def scoreAlignmentList(alignmentList):
scoreList = []
queriesWithStops = []
minScore = 0
for al in alignmentList:
stopCodons = 0
queryScore = 0
alN = gaplessStrings(al)
ref = alN[0]
query = alN[1]
refAA = translate(ref)
#print(refAA)
queryAA = translate(query)
#print(queryAA)
for c in refAA:
if c == '*':
stopCodons += 1
for c in queryAA:
if c == '*':
stopCodons += 1
if stopCodons == 0:
queryScore = sum(score_pairwise(refAA, queryAA, blosum62, -5, -1))
#print(queryScore)
scoreList.append(queryScore)
if minScore > queryScore:
minScore = queryScore
else:
queriesWithStops.append(stopCodons)
#print("stopCodon")
#print("")
for stopCodonCount in queriesWithStops:
scoreList.append(stopCodonCount * minScore)
return scoreList
def break_up_frame(s):
"""Returns offset, nuc, protein."""
start = 0
for match in re_stops.finditer(s):
index = match.start() + 3
if index % 3 != 0:
continue
n = s[start:index]
if options.ftype == "CDS":
offset, n, t = start_chop_and_trans(n)
else:
offset = 0
t = translate(n, options.table, to_stop=True)
if n and len(t) >= options.min_len:
yield start + offset, n, t
start = index
if options.ends == "open":
# No stop codon, Biopython's strict CDS translate will fail
n = s[start:]
# Ensure we have whole codons
# TODO - Try appending N instead?
# TODO - Do the next four lines more elegantly
if len(n) % 3:
n = n[:-1]
if len(n) % 3:
n = n[:-1]
if options.ftype == "CDS":
offset, n, t = start_chop_and_trans(n, strict=False)
else:
offset = 0
t = translate(n, options.table, to_stop=True)
if n and len(t) >= options.min_len:
yield start + offset, n, t
def get_frame(geneseq, gene_HXB2, genename, VERBOSE=0):
'''Get the frame by aligning the proteins'''
from seqanpy import align_local
from Bio.Seq import translate
from numpy import argmax
geneseq = ''.join(geneseq)
gene_HXB2 = ''.join(gene_HXB2)
if genename in ('tat1', 'rev1'):
gene_HXB2 = gene_HXB2[:len(gene_HXB2) - (len(gene_HXB2) % 3)]
elif genename in ('tat2', 'rev2'):
gene_HXB2 = gene_HXB2[len(gene_HXB2) % 3:]
prot_HXB2 = translate(gene_HXB2)
scores = []
for frame in xrange(3):
tmp = geneseq[frame:]
tmp = tmp[:len(tmp) - (len(tmp) % 3)]
tmp = translate(tmp)
(score, ali1, ali2) = align_local(prot_HXB2, tmp)
scores.append(score)
return argmax(scores)
def test(dna,AA,codeline,iAA,fAA,cds,strand):
firstBreak = codeline.find(',')
secondBreak = codeline.find(',',firstBreak+1)
thirdBreak = codeline.find(',',secondBreak+1)
fourthBreak = codeline.rfind(',')
codonStartSite = int(codeline[firstBreak+1:secondBreak])
initialCodon = codeline[secondBreak+1:thirdBreak]
codonEndSite = int(codeline[thirdBreak+1:fourthBreak])
finalCodon = codeline[fourthBreak+1:]
TranslatableInitialCodon = initialCodon
TranslatableFinalCodon = finalCodon
if strand ==-1:
TranslatableInitialCodon = reverse_complement(initialCodon)
TranslatableFinalCodon = reverse_complement(finalCodon)
#TEST CASES
if AA != cds.qualifiers['translation'][0]: #protein seqs match up
print "AA seqs not equal"
return False
elif dna[codonStartSite-1:codonEndSite] != initialCodon: #codon that is being modified is where its supposed to be
print dna[codonStartSite-1:codonEndSite] +'!=' + initialCodon + " :so codeline doesnt match up"
return False
elif translate(TranslatableInitialCodon) != iAA: #starting codon is what its supposed to be
return False
elif translate(TranslatableFinalCodon) != fAA: #final codon is what its supposed to be
return False
else:
return True
def six_frame_translations(seq, genetic_code=1):
"""Formatted string showing the 6 frame translations and GC content.
nice looking 6 frame translation with GC content - code from xbbtools
similar to DNA Striders six-frame translation
e.g.
from Bio.SeqUtils import six_frame_translations
print six_frame_translations("AUGGCCAUUGUAAUGGGCCGCUGA")
"""
from Bio.Seq import reverse_complement, translate
anti = reverse_complement(seq)
comp = anti[::-1]
length = len(seq)
frames = {}
for i in range(0, 3):
frames[i + 1] = translate(seq[i:], genetic_code)
frames[-(i + 1)] = reverse(translate(anti[i:], genetic_code))
# create header
if length > 20:
short = "%s ... %s" % (seq[:10], seq[-10:])
else:
short = seq
# TODO? Remove the date as this would spoil any unit test...
date = time.strftime("%y %b %d, %X", time.localtime(time.time()))
header = "GC_Frame: %s, " % date
for nt in ["a", "t", "g", "c"]:
header += "%s:%d " % (nt, seq.count(nt.upper()))
header += "\nSequence: %s, %d nt, %0.2f %%GC\n\n\n" % (short.lower(), length, GC(seq))
res = header
for i in range(0, length, 60):
subseq = seq[i : i + 60]
csubseq = comp[i : i + 60]
p = i / 3
res = res + "%d/%d\n" % (i + 1, i / 3 + 1)
res = res + " " + " ".join(map(None, frames[3][p : p + 20])) + "\n"
res = res + " " + " ".join(map(None, frames[2][p : p + 20])) + "\n"
res = res + " ".join(map(None, frames[1][p : p + 20])) + "\n"
# seq
res = res + subseq.lower() + "%5d %%\n" % int(GC(subseq))
res = res + csubseq.lower() + "\n"
# - frames
res = res + " ".join(map(None, frames[-2][p : p + 20])) + " \n"
res = res + " " + " ".join(map(None, frames[-1][p : p + 20])) + "\n"
res = res + " " + " ".join(map(None, frames[-3][p : p + 20])) + "\n\n"
return res
def check_translation(sequence, translation, table=None) :
if table is None :
#Seq method:
if translation != str(sequence.translate()) \
or translation != str(translate(sequence)) \
or translation != translate(str(sequence)) :
raise ValueError("%s -> %s" % (sequence, translation))
else:
if translation != str(sequence.translate(table)) \
or translation != str(translate(sequence,table)) \
or translation != translate(str(sequence),table) :
raise ValueError("%s -> %s (table %s)" \
% (sequence, translation, table))
return True
def get_our_costs_at_Rihn(costs_Rihn, costs_ours, data, aa_mutation_rates):
'''Get our costs at their positions'''
c = costs_ours.set_index('pos').loc[costs_Rihn['pos']]['median']
costs_Rihn_by_pos = costs_Rihn.set_index('pos')
c_float = []
c_IQD_target_specfic = []
for (p, mut), ci in zip(costs_Rihn_by_pos.iterrows(), c):
if ci == '<0.001':
ci = 0
elif ci == '>0.1':
ci = 1
else:
ci = float(ci)
c_float.append(ci)
