0, len(sequence)):
# now loop over all of the letters in the state path
for main_state in state_letters:
# e_{l}(x_{i})
emission_part = log_emission[(main_state, sequence[i])]
# loop over all possible states
possible_state_probs = {}
for cur_state in self.transitions_from(main_state):
# a_{kl}
trans_part = log_trans[(cur_state, main_state)]
# v_{k}(i - 1)
viterbi_part = viterbi_probs[(cur_state, i - 1)]
cur_prob = viterbi_part + trans_part
possible_state_probs[cur_state] = cur_prob
# finally calculate the viterbi probability using the max
max_prob = max(possible_state_probs.values())
viterbi_probs[(main_state, i)] = (emission_part + max_prob)
# now get the most likely state
for state in possible_state_probs:
if possible_state_probs[state] == max_prob:
pred_state_seq[(i - 1, main_state)] = state
break
# --- termination
# calculate the probability of the state path
# loop over all letters
all_probs = {}
for state in state_letters:
# v_{k}(L)
viterbi_part = viterbi_probs[(state, len(sequence) - 1)]
# a_{k0}
transition_part = log_trans[(state, state_letters[0])]
all_probs[state] = viterbi_part * transition_part
state_path_prob = max(all_probs.values())
# find the last pointer we need to trace back from
last_state = ''
for state in all_probs:
if all_probs[state] == state_path_prob:
last_state = state
assert last_state != '', "Didn't find the last state to trace from!"
# --- traceback
traceback_seq = MutableSeq('', state_alphabet)
loop_seq = range(0, len(sequence))
loop_seq.reverse()
cur_state = last_state
for i in loop_seq:
traceback_seq.append(cur_state)
cur_state = pred_state_seq[(i - 1, cur_state)]
# put the traceback sequence in the proper orientation
traceback_seq.reverse()
return traceback_seq.toseq(), state_path_prob
# Print the second codon position
seqs[2::3]
# Sequence Length Comparison
seq1 = Seq("TTGTGGCCGCTCAGATCAGGCAGTTTAGGCTTA")
seq2 = Seq("ATTTATAGAAATGTGGTTATTTCTTAAGCATGGC")
seq1 == seq2
# Mutable sequence
mut_seq = MutableSeq("TTGTGGCCGCTCAGATCAGGCAGTTTAGGCTTA")
print(f'MutSeq: {mut_seq}')
mut_seq[5] == "C"
print(mut_seq)
mut_seq.remove("T")
print(mut_seq)
mut_seq.reverse()
print(mut_seq)
!wget http://d28rh4a8wq0iu5.cloudfront.net/ads1/data/SRR835775_1.first1000.fastq
# Working with Fastq files
for record in SeqIO.parse("SRR835775_1.first1000.fastq", "fastq"):
print(record)
print(record.seq)
print(record.letter_annotations['phred_quality'])
quals = [record.letter_annotations['phred_quality'] for record in SeqIO.parse("SRR835775_1.first1000.fastq", "fastq")]
class TestMutableSeq(unittest.TestCase):
def setUp(self):
self.s = Seq.Seq("TCAAAAGGATGCATCATG", IUPAC.unambiguous_dna)
self.mutable_s = MutableSeq("TCAAAAGGATGCATCATG", IUPAC.ambiguous_dna)
def test_mutableseq_creation(self):
"""Test creating MutableSeqs in multiple ways"""
mutable_s = MutableSeq("TCAAAAGGATGCATCATG", IUPAC.ambiguous_dna)
self.assertIsInstance(mutable_s, MutableSeq, "Creating MutableSeq")
mutable_s = self.s.tomutable()
self.assertIsInstance(mutable_s, MutableSeq,
"Converting Seq to mutable")
array_seq = MutableSeq(
array.array(array_indicator, "TCAAAAGGATGCATCATG"),
IUPAC.ambiguous_dna)