cons, ipos, target_aa = mut['mut'][0], int(mut['mut'][1:-1]), mut['mut'][-1]
ipos +=714
print(cons, mut['NL4-3'], translate(data['init_codon']['pol']['p2'][ipos]))
c_IQD_target_specfic.append(fitness_cost_mutation('pol', data,
aa_mutation_rates, ipos,
target_aa, nbootstraps=100))
c[:] = c_float
c_IQD_target_specfic = np.array(c_IQD_target_specfic)
comp = (pd.concat([c, costs_Rihn.set_index('pos')['cost']], axis=1)
.rename(columns={'median': 'ours', 'cost': 'Rihn'}))
return comp, c_IQD_target_specfic
def find_frame(read):
"""Frame is the one with the smallest number of stop codons
"""
from Bio.Seq import translate
import Bio
# use this to cut read at multiple of three length
rem = len(read) % 3
last_pos = rem if rem else None
try:
read = read[:-last_pos]
except TypeError:
pass
assert len(read) % 3 == 0, read
read_len = len(read) - 3
try:
counts = [(translate(read[f : read_len + f]).count("*"), f + 1) for f in range(3)]
except Bio.Data.CodonTable.TranslationError:
counts = [(gap_translation(read[f:]).count("*"), f + 1) for f in range(3)]
sor_cnt = sorted(counts)
stop_codons, frame = sor_cnt[0]
if stop_codons > 0:
warnings.warn("The sequence %s contains %dstop codons" % (read, stop_codons))
if sor_cnt[1][0] == 0:
warnings.warn("Two frames are possible! %d and %d" % (frame, sor_cnt[1][1]))
return frame
def PTRA(DNA,protein):
index = []
for i in [1,2,3,4,5,6,9,10,11,12,13,14,15]:
p = translate(DNA, table=i, stop_symbol='*', to_stop=True)
if p == protein:
index.append(i)
return index
def get_local_codon(self, mutations, pos, mut=None):
codon_pos = pos%3
codon_seq = mutations[pos - codon_pos:pos + 3 - codon_pos]
codon_seq = ''.join(map(lambda _x: _x['ref'], codon_seq))
if mut:
codon_seq = codon_seq[:codon_pos]+ mut + codon_seq[codon_pos + 1:]
return translate(codon_seq)
def translate_with_gaps(seq):
'''Translate sequence with gaps'''
from Bio.SeqRecord import SeqRecord
from Bio.Seq import Seq, translate
from Bio.Alphabet.IUPAC import protein
L = len(seq)
if L % 3:
raise ValueError('The sequence length is not a multiple of 3')
seqstr = ''.join(seq)
prot = []
for i in xrange(L // 3):
codon = seqstr[3 * i: 3 * (i+1)]
if codon == '---':
prot.append('-')
elif '-' in codon:
raise ValueError('Non-aligned gaps found')
else:
prot.append(''.join(translate(codon)))
prot = ''.join(prot)
# Output in various formats
if isinstance(seq, basestring):
return prot
elif isinstance(seq, Seq):
return Seq(prot, protein)
elif isinstance(seq, SeqRecord):
return SeqRecord(Seq(prot, protein), id=seq.id, name=seq.name,
description=seq.description)
else:
import numpy as np
return np.fromstring(prot, 'S1')
def get_translation(self,sequence=None):
translation = None
seq = sequence if sequence else self.get_spliced_seq()
if seq:
seqlen = len(seq) / 3 * 3;
if seqlen >= 3:
translation = translate(seq[:seqlen])
return translation
def main(filename):
with open(filename) as fin:
dna, prot = fin.read().strip().split('\n')
res = 1
while translate(dna, table=res, stop_symbol='') != prot:
res += 1
print res
def check_translation(sequence, translation, table=None):
if table is None:
t = 1
else:
t = table
if translation != str(sequence.translate(t)) \
or translation != str(translate(sequence, t)) \
or translation != translate(str(sequence), t):
# More details...
for i, amino in enumerate(translation):
codon = sequence[i * 3:i * 3 + 3]
if amino != str(codon.translate(t)):
raise ValueError("%s -> %s not %s (table %s)"
% (codon, amino, codon.translate(t), t))
# Shouldn't reach this line:
raise ValueError("%s -> %s (table %s)"
% (sequence, translation, t))
return True
def translate_read(self, read, start, end):
trimmed_read, offset = self.trim_read(read, start, end, codon=True)
prot_seq = translate(trimmed_read[offset:])
prot_start = (read.pos + offset - start) / 3
if prot_start < 0:
prot_start = 0
return prot_seq, prot_start
def start_chop_and_trans(s, strict=True):
"""Returns offset, trimmed nuc, protein."""
if strict:
assert s[-3:] in stops, s
assert len(s) % 3 == 0
for match in re_starts.finditer(s):
# Must check the start is in frame
start = match.start()
if start % 3 == 0:
n = s[start:]
assert len(n) % 3 == 0, "%s is len %i" % (n, len(n))
if strict:
t = translate(n, options.table, cds=True)
else:
# Use when missing stop codon,
t = "M" + translate(n[3:], options.table, to_stop=True)
return start, n, t
return None, None, None
def frame(self, seq, frame, translation_table = 1):
if not ((-3 <= frame <= -1) or (1 <= frame <= 3)):
frame = 1
if frame != 1:
raise NotImplementedError
#TODO - Support the frame argument
#The old code didn't, but I can guess from
#the code the expected 1,2,3 for the forward
#strands and -1,-2,-3 for the reverse.
return translate(seq, table=translation_table)
def dNdS(self, reference, start, end):
ps, pn = 0, 0
n_codon = (end - start) / 3
for i in range(start, end, 3):
ref_codon = reference[i-start:i-start+3]
ref_aa = translate(ref_codon)
s_i, n_i = self._dNdS_sites(ref_codon)
if s_i == 0: continue
m_i = 0
inner_s, inner_n = 0, 0
reads = self.samfile.fetch('CONSENSUS_B_GAG_POL', start, end)
for read in reads:
trimmed_read = self.trim_read(read, i, i+3, codon=False)
if len(trimmed_read) < 3: continue
m_i += 1
cur_pos = read.pos - i
if cur_pos < 0:
cur_pos = 0
sij, nij = 0, 0
for j, nt in enumerate(trimmed_read):
if nt == ref_codon[j]: continue
mut_codon = ref_codon[:j] + nt + ref_codon[j+1:]
if translate(mut_codon) == ref_aa:
sij += 1
else:
nij += 1
inner_s += sij / s_i
inner_n += nij / n_i
ps += inner_s / m_i
pn += inner_n / m_i
ps /= float(n_codon)
pn /= float(n_codon)
ds = -.75 * np.log(1 - 4*ps/3)
dn = -.75 * np.log(1 - 4*pn/3)
print ds/dn
def _dNdS_sites(self, codon):
syn = 0
non = 0
alphabet = 'ACGT'
aa = translate(codon)
if len(codon) < 3: return syn, non
for i in range(3):
for mut in alphabet:
if mut == codon[i]: continue
mut_codon = codon[:i] + mut + codon[i+1:]
syn_flag = (aa == translate(mut_codon))
syn += syn_flag
non += (not syn_flag)
syn /= 3.
non /= 3.
assert syn + non == 3
return syn, non
def transl(seq):
out_seq = ""
for codon in codons(seq):
if codon == '---':
aa = '-'
elif codon == '...':
aa = '.'
else:
aa = translate(codon)
out_seq += aa
return out_seq
def six_frames(seq, genetic_code=1):
'''
input a DNA sequence
pad to a whole number of codons if required
probably only works for ambiguous alphabet sequences
return the six possible protein translations
'''
rev = reverse_complement(seq)
frames = {}
for i in [0,1,2]:
l = len(seq) - i
j = i + l - l%3
frames['%+d'%i] = translate(seq[i:j],genetic_code)
frames['-%d'%i] = translate(rev[i:j],genetic_code)
return frames
def writeSTF():
global difference, seqRecordToCheck, seqRecordToCheckComplement, variation, featureName, featureSeq, seqLength, m
difference = len(record.seq) % 3
seqRecordToCheck = str(record.seq)
if difference != 0:
seqRecordToCheck = str(record.seq)[:-difference]
else:
seqRecordToCheck = str(record.seq)
seqRecordToCheckComplement = str(reverse_complement(seqRecordToCheck))
# Reading Frames
firstReadingFrame = translate(seqRecordToCheck)
secondReadingFrame = translate(seqRecordToCheck[1::] + seqRecordToCheck[0])
thirdReadingFrame = translate(seqRecordToCheck[2::] + seqRecordToCheck[0:2])
# Reading Frames (reverseComplement)
firstReadingFrameComplement = translate(seqRecordToCheckComplement)
secondReadingFrameComplement = translate(seqRecordToCheckComplement[1::] + seqRecordToCheckComplement[0])
thirdReadingFrameComplement = translate(seqRecordToCheckComplement[2::] + seqRecordToCheckComplement[0:2])
for variation in featureStatistic_container[feature]:
featureName = variation.note
featureSeq = str(variation.seq)
featureLength = len(variation.seq)
seqLength = len(seqRecordToCheck)
firstReadingFrameCircular = firstReadingFrame + firstReadingFrame[0:featureLength - 1]
secondReadingFrameCircular = secondReadingFrame + secondReadingFrame[0:featureLength - 1]
thirdReadingFrameCircular = thirdReadingFrame + thirdReadingFrame[0:featureLength - 1]
firstReadingFrameComplementCircular = firstReadingFrameComplement + firstReadingFrameComplement[
0:featureLength - 1]
secondReadingFrameComplementCircular = secondReadingFrameComplement + secondReadingFrameComplement[
0:featureLength - 1]
thirdReadingFrameComplementCircular = thirdReadingFrameComplement + thirdReadingFrameComplement[
0:featureLength - 1]
# Find Matches
firstFrameMatchesCircular = re.finditer(featureSeq, firstReadingFrameCircular)
secondFrameMatchesCircular = re.finditer(featureSeq, secondReadingFrameCircular)
thirdFrameMatchesCircular = re.finditer(featureSeq, thirdReadingFrameCircular)
firstFrameComplementMatchesCircular = re.finditer(featureSeq, firstReadingFrameComplementCircular)
secondFrameComplementMatchesCircular = re.finditer(featureSeq, secondReadingFrameComplementCircular)
thirdFrameComplementMatchesCircular = re.finditer(featureSeq, thirdReadingFrameComplementCircular)
for m in firstFrameMatchesCircular:
addFeatureSTF()
for m in secondFrameMatchesCircular:
addFeatureSTF()
for m in thirdFrameMatchesCircular:
addFeatureSTF()
for m in firstFrameComplementMatchesCircular:
addFeatureComplSTF()
for m in secondFrameComplementMatchesCircular:
addFeatureComplSTF()
for m in thirdFrameComplementMatchesCircular:
addFeatureComplSTF()
def ptra():
with open("rosalind_ptra.txt") as f:
dna = f.readline().strip()
prot = f.readline().strip()
print dna
print prot
table = 1
while translate(dna, table=table, to_stop=True) != prot:
table += 1
print table
def align_codon_pairwise(seqstr, refstr, **kwargs):
'''Pairwise alignment via codons
Parameters:
**kwargs: passed down to SeqAn alignment function
'''
from Bio.Seq import translate
from seqanpy import align_global
from itertools import izip
if len(seqstr) % 3:
raise ValueError('The length of the first sequence is not a multiple of 3')
elif len(refstr) % 3:
raise ValueError('The length of the second sequence is not a multiple of 3')
seqpr = translate(seqstr)
refpr = translate(refstr)
(score, alis, alir) = align_global(seqpr, refpr, **kwargs)
aliseq = []
aliref = []
poss = 0
posr = 0
for aas, aar in izip(alis, alir):
if aas == '-':
aliseq.append('---')
else:
aliseq.append(seqstr[poss: poss+3])
poss += 3
if aar == '-':
aliref.append('---')
else:
aliref.append(refstr[posr: posr+3])
posr += 3
aliseq = ''.join(aliseq)
aliref = ''.join(aliref)
return (aliseq, aliref)
def writeBothToFile(seqFileName, newSeqLength, randFileName, transFileName):
randOutFile = open(randFileName, "w")
randOutFile.write("> Randomly generated gene of length %d \n" % int(newSeqLength))
transOutFile = open(transFileName, "w")
transOutFile.write("> AA translation and untranslation of randomly generated gene of length %d\n" % int(newSeqLength))
sequence = generateRandomGene(seqFileName, newSeqLength)
randOutFile.write(sequence)
seqPerm = untranslate(translate(sequence))
transOutFile.write(seqPerm)
randOutFile.close()
transOutFile.close()
def get_protein(record, feature):
protein = {}
protein['identifier'] = fasta_identifier(flatten(feature.qualifiers))
protein['description'] = mygetattr(feature.qualifiers, 'product', '')
# prefer the annotated translation versus our own one
if feature.qualifiers.has_key('translation'):
# what if more than one translation?
protein['sequence'] = feature.qualifiers['translation'].pop(0)
else:
protein['sequence'] = translate(get_seq_0_based(record.seq.data, feature.location.nofuzzy_start, feature.location.nofuzzy_end, feature.strand))
if not len(protein['sequence']):
print >>sys.stderr, "could not translate %s" % (protein['identifier'])
return protein
def test_the_translation_of_stops(self):
"""Check obj.translate() method with stop codons."""
misc_stops = "TAATAGTGAAGAAGG"
for nuc in [Seq(misc_stops),
Seq(misc_stops, generic_nucleotide),
Seq(misc_stops, generic_dna),
Seq(misc_stops, unambiguous_dna)]:
self.assertEqual("***RR", str(nuc.translate()))
self.assertEqual("***RR", str(nuc.translate(1)))
self.assertEqual("***RR", str(nuc.translate("SGC0")))
self.assertEqual("**W**", str(nuc.translate(table=2)))
self.assertEqual("**WRR",
str(nuc.translate(table='Yeast Mitochondrial')))
self.assertEqual("**WSS", str(nuc.translate(table=5)))
self.assertEqual("**WSS", str(nuc.translate(table=9)))
self.assertEqual("**CRR", str(nuc.translate(table='Euplotid Nuclear')))
self.assertEqual("***RR", str(nuc.translate(table=11)))
self.assertEqual("***RR", str(nuc.translate(table='11')))
self.assertEqual("***RR", str(nuc.translate(table='Bacterial')))
self.assertEqual("**GRR", str(nuc.translate(table=25)))
self.assertEqual("", str(nuc.translate(to_stop=True)))
self.assertEqual("O*ORR", str(nuc.translate(table=special_table)))
self.assertEqual("*QWRR",
str(nuc.translate(table=Chilodonella_uncinata_table)))
# These test the Bio.Seq.translate() function - move these?:
self.assertEqual("*QWRR",
translate(str(nuc), table=Chilodonella_uncinata_table))
self.assertEqual("O*ORR", translate(str(nuc), table=special_table))
self.assertEqual("", translate(str(nuc), to_stop=True))
self.assertEqual("***RR", translate(str(nuc), table='Bacterial'))
self.assertEqual("***RR", translate(str(nuc), table='11'))
self.assertEqual("***RR", translate(str(nuc), table=11))
self.assertEqual("**W**", translate(str(nuc), table=2))
self.assertEqual(str(Seq("TAT").translate()), "Y")
self.assertEqual(str(Seq("TAR").translate()), "*")
self.assertEqual(str(Seq("TAN").translate()), "X")
self.assertEqual(str(Seq("NNN").translate()), "X")
self.assertEqual(str(Seq("TAt").translate()), "Y")
self.assertEqual(str(Seq("TaR").translate()), "*")
self.assertEqual(str(Seq("TaN").translate()), "X")
self.assertEqual(str(Seq("nnN").translate()), "X")
self.assertEqual(str(Seq("tat").translate()), "Y")
self.assertEqual(str(Seq("tar").translate()), "*")
self.assertEqual(str(Seq("tan").translate()), "X")
self.assertEqual(str(Seq("nnn").translate()), "X")
def translations(self):
"""
Yield all six translations of a nucleotide sequence.