self.assertIsInstance(array_seq, MutableSeq,
"Creating MutableSeq using array")
def test_repr(self):
self.assertEqual(
"MutableSeq('TCAAAAGGATGCATCATG', IUPACAmbiguousDNA())",
repr(self.mutable_s))
def test_truncated_repr(self):
seq = "TCAAAAGGATGCATCATGTCAAAAGGATGCATCATGTCAAAAGGATGCATCATGTCAAAAGGA"
expected = "MutableSeq('TCAAAAGGATGCATCATGTCAAAAGGATGCATCATGTCAAAAGGATGCATCATG...GGA', IUPACAmbiguousDNA())"
self.assertEqual(expected, repr(MutableSeq(seq, IUPAC.ambiguous_dna)))
def test_equal_comparison(self):
"""Test __eq__ comparison method"""
self.assertEqual(self.mutable_s, "TCAAAAGGATGCATCATG")
def test_equal_comparison_of_incompatible_alphabets(self):
with warnings.catch_warnings(record=True):
self.mutable_s == MutableSeq('UCAAAAGGA', IUPAC.ambiguous_rna)
def test_not_equal_comparison(self):
"""Test __ne__ comparison method"""
self.assertNotEqual(self.mutable_s, "other thing")
def test_less_than_comparison(self):
"""Test __lt__ comparison method"""
self.assertTrue(self.mutable_s[:-1] < self.mutable_s)
def test_less_than_comparison_of_incompatible_alphabets(self):
with warnings.catch_warnings(record=True):
self.mutable_s[:-1] < MutableSeq("UCAAAAGGAUGCAUCAUG",
IUPAC.ambiguous_rna)
def test_less_than_comparison_without_alphabet(self):
self.assertTrue(self.mutable_s[:-1] < "TCAAAAGGATGCATCATG")
def test_less_than_or_equal_comparison(self):
"""Test __le__ comparison method"""
self.assertTrue(self.mutable_s[:-1] <= self.mutable_s)
def test_less_than_or_equal_comparison_of_incompatible_alphabets(self):
with warnings.catch_warnings(record=True):
self.mutable_s[:-1] <= MutableSeq("UCAAAAGGAUGCAUCAUG",
IUPAC.ambiguous_rna)
def test_less_than_or_equal_comparison_without_alphabet(self):
self.assertTrue(self.mutable_s[:-1] <= "TCAAAAGGATGCATCATG")
def test_add_method(self):
"""Test adding wrong type to MutableSeq"""
with self.assertRaises(TypeError):
self.mutable_s + 1234
def test_radd_method(self):
self.assertEqual("TCAAAAGGATGCATCATGTCAAAAGGATGCATCATG",
self.mutable_s.__radd__(self.mutable_s))
def test_radd_method_incompatible_alphabets(self):
with self.assertRaises(TypeError):
self.mutable_s.__radd__(
MutableSeq("UCAAAAGGA", IUPAC.ambiguous_rna))
def test_radd_method_using_seq_object(self):
self.assertEqual("TCAAAAGGATGCATCATGTCAAAAGGATGCATCATG",
self.mutable_s.__radd__(self.s))
def test_radd_method_wrong_type(self):
with self.assertRaises(TypeError):
self.mutable_s.__radd__(1234)
def test_as_string(self):
self.assertEqual("TCAAAAGGATGCATCATG", str(self.mutable_s))
def test_length(self):
self.assertEqual(18, len(self.mutable_s))
def test_converting_to_immutable(self):
self.assertIsInstance(self.mutable_s.toseq(), Seq.Seq)
def test_first_nucleotide(self):
self.assertEqual('T', self.mutable_s[0])
def test_setting_slices(self):
self.assertEqual(MutableSeq('CAAA', IUPAC.ambiguous_dna),
self.mutable_s[1:5], "Slice mutable seq")
self.mutable_s[1:3] = "GAT"
self.assertEqual(
MutableSeq("TGATAAAGGATGCATCATG",
IUPAC.ambiguous_dna), self.mutable_s,
"Set slice with string and adding extra nucleotide")
self.mutable_s[1:3] = self.mutable_s[5:7]
self.assertEqual(
MutableSeq("TAATAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s, "Set slice with MutableSeq")
self.mutable_s[1:3] = array.array(array_indicator, "GAT")
self.assertEqual(
MutableSeq("TGATTAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s, "Set slice with array")
def test_setting_item(self):
self.mutable_s[3] = "G"
self.assertEqual(MutableSeq("TCAGAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_deleting_slice(self):
del self.mutable_s[4:5]
self.assertEqual(MutableSeq("TCAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_deleting_item(self):
del self.mutable_s[3]
self.assertEqual(MutableSeq("TCAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_appending(self):
self.mutable_s.append("C")
self.assertEqual(
MutableSeq("TCAAAAGGATGCATCATGC", IUPAC.ambiguous_dna),
self.mutable_s)
def test_inserting(self):
self.mutable_s.insert(4, "G")
self.assertEqual(
MutableSeq("TCAAGAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_popping_last_item(self):
self.assertEqual("G", self.mutable_s.pop())
def test_remove_items(self):
self.mutable_s.remove("G")
self.assertEqual(MutableSeq("TCAAAAGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s, "Remove first G")
self.assertRaises(ValueError, self.mutable_s.remove, 'Z')
def test_count(self):
self.assertEqual(7, self.mutable_s.count("A"))
self.assertEqual(2, self.mutable_s.count("AA"))
def test_index(self):
self.assertEqual(2, self.mutable_s.index("A"))
self.assertRaises(ValueError, self.mutable_s.index, "8888")
def test_reverse(self):
"""Test using reverse method"""
self.mutable_s.reverse()
self.assertEqual(MutableSeq("GTACTACGTAGGAAAACT", IUPAC.ambiguous_dna),
self.mutable_s)
def test_reverse_with_stride(self):
"""Test reverse using -1 stride"""
self.assertEqual(MutableSeq("GTACTACGTAGGAAAACT", IUPAC.ambiguous_dna),
self.mutable_s[::-1])
def test_complement(self):
self.mutable_s.complement()
self.assertEqual(str("AGTTTTCCTACGTAGTAC"), str(self.mutable_s))
def test_complement_rna(self):
seq = Seq.MutableSeq("AUGaaaCUG", IUPAC.unambiguous_rna)
seq.complement()
self.assertEqual(str("UACuuuGAC"), str(seq))
def test_complement_mixed_aphabets(self):
seq = Seq.MutableSeq("AUGaaaCTG")
with self.assertRaises(ValueError):
seq.complement()
def test_complement_rna_string(self):
seq = Seq.MutableSeq("AUGaaaCUG")
seq.complement()
self.assertEqual('UACuuuGAC', str(seq))
def test_complement_dna_string(self):
seq = Seq.MutableSeq("ATGaaaCTG")
seq.complement()
self.assertEqual('TACtttGAC', str(seq))
def test_reverse_complement(self):
self.mutable_s.reverse_complement()
self.assertEqual("CATGATGCATCCTTTTGA", str(self.mutable_s))
def test_reverse_complement_of_protein(self):
seq = Seq.MutableSeq("ACTGTCGTCT", Alphabet.generic_protein)
with self.assertRaises(ValueError):
seq.reverse_complement()
def test_to_string_method(self):
"""This method is currently deprecated, probably will need to remove this test soon"""
with warnings.catch_warnings(record=True):
self.mutable_s.tostring()
def test_extend_method(self):
self.mutable_s.extend("GAT")
self.assertEqual(
MutableSeq("TCAAAAGGATGCATCATGGAT", IUPAC.ambiguous_dna),
self.mutable_s)