@return: A generator that produces six L{TranslatedRead} instances.
"""
rc = self.reverseComplement().sequence
for reverseComplemented in False, True:
for frame in 0, 1, 2:
seq = rc if reverseComplemented else self.sequence
# Get the suffix of the sequence for translation. I.e.,
# skip 0, 1, or 2 initial bases, depending on the frame.
# Note that this makes a copy of the sequence, which we can
# then safely append 'N' bases to to adjust its length to
# be zero mod 3.
suffix = seq[frame:]
lengthMod3 = len(suffix) % 3
if lengthMod3:
suffix += ('NN' if lengthMod3 == 1 else 'N')
yield TranslatedRead(self, translate(suffix), frame,
reverseComplemented)
def apply_operation():
"""Do the selected operation."""
codon_table = codon_list.get(codon_list.curselection())
print('Code: {}'.format(codon_table))
seq = ''.join(input_text.get(1.0, tk.END).split())
print('Input sequence: {}'.format(seq))
operation = transform_var.get()
print('Operation: {}'.format(operation))
if operation == 'transcribe':
result = transcribe(seq)
elif operation == 'translate':
result = translate(seq, table=codon_table, to_stop=True)
elif operation == 'back transcribe':
result = back_transcribe(seq)
else:
result = ''
output_text.delete(1.0, tk.END)
output_text.insert(tk.END, result)
print('Result: {}'.format(result))
return
def process_seq(header, seq):
hits = 0
id = header
if id.count(" ") > 0: id = id[:id.index(" ")]
seq = Seq(seq)
# direction1 is the direction we originally have had, 2 is the antisense strand
# then TRANSLATE ALL POSSIBLE ORFs, do not stop at STOP codons
dna_sequence_direction1 = seq
dna_sequence_direction2 = dna_sequence_direction1.reverse_complement()
translations = {}
translations['+1'] = translate(dna_sequence_direction1)
translations['-1'] = translate(dna_sequence_direction2)
translations['+2'] = translate(dna_sequence_direction1[1:])
translations['-2'] = translate(dna_sequence_direction2[1:])
translations['+3'] = translate(dna_sequence_direction1[2:])
translations['-3'] = translate(dna_sequence_direction2[2:])
# get all polypeptides between stops, filter out those shorter than minlength
polypeptides = {}
for frame, translation in translations.iteritems():
peptides = translation.split('*')
if int(frame) < 0: startpos = len(seq) +1 + int(frame)
else: startpos = int(frame)
#print >> sys.stderr, "frame: %s | startpos: %s | scaffold length: %s" %(frame, startpos, len(seq))
#print >> sys.stderr, "# peptides: %s | pep.length: %s | transformed length: %s | scaffold length: %s" %(len(peptides), sum([len(pep) for pep in peptides]), (sum([len(pep) for pep in peptides])+len(peptides))*3, len(seq))
for peptide in peptides:
peptide += '*'
if int(frame) < 0: stoppos = startpos +1 - (3*len(peptide))
else: stoppos = startpos -1 + (3*len(peptide))
polypeptides[str(startpos)+':'+str(stoppos)] = peptide.tostring()
if int(frame) < 0: startpos = stoppos-1
else: startpos = stoppos+1
for key, pepseq in polypeptides.iteritems():
if len(pepseq) < args['minlength']: continue
startpos, stoppos = [int(e) for e in key.split(":")]
hits += 1
print ">%s[%s:%s]" %( id, startpos, stoppos )
print pepseq
return hits
def translate_dna_prot(dna,prot):
for i in ncbi_ids:
if translate(dna, stop_symbol="",table=i) == prot:
return i
def frame(self, seq, frame, translation_table=1):
if frame < 0:
seq = reverse_complement(seq)
seq = seq[(abs(frame) - 1):]
return translate(seq, table=translation_table)
# if we want to transcribe from the template strand (3' -> 5'):
transcribe(template_dna.reverse_complement())
# transcribing back to DNA:
from Bio.Seq import Seq, back_transcribe
back_transcribe(
messenger_rna) # just changes U -> T and gives the coding strand
# 3.8 Translation (mRNA -> Protein)
# Uses standard genetic code
from Bio.Seq import Seq, translate
from Bio.Alphabet import IUPAC
messenger_rna = Seq("AUGGCCAUUGUAAUGGGCCGCUGAAAGGGUGCCCGAUAG",
IUPAC.unambiguous_rna)
translate(messenger_rna)
# Direct translation (DNA -> Protein
from Bio.Seq import Seq, translate
from Bio.Alphabet import IUPAC
coding_dna = Seq("ATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAG",
IUPAC.unambiguous_dna)
translate(coding_dna)
# we can specify other translation tables by name
translate(coding_dna, table="Vertebrate Mitochondrial")
# or by NCBI number
translate(coding_dna, table=2)
# 3.9 Transcription and Translation
def six_frame_translations(seq, genetic_code=1):
"""Return pretty string showing the 6 frame translations and GC content.
Nice looking 6 frame translation with GC content - code from xbbtools
similar to DNA Striders six-frame translation
>>> from Bio.SeqUtils import six_frame_translations
>>> print(six_frame_translations("AUGGCCAUUGUAAUGGGCCGCUGA"))
GC_Frame: a:5 t:0 g:8 c:5
Sequence: auggccauug ... gggccgcuga, 24 nt, 54.17 %GC
<BLANKLINE>
<BLANKLINE>
1/1
G H C N G P L
W P L * W A A
M A I V M G R *
auggccauuguaaugggccgcuga 54 %
uaccgguaacauuacccggcgacu
A M T I P R Q
H G N Y H A A S
P W Q L P G S
<BLANKLINE>
<BLANKLINE>
""" # noqa for pep8 W291 trailing whitespace
from Bio.Seq import reverse_complement, reverse_complement_rna, translate
if "u" in seq.lower():
anti = reverse_complement_rna(seq)
else:
anti = reverse_complement(seq, inplace=False) # TODO: remove inplace=False
comp = anti[::-1]
length = len(seq)
frames = {}
for i in range(0, 3):
fragment_length = 3 * ((length - i) // 3)
frames[i + 1] = translate(seq[i : i + fragment_length], genetic_code)
frames[-(i + 1)] = translate(anti[i : i + fragment_length], genetic_code)[::-1]
# create header
if length > 20:
short = "%s ... %s" % (seq[:10], seq[-10:])
else:
short = seq
header = "GC_Frame:"
for nt in ["a", "t", "g", "c"]:
header += " %s:%d" % (nt, seq.count(nt.upper()))
header += "\nSequence: %s, %d nt, %0.2f %%GC\n\n\n" % (
short.lower(),
length,
GC(seq),
)
res = header
for i in range(0, length, 60):
subseq = seq[i : i + 60]
csubseq = comp[i : i + 60]
p = i // 3
res += "%d/%d\n" % (i + 1, i / 3 + 1)
res += " " + " ".join(frames[3][p : p + 20]) + "\n"
res += " " + " ".join(frames[2][p : p + 20]) + "\n"
res += " ".join(frames[1][p : p + 20]) + "\n"
# seq
res += subseq.lower() + "%5d %%\n" % int(GC(subseq))
res += csubseq.lower() + "\n"
# - frames
res += " ".join(frames[-2][p : p + 20]) + "\n"
res += " " + " ".join(frames[-1][p : p + 20]) + "\n"
res += " " + " ".join(frames[-3][p : p + 20]) + "\n\n"
return res
def dna_to_amino_acid(dna_seq):
return translate(dna_seq)
from Bio.Seq import translate
with open("rosalind_prot.txt") as p:
myfile = p.read()
print(translate(myfile, stop_symbol=""))
def translation(DNA):
return translate(DNA, to_stop=True)
import warnings
from Bio.Alphabet import IUPAC
from Bio.Seq import Seq, translate
warnings.filterwarnings('ignore')
with open('rosalind_orfr.txt', 'r') as f:
seq_text = f.read().strip()
seq = Seq(seq_text, IUPAC.unambiguous_dna)
DNAs = [seq, seq.reverse_complement()]
longest_protein = ''
for i in range(3):
for DNA in DNAs:
protein = translate(DNA[i:], to_stop=True)
if len(longest_protein) < len(protein):
longest_protein = protein
print(longest_protein)
from Bio.Seq import translate
DNA_seq=open("rosalind_orfr.txt","r").read().rstrip()
rc_seq = DNA_seq.replace("A", 't').replace("C", 'g').replace("G", 'c').replace("T", 'a')[::-1].upper()
forward_orf_ind =[i for i in range(len(DNA_seq)-3+1) if DNA_seq[i:i+3] == 'ATG']
reverse_orf_ind =[i for i in range(len(rc_seq)-3+1) if rc_seq[i:i+3] == 'ATG']
list_of_AASeq = []
for idx in forward_orf_ind:
list_of_AASeq.append(translate(DNA_seq[idx:], to_stop=True))
for idx in reverse_orf_ind:
list_of_AASeq.append(translate(rc_seq[idx:], to_stop=True))
print max(list_of_AASeq, key=len)
def check_emboss_translate(self, sequence, table=None, frame=None):
"""Call transeq, returns protein sequence as string."""