def test_extend_with_mutable_seq(self):
self.mutable_s.extend(MutableSeq("TTT", IUPAC.ambiguous_dna))
self.assertEqual(
MutableSeq("TCAAAAGGATGCATCATGTTT", IUPAC.ambiguous_dna),
self.mutable_s)
def test_delete_stride_slice(self):
del self.mutable_s[4:6 - 1]
self.assertEqual(MutableSeq("TCAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_extract_third_nucleotide(self):
"""Test extracting every third nucleotide (slicing with stride 3)"""
self.assertEqual(MutableSeq("TAGTAA", IUPAC.ambiguous_dna),
self.mutable_s[0::3])
self.assertEqual(MutableSeq("CAGGTT", IUPAC.ambiguous_dna),
self.mutable_s[1::3])
self.assertEqual(MutableSeq("AAACCG", IUPAC.ambiguous_dna),
self.mutable_s[2::3])
def test_set_wobble_codon_to_n(self):
"""Test setting wobble codon to N (set slice with stride 3)"""
self.mutable_s[2::3] = "N" * len(self.mutable_s[2::3])
self.assertEqual(MutableSeq("TCNAANGGNTGNATNATN", IUPAC.ambiguous_dna),
self.mutable_s)
class TestMutableSeq(unittest.TestCase):
def setUp(self):
self.s = Seq.Seq("TCAAAAGGATGCATCATG", IUPAC.unambiguous_dna)
self.mutable_s = MutableSeq("TCAAAAGGATGCATCATG", IUPAC.ambiguous_dna)
def test_mutableseq_creation(self):
"""Test creating MutableSeqs in multiple ways"""
mutable_s = MutableSeq("TCAAAAGGATGCATCATG", IUPAC.ambiguous_dna)
self.assertIsInstance(mutable_s, MutableSeq, "Creating MutableSeq")
mutable_s = self.s.tomutable()
self.assertIsInstance(mutable_s, MutableSeq, "Converting Seq to mutable")
array_seq = MutableSeq(array.array(array_indicator, "TCAAAAGGATGCATCATG"),
IUPAC.ambiguous_dna)
self.assertIsInstance(array_seq, MutableSeq, "Creating MutableSeq using array")
def test_repr(self):
self.assertEqual("MutableSeq('TCAAAAGGATGCATCATG', IUPACAmbiguousDNA())",
repr(self.mutable_s))
def test_truncated_repr(self):
seq = "TCAAAAGGATGCATCATGTCAAAAGGATGCATCATGTCAAAAGGATGCATCATGTCAAAAGGA"
expected = "MutableSeq('TCAAAAGGATGCATCATGTCAAAAGGATGCATCATGTCAAAAGGATGCATCATG...GGA', IUPACAmbiguousDNA())"
self.assertEqual(expected, repr(MutableSeq(seq, IUPAC.ambiguous_dna)))
def test_equal_comparison(self):
"""Test __eq__ comparison method"""
self.assertEqual(self.mutable_s, "TCAAAAGGATGCATCATG")
def test_equal_comparison_of_incompatible_alphabets(self):
with warnings.catch_warnings(record=True):
self.mutable_s == MutableSeq('UCAAAAGGA', IUPAC.ambiguous_rna)
def test_not_equal_comparison(self):
"""Test __ne__ comparison method"""
self.assertNotEqual(self.mutable_s, "other thing")
def test_less_than_comparison(self):
"""Test __lt__ comparison method"""
self.assertTrue(self.mutable_s[:-1] < self.mutable_s)
def test_less_than_comparison_of_incompatible_alphabets(self):
with warnings.catch_warnings(record=True):
self.mutable_s[:-1] < MutableSeq("UCAAAAGGAUGCAUCAUG", IUPAC.ambiguous_rna)
def test_less_than_comparison_without_alphabet(self):
self.assertTrue(self.mutable_s[:-1] < "TCAAAAGGATGCATCATG")
def test_less_than_or_equal_comparison(self):
"""Test __le__ comparison method"""
self.assertTrue(self.mutable_s[:-1] <= self.mutable_s)
def test_less_than_or_equal_comparison_of_incompatible_alphabets(self):
with warnings.catch_warnings(record=True):