# TODO - Support transeq in Bio.Emboss.Applications?
# (doesn't seem worthwhile as Biopython can do translations)
# Setup,
cline = exes["transeq"]
if len(sequence) < 100:
filename = None
cline += " -sequence asis:%s" % sequence
else:
# There are limits on command line string lengths...
# use a temp file instead.
filename = "Emboss/temp_transeq.txt"
SeqIO.write(SeqRecord(sequence, id="Test"), filename, "fasta")
cline += " -sequence %s" % filename
cline += " -auto" # no prompting
cline += " -filter" # use stdout
if table is not None:
cline += " -table %s" % str(table)
if frame is not None:
cline += " -frame %s" % str(frame)
# Run the tool,
child = subprocess.Popen(
str(cline),
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
universal_newlines=True,
shell=(sys.platform != "win32"),
)
out, err = child.communicate()
msg = "cline='%s'" % cline
# Check no error output:
self.assertEqual(err, "", msg=msg)
# Check we could read its output
record = SeqIO.read(StringIO(out), "fasta")
result = child.wait()
self.assertEqual(result, 0, msg=msg)
if filename:
os.remove(filename)
self.assertTrue(record.id.startswith("Test"), msg=msg)
else:
self.assertTrue(record.id.startswith("asis"), msg=msg)
translation = record.seq
if table is None:
table = 1
self.assertEqual(translation, sequence.translate(table))
self.assertEqual(translation, translate(sequence, table))
self.assertEqual(translation, translate(str(sequence), table))
# More details...
for i, amino in enumerate(translation):
codon = sequence[i * 3 : i * 3 + 3]
msg = "codon %s, table %s" % (codon, table)
self.assertEqual(amino, codon.translate(table), msg=msg)
def dna2prot(seq):
"""Translate DNA sequence to protein sequence"""
return translate(Seq(seq)).tostring()
def collect_ccds_record(listObject, data_dict, rev=True):
orderCCDS = dict()
record_with_frame = dict()
record_original = dict()
new_gene_list = dict()
for geneName in listObject:
record_with_frame[geneName] = list()
record_original[geneName] = list()
try:
ccds_object = data_dict[geneName]
except KeyError:
continue
if rev == True:
ccds_positions = sorted([(int(x.split("-")[0]),
int(x.split("-")[1]))
for x in ccds_object["pos"]])[::-1]
else:
ccds_positions = sorted([(int(x.split("-")[0]),
int(x.split("-")[1]))
for x in ccds_object["pos"]])
orderCCDS[geneName] = ccds_positions
remaining = 0
first_flag = False
for seq_coord in ccds_positions:
flagThing = False
while flagThing != True:
try:
handle_in = Entrez.efetch(db="nucleotide",
id=ccds_object["id"],
rettype="fasta",
strand=+1,
seq_start=seq_coord[0] + 1,
seq_stop=seq_coord[1] + 1)
record = SeqIO.read(handle_in, "fasta")
flagThing = True
except (IOError, httplib.HTTPException):
continue
if first_flag == False:
if len(record.seq) % 3 != 0:
if rev == True:
sequenceObj = record.seq.reverse_complement() + Seq(
"N" * (3 - len(record.seq) % 3), generic_dna)
record_original[geneName].append(
[record.id, str(sequenceObj)])
else:
sequenceObj = record.seq + Seq(
"N" * (3 - len(record.seq) % 3), generic_dna)
record_original[geneName].append(
[record.id, str(sequenceObj)])
inseq = translate(sequenceObj)
if "*" in inseq:
new_gene_list.append(geneName)
break
remaining = len(record.seq) % 3
record.seq = inseq
else:
if rev == True:
sequenceObj = record.seq.reverse_complement()
record_original[geneName].append(
[record.id, str(sequenceObj)])
else:
sequenceObj = record.seq
record_original[geneName].append(
[record.id, str(sequenceObj)])
remaining = len(record.seq) % 3
record.seq = translate(sequenceObj)
first_flag = True
elif first_flag == True:
if remaining != 0:
if rev == True:
sequenceObj = Seq(
"N" * (remaining),
generic_dna) + record.seq.reverse_complement()
else:
sequenceObj = Seq("N" * (remaining),
generic_dna) + record.seq
remaining = len(sequenceObj) % 3
if len(sequenceObj) % 3 != 0:
sequenceObj = sequenceObj + Seq(
"N" * (3 - len(sequenceObj) % 3), generic_dna)
record_original[geneName].append(
[record.id, str(sequenceObj)])
inseq = translate(sequenceObj)
record.seq = inseq
elif len(record.seq) % 3 != 0:
if rev == True:
sequenceObj = record.seq.reverse_complement() + Seq(
"N" * (3 - len(record.seq) % 3), generic_dna)
else:
sequenceObj = record.seq + Seq(
"N" * (3 - len(record.seq) % 3), generic_dna)
record_original[geneName].append(
[record.id, str(sequenceObj)])
inseq = translate(sequenceObj)
remaining = len(record.seq) % 3
record.seq = inseq
else:
if rev == True:
sequenceObj = record.seq.reverse_complement()
else:
sequenceObj = record.seq
record_original[geneName].append(
[record.id, str(sequenceObj)])
remaining = len(sequenceObj) % 3
record.seq = translate(sequenceObj)
if record.seq.count("*") > 1:
new_gene_list.append(geneName)
break
print(geneName, record.id, record.seq)
record_with_frame[geneName].append(record)
handle_in.close()
return record_with_frame, set(new_gene_list), orderCCDS, record_original
from Bio import SeqIO
from Bio.Seq import Seq, transcribe, translate
import sys
file_out = 'gene_seq_out.fasta'
if __name__ == '__main__':
# filenames_list = list of entered arguments from command line.
file_in = sys.argv[:1]
#Open output file and write
with open(file_out, 'w') as f_out:
#as file_in is a list, could have more than one file so we need to iterate.
for filename in file_in:
#my_sequence_recorded_iterable is a list, each sequence of the file will have a sequence record,
#the record is composed by seq, id, name and description.