self.mutable_s[:-1] <= MutableSeq("UCAAAAGGAUGCAUCAUG", IUPAC.ambiguous_rna)
def test_less_than_or_equal_comparison_without_alphabet(self):
self.assertTrue(self.mutable_s[:-1] <= "TCAAAAGGATGCATCATG")
def test_add_method(self):
"""Test adding wrong type to MutableSeq"""
with self.assertRaises(TypeError):
self.mutable_s + 1234
def test_radd_method(self):
self.assertEqual("TCAAAAGGATGCATCATGTCAAAAGGATGCATCATG",
self.mutable_s.__radd__(self.mutable_s))
def test_radd_method_incompatible_alphabets(self):
with self.assertRaises(TypeError):
self.mutable_s.__radd__(MutableSeq("UCAAAAGGA", IUPAC.ambiguous_rna))
def test_radd_method_using_seq_object(self):
self.assertEqual("TCAAAAGGATGCATCATGTCAAAAGGATGCATCATG",
self.mutable_s.__radd__(self.s))
def test_radd_method_wrong_type(self):
with self.assertRaises(TypeError):
self.mutable_s.__radd__(1234)
def test_as_string(self):
self.assertEqual("TCAAAAGGATGCATCATG", str(self.mutable_s))
def test_length(self):
self.assertEqual(18, len(self.mutable_s))
def test_converting_to_immutable(self):
self.assertIsInstance(self.mutable_s.toseq(), Seq.Seq)
def test_first_nucleotide(self):
self.assertEqual('T', self.mutable_s[0])
def test_setting_slices(self):
self.assertEqual(MutableSeq('CAAA', IUPAC.ambiguous_dna),
self.mutable_s[1:5], "Slice mutable seq")
self.mutable_s[1:3] = "GAT"
self.assertEqual(MutableSeq("TGATAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s,
"Set slice with string and adding extra nucleotide")
self.mutable_s[1:3] = self.mutable_s[5:7]
self.assertEqual(MutableSeq("TAATAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s, "Set slice with MutableSeq")
self.mutable_s[1:3] = array.array(array_indicator, "GAT")
self.assertEqual(MutableSeq("TGATTAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s, "Set slice with array")
def test_setting_item(self):
self.mutable_s[3] = "G"
self.assertEqual(MutableSeq("TCAGAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_deleting_slice(self):
del self.mutable_s[4:5]
self.assertEqual(MutableSeq("TCAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_deleting_item(self):
del self.mutable_s[3]
self.assertEqual(MutableSeq("TCAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_appending(self):
self.mutable_s.append("C")
self.assertEqual(MutableSeq("TCAAAAGGATGCATCATGC", IUPAC.ambiguous_dna),
self.mutable_s)
def test_inserting(self):
self.mutable_s.insert(4, "G")
self.assertEqual(MutableSeq("TCAAGAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_popping_last_item(self):
self.assertEqual("G", self.mutable_s.pop())
def test_remove_items(self):
self.mutable_s.remove("G")
self.assertEqual(MutableSeq("TCAAAAGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s, "Remove first G")
self.assertRaises(ValueError, self.mutable_s.remove, 'Z')
def test_count(self):
self.assertEqual(7, self.mutable_s.count("A"))
self.assertEqual(2, self.mutable_s.count("AA"))
def test_index(self):
self.assertEqual(2, self.mutable_s.index("A"))
self.assertRaises(ValueError, self.mutable_s.index, "8888")
def test_reverse(self):
"""Test using reverse method"""
self.mutable_s.reverse()
self.assertEqual(MutableSeq("GTACTACGTAGGAAAACT", IUPAC.ambiguous_dna),
self.mutable_s)
def test_reverse_with_stride(self):
"""Test reverse using -1 stride"""
self.assertEqual(MutableSeq("GTACTACGTAGGAAAACT", IUPAC.ambiguous_dna),
self.mutable_s[::-1])
def test_complement(self):
self.mutable_s.complement()
self.assertEqual(str("AGTTTTCCTACGTAGTAC"), str(self.mutable_s))
def test_complement_rna(self):
seq = Seq.MutableSeq("AUGaaaCUG", IUPAC.unambiguous_rna)
seq.complement()
self.assertEqual(str("UACuuuGAC"), str(seq))
def test_complement_mixed_aphabets(self):
seq = Seq.MutableSeq("AUGaaaCTG")
with self.assertRaises(ValueError):
seq.complement()
def test_complement_rna_string(self):
seq = Seq.MutableSeq("AUGaaaCUG")
seq.complement()
self.assertEqual('UACuuuGAC', str(seq))
def test_complement_dna_string(self):
seq = Seq.MutableSeq("ATGaaaCTG")
seq.complement()
self.assertEqual('TACtttGAC', str(seq))
def test_reverse_complement(self):
self.mutable_s.reverse_complement()
self.assertEqual("CATGATGCATCCTTTTGA", str(self.mutable_s))
def test_reverse_complement_of_protein(self):
seq = Seq.MutableSeq("ACTGTCGTCT", Alphabet.generic_protein)
with self.assertRaises(ValueError):
seq.reverse_complement()
def test_to_string_method(self):
"""This method is currently deprecated, probably will need to remove this test soon"""
with warnings.catch_warnings(record=True):
self.mutable_s.tostring()
def test_extend_method(self):
self.mutable_s.extend("GAT")
self.assertEqual(MutableSeq("TCAAAAGGATGCATCATGGAT", IUPAC.ambiguous_dna),
self.mutable_s)
def test_extend_with_mutable_seq(self):
self.mutable_s.extend(MutableSeq("TTT", IUPAC.ambiguous_dna))
self.assertEqual(MutableSeq("TCAAAAGGATGCATCATGTTT", IUPAC.ambiguous_dna),
self.mutable_s)
def test_delete_stride_slice(self):
del self.mutable_s[4:6 - 1]
self.assertEqual(MutableSeq("TCAAAGGATGCATCATG", IUPAC.ambiguous_dna),
self.mutable_s)
def test_extract_third_nucleotide(self):
"""Test extracting every third nucleotide (slicing with stride 3)"""
self.assertEqual(MutableSeq("TAGTAA", IUPAC.ambiguous_dna), self.mutable_s[0::3])
self.assertEqual(MutableSeq("CAGGTT", IUPAC.ambiguous_dna), self.mutable_s[1::3])
self.assertEqual(MutableSeq("AAACCG", IUPAC.ambiguous_dna), self.mutable_s[2::3])
def test_set_wobble_codon_to_n(self):
"""Test setting wobble codon to N (set slice with stride 3)"""
self.mutable_s[2::3] = "N" * len(self.mutable_s[2::3])
self.assertEqual(MutableSeq("TCNAANGGNTGNATNATN", IUPAC.ambiguous_dna),
self.mutable_s)
def viterbi(self, sequence, state_alphabet):
"""Calculate the most probable state path using the Viterbi algorithm.
This implements the Viterbi algorithm (see pgs 55-57 in Durbin et
al for a full explanation -- this is where I took my implementation
ideas from), to allow decoding of the state path, given a sequence
of emissions.
Arguments:
o sequence -- A Seq object with the emission sequence that we
want to decode.
o state_alphabet -- The alphabet of the possible state sequences
that can be generated.
"""
# calculate logarithms of the transition and emission probs
log_trans = self._log_transform(self.transition_prob)
log_emission = self._log_transform(self.emission_prob)
viterbi_probs = {}
pred_state_seq = {}
state_letters = state_alphabet.letters
# --- initialization
#
# NOTE: My index numbers are one less than what is given in Durbin
# et al, since we are indexing the sequence going from 0 to
# (Length - 1) not 1 to Length, like in Durbin et al.
#
# v_{0}(0) = 1
viterbi_probs[(state_letters[0], -1)] = 1
# v_{k}(0) = 0 for k > 0
for state_letter in state_letters[1:]:
viterbi_probs[(state_letter, -1)] = 0
# --- recursion
# loop over the training squence (i = 1 .. L)
for i in range(0, len(sequence)):
# now loop over all of the letters in the state path
for main_state in state_letters:
# e_{l}(x_{i})
emission_part = log_emission[(main_state, sequence[i])]
# loop over all possible states
possible_state_probs = {}
for cur_state in self.transitions_from(main_state):
# a_{kl}
trans_part = log_trans[(cur_state, main_state)]
# v_{k}(i - 1)
viterbi_part = viterbi_probs[(cur_state, i - 1)]
cur_prob = viterbi_part + trans_part
possible_state_probs[cur_state] = cur_prob
# finally calculate the viterbi probability using the max
max_prob = max(possible_state_probs.values())
viterbi_probs[(main_state, i)] = (emission_part + max_prob)
# now get the most likely state
for state in possible_state_probs.keys():
if possible_state_probs[state] == max_prob:
pred_state_seq[(i - 1, main_state)] = state
break
# --- termination
# calculate the probability of the state path
# loop over all letters
all_probs = {}
for state in state_letters:
# v_{k}(L)
viterbi_part = viterbi_probs[(state, len(sequence) - 1)]
# a_{k0}
transition_part = log_trans[(state, state_letters[0])]
all_probs[state] = viterbi_part * transition_part
state_path_prob = max(all_probs.values())
# find the last pointer we need to trace back from
last_state = ''
for state in all_probs.keys():
if all_probs[state] == state_path_prob:
last_state = state
assert last_state != '', "Didn't find the last state to trace from!"
# --- traceback
traceback_seq = MutableSeq('', state_alphabet)
loop_seq = range(0, len(sequence))
loop_seq.reverse()
cur_state = last_state
for i in loop_seq:
traceback_seq.append(cur_state)
cur_state = pred_state_seq[(i - 1, cur_state)]
# put the traceback sequence in the proper orientation
traceback_seq.reverse()
return traceback_seq.toseq(), state_path_prob
print seq[:5] #methods as string
print len(seq)
#seq[0]='C' #aren't mutables
st=str(seq) #toString
print st
#tipo de dato secuencia editable
from Bio.Seq import MutableSeq
mut_seq=seq.tomutable() #convertirlo a tipo seq mutable
print mut_seq
mut_seq[0]='C'
print mut_seq
mut_seq=MutableSeq('ATGCCG',IUPAC.IUPACUnambiguousDNA())
#has methods as a list: append(), insert(), pop(), remove()
mut_seq[1:3]='TTT'
mut_seq.reverse()
mut_seq.complement()
print mut_seq
mut_seq.reverse_complement()
print mut_seq
#tipo de dato metadatos de secuencia
from Bio.SeqRecord import SeqRecord
seqrec=SeqRecord(seq,id='001', name='My Secuencia')
#2 main attributes:
# id: string identifier, optional, recommended
# seq: Seq object, required
#additional attributes
# name, description: name and more info of sequence
# dbxrefs: list of strings, each string an id of a DB
# features: list of SeqFeature objects, those found in Genbank records
print id(seq1) == id(seq2) # seq1 == seq2 look for the same object
print str(seq1) == str(seq2) # convert to string
print str(seq1) == str(seq3) # dna similar enought to protein
#MutableSeq
from Bio.Seq import MutableSeq
mutseq = seq1.tomutable() # convert to MutableSeq
print mutseq, type(mutseq)
mutSeq = MutableSeq('CGTTTAAGCTGC',IUPAC.unambiguous_dna)
print mutSeq, type(mutSeq)
mutseq[1]='T' # imposible on simple Seq
print mutseq
seq1 = mutseq.toseq() # convert to Seq
mutSeq.remove('A') # remove first A
mutSeq[2:-5]='TTTT'
mutSeq.reverse() # reverse() and reverse_complement() change object itself
print mutSeq
#MutableSeq can't be a dictionary key, Seq and string can
#UnknownSeq
# Subclass of Seq when you know length but not the characters to save memory
from Bio.Seq import UnknownSeq
unk = UnknownSeq(25)
print unk, len(unk), type(unk)
unkDNA = UnknownSeq(20, alphabet=IUPAC.ambiguous_dna)
print unkDNA # N = any base
unkProt = UnknownSeq(10, alphabet=IUPAC.protein)
print unkProt # X = any aminoacid
print unkDNA.complement(), unkDNA.reverse_complement()
print unkDNA.transcribe(), unkDNA.translate()