my_sequence_recorded_iterable = list(
SeqIO.parse(open(filename, mode='r'), 'fasta'))
# if the length of the list is empty print a warning and write to stderr.
if len(my_sequence_recorded_iterable) == 0:
print(f'WARNING file: {filename}: Empty file', file=sys.stderr)
#now we will iterate on my_sequence_recorded_iterable list, with seq_record elements
for seq_record in my_sequence_recorded_iterable:
#seq_record.description=' '.join(seq_record.description.split()[1:]) in here I edit the description
# as it originally contains the id.
# we now write each iterated sequence 'seq_record' in our output file f_out as fasta format.
SeqIO.write(seq_record, f_out, 'fasta')
#We now print to stdoout.
print('>' + seq_record.id)
print(translate(seq_record.seq))
#!/usr/bin/python
'''
translate nucleotide sequences into protein sequences
'''
import sys,argparse
import rjvbio.seq
import Bio.SeqIO,Bio.SeqRecord
from Bio.Seq import translate, Seq
ap = argparse.ArgumentParser(description=__doc__,formatter_class=argparse.ArgumentDefaultsHelpFormatter)
ap.add_argument('--inp',nargs='+',required=True,type=str,help='input sequence file(s)')
ap.add_argument('--inpformat',default='fasta',type=str,help='format of input file(s), eg fasta,fastq,genbank see http://biopython.org/wiki/SeqIO#File_Formats for details')
ap.add_argument('--out',default='STDOUT',type=str,help='output FASTA file')
conf = ap.parse_args()
if conf.out == 'STDOUT':
fout = sys.stdout
else:
fout = open(conf.out,'wb')
for fname in conf.inp:
for rec in Bio.SeqIO.parse(fname,conf.inpformat):
seq = translate(rec.seq)
newrec = Bio.SeqRecord.SeqRecord(seq, id=rec.id,description='')
Bio.SeqIO.write(newrec,fout,"fasta")
if conf.out != 'STDOUT': fout.close()
# (at your option) any later version.
# This software is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with GNU Emacs. If not, see <http://www.gnu.org/licenses/>
from Bio.Seq import translate
import sys
with open('c:/Users/Weka/Downloads/rosalind_ptra(2).txt') as f:
i = 0
for line in f:
print(line.strip())
if i == 0:
coding_dna = line.strip()
if i == 1:
out = line.strip()
for table in [1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 13, 14, 15]:
print(table)
translated = translate(coding_dna, table=table, to_stop=True)
# if len(translated)==len(out):
if translated == out:
print(table, translated)
sys.exit()
print('Not matched: ' + translated)
i += 1
def translate(self, codon_table):
seq = "".join(self.src_text.GetValue().split()) # remove whitespace
print(seq)
self.dest_text.Clear()
self.dest_text.SetValue(translate(seq, table=codon_table,
to_stop=True))
from Bio.Seq import translate
dna = "ATGCAGACCAAACACGAGCAGTTCCGTGCGCAATCCGCGACCGCCGGATCTTCTAGTCACTGGACCACCTCGACCACCTTCGGAACCGAGTCTCTGGCGGATAAGCGTGGGCTGGATATCCCGACGTCCCGATTCGCAGTTACACCAGTATCCGCCAACGGACACGATGGTTTTGAGATCGCTCACTCCGACGCTCCTCGCCACCAAGGCGCAATATTGCCGAACACAGCCGTGAAAGCAACCTGCCTTTTTGATGAGCTAGTTACAGTCACTGTGAATCCGCCGCGCCGAAAGCTGATTTATTCCGGTTACCTAGAATGGATGAATATACTCGAACATTATTATGAAACAGTATCTGGTCCTAAGTTGGCGTTGTATATTTATCTGCCCTGTCTCGTCACTGGATCAACTTCCTGTATCGTTAACTCTCCTTGATCTCTTATCAATATTGGGGCTCTAAAGCTACGTTTTCGAGTGGGAAACGCTGCGGCTCCTTATGTGAAGCGCAAAAGTCTTTTAACGATAAGTTGCATCACGACACACCCGGTGCAGAAAGAATCTTCCCCACCCTCCCGTGGTGAATGTAAACCTGGGGCCGGTTATCCCGGTGGTGAATACTTGAATATCCATCCTGGATTAGTGGTACGCACTCCTGGTAGCGCCCGTCCCTTATACTTACCGTGAGATTCTTCGTCGACCTCTGGCGTCGCCAATAAGTACAAATGCTTCAGTGCTTCTAACATTGACGATAACGGAAAACTTGTCGGAGAGGCGGGGTTACGGACACCGAACTTAACGCCTTACCATATGTTACAATTACGATCGGCCATCCCAATCTGCACACTCGATAAACGCCAAACGAGTGCAAACCCGAGTAGCATTAGCCTTCCCGCTAAACTGCCGCGAATCACCGCCGCCATCTGCCCCTTCCGGGAGCAATCTTCCTCATGAAATAAACCACCGCCGTCGAGTCTATGCACACTATGAGTCCTCTGGAAGTACCTGATGGGCTGCCGGGAAAATCCCCCCGCGTTGAGTGCGGATCAGCGTTGAAATCCGGCTCACGGCTCACTGGTGAGTATCTTCACATGAACATGGGGTCACGCTCGTGTAGACCTGGCGGACGTCGTGGACGAGCCACCTATAGTCAATGGGCTAGCAGAAACCATACCTCAATATTCAAACAACACGACGTACGGGGATAATCTACTGCCGACGAGTATGGCGTACGATGAACCTACCTGAATCGCCACGCTCATATTACTTACGGGGTGTTGAGTCCTCCTTTACTTGAGCACTAGCCCACACGAGTTGTTGTTAGTCGATTCCCTCGTTCTCAGTGACTTAGACTTGTCCACATGCCCTGAGAAGAGCAACGACGGTGAATACCCTTGCCGCTATATAAAGCCGCGGGAAAAAGACCTGGGCACCGTTAAACAGTCGTTTGCAATTTCTTTACGCCTATTAATGTCAAACCATTGGATGGCCCCGTCGCCGGAGGGGCCGAAAAGTTTGCGGTCTTATGGCCTCTTTACTCGGAACTGGAGTATTTATTCACCCTGACTTGCGCCTGTATATGGCTATTCCACATTCTTTAATATTCATTCGGTCGAGCTTCCGTTGCCCTCTAAGTCACCACTGTCCATCGTGTCCTCAACTAGCCTCTTATCCGTCTGTCTACGTACTACAACCCGTTCGGGGTGATACTATGATTGGATACTTTCACTGCTAGGCTGGCAGGATTCGTTCAACTATTTGTTCCAGGCCACGGCGACGTCCGACGTAAACGAGCTTTGTCGAAAATGAATCTTTTGGTCTTTACTACGATGCTACCCAACAGAAGATAAGAATGGGAACAATTGAAGTCCATTTGCCATTAATCCTCCGGCTAAAAAATCGGCGAGTCCCGTACCCCCCTCATTTGTAGACTGAGACGAGGTTGTCACCATTCCACCTGATGGCATCTACTCCCAAGCCTCATTTGGGGAGGCTCTGGGACTTAATAGCGCGCCTAACCGAATTCGCAACGCTATTCCCAATAAGGCGGAGCGAACACCTACCTCGATAGGATCCATTAGCTGTGTAGATGACCACATGGCGGAGATTACGGGACAACAGAGCCCCTTAAATCGGTATGAAGTAGCAGGTTGATACCCTGCTGAAACTTGAATCTATGTAAAGGACAAGGTTAATGCTTACATCTGTTTGGCTCACCTGTTCCATAGTCATCCTTCGGTATCTTATCTCAGCGGGCCTAACACATACCGTCTCATCCGGTCAATAAATTCGCGGTCAGAAATTCTATGGCCCGCTTATATCCCCCCGGTCGGTTGCCACCGCAGCATGATTCAAGGATCACTTCCCGATCAACACGCACATCTGCGTACGTGCTGTCAACTACTAAGTAGTGCTGCACGCGACCTGGTTTTGAGTGGCCTAGGGTTTCCGGTTAACTGATATTTACACACATGCAGTCATTCTTGGATCCCCACGCGAAAGAATCAGAGTATGTGGGATCTAGGTACGGTGTCGGGTCGACTACAAGTGGGCCTAGGGTGCTCATCAGGCCGGGGTATGGGTTCCTACAAAGGGCAGGAGGGCATGAACGCATTTTCACGTGAGGGTGTGCGCCGACAGGGAAATCCGCGAGATCATGCGCGTGAAGTTCACCGGAACGCGACACGATCAATCCACTGTAGCGAACGTGTGACGGGTACTCACGAACTCGGTTGCCCCGCGTACATCCCTATACTCCGGCCCCATGATTTGAAACATGGCAATCCACACCGCTGCGATTACGAAGGACCCCTTAGTCCTCGTGCAACCCTGAGCGACGTGCGCTGAGTAAGCTGCCGCAGCTATGAATTAATATCTGATGTGGGACCCGCGGGAGTGTTTGAGCGATCGACCACGTATATTGTGTCACTGGCCACCGGGAACCTCTGTCCACGACTTGAAAACATTCGGGTTGGGCGCCGAACTCTAGTTGCCATGGATATGTCGCGGGTTATATTAAAACGCGACACAGCTAACGGGTGCCTCACACGCGCTGCTATGACTGACTTGAGCTCTTGACAACAAGGAATCGTATTCCGGTCATCTTTCTTGACAGAGCGACACAACGACTGCTTCCTCGGTGACACCCGGCTTGAGTGGCAGGAGGTCGTCGCACTACCTGCTCATTTTTCCGCTAAAAACAATGTACCGCTGACACACTACGCTAGTCAACAGTGCTATTATTTACAGCCCTGCTTGGGGACCGATATAATTGCTGTCAGTTTCACCGATCCAAAGGGGCGTCCAGCACCGGGAACTACGAGCCTCCCAGACGACCGTCGGGCCCGCTCTGGCACTAAGTTCGATGAGGATGCCAATTCCGCCAAACCGGACGACCGCATACCCAAGGATCGTTCTTTACCTAAGCTAACCTCACTGGGGTTCTGCGTGACTCAATCACCATATGTTTTTTTTGTTGAAGTGTCAGAACATTCCTGGTGCTTGATGTCTTACCATTTGTGACCCTCGTGTTCTTTGTATAACATGGGCACGTTAGCAATTATGCTTCCCGAACGACCTCTAGCCGGAAAGCTCGCTCGACCCGGAATTAAATGTCCGGCGGTCCGGGAAATCAAGTTTCGTCCAATCGGTTGCGGGATCTTTGTAAAGGTCCCCTTCTCTCGATGTGCGCGTGGTCAATTCTCGGGGAACTTCGTCGGGTCCCGATGGCCGTTCGGATATTCGGCCCGAGGCGACATCGCGCGTAAATGATATGAGTTGGACCCGTCGGACGGCACGTCGCGCTTCCCAGTGTGACTGCACTTTGTCATAAGCAGTGGCTCTCACCCGGGAAAGTGTTTGGACCCGCAACAGCAGTTTGAAGTACACTTCGCCGGGACGTTTTCTTTATTCGTGGTTACCACAGCGAGCTACTGAGACTGGGGGCCTCAATGCAATCTATGTATCAGTGAATGTTGTGGCCAAGAGCTCTCCTTATGTCGTGATAACGTTATTTATTTCACGGAAACACAAGACATGTGGCTGTGTGCTGGATTACAGGGGGCTGCTCGCCTCATAACACTTTGAGAGCAGTCTGTAGCCGAGAGCAGTACAGTTCCCTGATATCGGTGAATTGTCCGATGTCCCTATAAACCAGACGGATTTTTGGGGTTTGCAGACCACGGTCCATACATACTATATTATCGCATTTCCGGGGGCGCCAGCGATACTAACTCGGAACATCGTGGAGGGGAACTCATGTCAGAGCGAGGCGTTAACGAAGACTATTCATCGATATTCGATATGAGTTCGTGTGGGAACGACCAGCGCAAGATGCGCAATCCGGGATCCTGATGGTACTATGAAGTCATACCTCGTGCAGGTGTCCGTCTTTTGCGTATCTGGTGCAGCGTAGGGCTATGTTATCCCTCGGGACATAATAGTATCCCAGCTAGTAGTGACATCTTTAGCCCCGGGACTGTGCAATTATCATGAACTCAAGTTCTACTCTCTCACTCTCCAAAGACCAATTGGGTAAAATTTATTTCCCGCCTGTCAGACTTGTTGGCTCAAAGCTTCTGCATAAAGGCAAGCAGCGCATCATGAAATGGCGGCCTATGGGCGGACAAGGCGGTTACTGCCATCTATCGTATGTTTAGCGCTGACCTGTCGCGAGGCATTGCTGGATTAACTTTAACAGGAAATCGAACCATAAATCGGTTGGATCTTTCGTTGATCCACAGCTTCGGGGCCACTTCCATGTACTGCGACTCACGTTTTATGTGATTTCCTGCTTACGTGGTATATGGCGCCGTCCGGCGATGAACTAACTACGAGACTAGCGGTTGAACATTCCACTACGCTTCGGTAGCCATTACTTGTGCTAATACCTTTGTCGGATCTCAAGGTATACTCGGTTTCTCCAATATATCATTGCTGCCGCTCGACCGGCCCGTGGCGTCCCCACCCCTATACCGGATGTATGAGCGTTCTGGGAGTAAAGCGCGCCACACACCGAGCCCATTCGACGCGCAAAATGACGGACGTCATCATCGGTCACTTACCTTCGAGTTGTTTTCGGGAGTTGGCTTATTAACTTGATTCAGTGGGTTACAGCGGGAACTAGACCAGCACGCCACTGACCTATTCATAATAGCTGTGGAACCGATGATCATACTGTTGTTTGCTTATATGGTAGAATTTCTGTCCAGTGGGCTGAATCTAAGCATTGCGCGATTTGCTGAAGAGCCCACCCGGTCTTGAATTATGCTACCCGCCTCCTGCGAGGATGATCTATGAATGCGATCGCGTAGCTCAGAATTTTGATCCCACGAAATATTGCTGTTAGATGCAAGCTCTGGCGCTTATGTGTATAAAGCTTGAACCTCCCGAGGCGCTGTGTCAAGTACGAGTTTCGGCCGCATTTGGGTGCCCACTACCTTATTGGGAATACTTCCGTGAAGTAGCGTCAATCATCAGTCACGGACCTCGCCCCCCTTTGTACTTGCGTCAATGGGACTGACCGCAATGCAAGATTGATCACTCGCCTATGGGCAATGGCACATAGAGCACTGGTTTCTAATTTCGAACCGGGTCCGGCGTTGCGACTCGAGTCCGGAGCCTGGCTGTGTATTTCGACCCGTCGTCGGGGGGTGCCCTATGTCTGCCTGTTTGGAACATTCCGATCTTAAGAGTCGCTTAATCCCTGCTGATAACAGCTCACGGGGCGGTCGTCAGTCGTATGCGACCCTCCACAACACTGGAAACTTGTGAGCAACCCGTCATACCGTTGTTGGTCGGACTATCCGCTGCAATGCCCTCTCTCAGCTATTTTGTCGCGCGTTTAACAATTATGTGATGACTGAGAGCTCCCGTCCAAAGCATTCGGATGCAAAACTGTCAAAGGGCGGCTTGATGTCCTTAAAAATCATCGAAGTTATGCGCTCCATAGCCAGTTCAGACCCCTACGCCGGGAGCATTACTCTTTTGTTTAAACAGAACACCACCCGAGCACTGATAGTGTACATACTGGAAGAACTAAACTTTGTAGGGCAATCTCGACATGGGTCAGATCCGGCCGATCTTATTTTCTTCTGCTCGCCGTGACTCGGTCAGCAACGCAATAAGCATATTACCCCACACTTGACGGTTGTGGGATGTCGCGAATATCTCATTTACGACCTAACCTCAAACCCAGAAGTTGCTGGAATCCGATTAAACAACACCGAATCTTCAACCTGTTCTTTTTCTTCCGGCCATCACAGCGCTGGTGTTTTGACGAGCAGTTCCGGCAATCTCCCAGGCAGTGGCCATTGCGACTTGCATGGCAAAAGCGAAATGGTAGTTGCAGTAAGCCACGGGAAACTGCAGACCTGGCGAGTTGGAGTGGCGCGAGCCGTAGGTTACACCATCCCTAAGTGGACCACAATCGGGGTGCATTCACAAATCCACAAGTTCAATCGGGGTGGGATAGCATGGGATCGAAAACATCAAGGGCAAGCATTCCACTTGCTCCTAGGACTTGTTTGGTACGGGGCACTAGTACATCGCCTAAAGGACGGCACCTACGTTCATGCTAATATTGGACAACGTCTCTGCCTGGGCAATCGGACGGAGACGTTAGTTCGACCCGACAACTCCATTGGCCTCTGACCCTTTGCAATAAATATGAGCTCGGGCTCGATGTATCGGTTTTTAGAAGCCCGAGCAGCATACCATCATGATTGCTTGGGTCGCTCATTGTGTTCCATCGCCGAGCCGTGACACGTTTGCGCGGCGTCTCTTGATATGATCGCAACAACCCAAAAAACGTCGTCGAATCGGCGGGCCTGTCCGTTCACGGAGTGCTCCGGACAAGATGCTCAATTACATGTTGCTCTATTCCCATTGCTCGCCCAACCGCACTCTTGAATCAGTTATCGCTTCTGTGGGGTTCACTGGGTGTTGTATAACTCCAACCACTTCCCCACTCCCTTTATCCGTGAACAAAAAACGACGAAAAATAAAGTCAACGTAACCTTGTATTCGTGGCAGGGGTCCGTTGTCGGAGCGATACCATGGTCTGTTATCCACTTTTTCTACTTACGCGCAGCACGTTTAGCTGTTGAAACCTGGGGAACCGGAAAGTTAGCTTTTATGTATCCATTGCATTACGTGCTCTGGGATAATACACAAGCCATTTTGTACCGGCCGAAATCTTTAGCACCTACGTCAATCATGCCCAACCACTGCTTCGCTCTGACTGGAGCTATAATTGAACTCTTCTTGATATGATATACAGCACTACGTCAATCAGCTAATATAGCCCTTGCTGTACATCGCCAGTTATGACCGCGGAAAACTGCTGAGCCGAAAGCGACCCACCAGAAGGGGGCCACGGATGAACATACTTGGGAGCTTTGCCCTCCCGGTCGTCCGATCCGACTAGAAGGCTGGCTAAGCGTGCTCCGGAAGCAAAAAGGCCAGCGGGCGATAGCAATGACCCGGTGGCCGGAGTGGGATTCACGTGTTACACGTTTAAGTCGAGTTCTTGGGTTCTGTGGACGCTTGAAGAACCTACGATGCTTCCGTTTATTTCATCGTAGTCTCCCCAACTGGCGATTGCGACATCAGAGTCAGGATCGTTTGGTACTATTGTGGGGAGACATGTATCACCTGTATGACCGTTACTGAGGTGGTCACCAAATTTTTTGGGATTCGAACCATGCAGTACTCTACTCGGATGGGCCACCGACGTGTGTATCATTTTCGACTGAGAATGCATCTTCGATGCCACGGGATTCCCCGACATCCACAACCCGCCTCATTTGGTCTAGTAGCCTTTCCTGGTGTCCTACACCGTCGCAGGGGGTCGATGGCACGCCCGATAACGGGTGGCGATCGTCAGCGCCTCAAACTTTACGTGTGTCGAAGCACCTTTGATCGGACGTGCACTGACCTGCGGGCGGTAATTCTCGCGACTTTTCCGGAGGGGCAGATGGCATGGGAGTCGAACGCCAGGGATCGGGTTCTGTGTACGTCGTCCTGGCCCCACGTAACTATCTTCGTCCCATTCTGCGGACCGGCCGGATTTCGTGCACCGCGCAGGCGCGGATACTGAAAGTGGTTAGTGAGATTTGAATGGCATTCACGTTTTCGATCTATGGGTTCGCGAGCTTATATGCACTAAACGAAATCGAGACAGCAAAGCCATTTAAGCGAAAGGATGCGTGGTGGCTTTATGCCGGAGTTAACTCCCTCCGGTGGGAACAAATAACCGTTCTCCCGCTGCAGAATTGCCTGCTTCTTGTGTGGGAGTATCCCTTCGTACCCGAAGCGGGCGTCGGTGACGTAGGCTCTATTCCGATCTACATAGCCGAGTGTTGCCCCCACTACATACAGGTAAACATCATAGCCGGGGCAAACGGAACGGCCCTTACATTCCCGCTCCTCTCTAGCGGTGTGCGCACAGCTACCGGGCGAATTCATCGAAAGTCGTATAGCCTACTTCCCCAACAAGTTATCCTCTTGTATTGAAATCACGCACTCGCACTGGCCACGTGGTGAACTGGTGCTCGTCAGTGCACCGCCGCGGAATTCCGCGTCCCTATGACACGGTTGCGGGTATTAAGCTGGGTTCAGACTCCTGCCGCTGGAGTTCTTAAGCTGCACGTACAAGCCTCATGTCAACCGCATCACGAGTCTGCCAACCGGCTCCTCCCGGGGGTAGTTCCGCCTGTTCGTGCCCAGCTACTATTCGTTGCACGAGACCGTCCTTCTCTGGGTGCCGCCCCCATAGCATTAAGTACAGAGTTAATCCCGGTCGACCTTATAACGAAATGAGAACCACTTCTAATGGATGAGGGCGCTAGCCGACATGTTACTCACGGCAACCTTCCTGACATATATACAGGTTGGGGAGAGACGTGGCGTTTGCCAACGCAGGGGTTTGAGCTCGAGAGCCAGCACTTCGTTTGATTCGTTGAACTCTCAGCACCGGCTCGTACACGGAAAGCTCATCGAAGCTGCGCTACCAAAGGTTTTCGTGGGCCGCCCACCGGCCCATCATTGCTCTACCCTATGCTCAAACCTCGCCAGGTGGAGGTGCCCTCCAGCGATACGGTTACAGTTGTACGATCGCAAATTTCCTTATCAGGGGGCCAGGTCACCGCGATTCTACGTGTACCACGGAAGCGTTTACCTTGCTTTAATTCGGCTGTGGCTTCATGATGTGGTAATTTTGCCCTCCGCCGTGGTCATTGTTTTACCTCAGGACGGTACAAGAACAAGCGACCAGCCCTGTCCACTGTCTGGGGTTCGAAAATTTCTCCTGTTATCTACAATAATAAACAATTGACGTGAACGCGCCAATTGAACTGTGAATGTATAAAATTAGTCCACGGGACAAATCCGCAAAGCCTCCATGTACGTGCCGTCGCCGAGAACCGACGAATTGCCAATGGCGCCCCGCCAACACTAGTGTTGTCACATCCGCGCTTTATAGATGGCTCCTACCTACACTATTGGCACTCCCGATCGCAGCATGTCTCAAAGTTCGCGTCTCATCTGGCACAATATCCCGTTAATTCTTGTCAGTGTTTGCATGGTGCACGATTCCTATTGATCAACAACGCCGTACGCAATTATAGTGTATATACTGCCGGTATAAATTTACCGAACTCCTGTACTATATACTTGACCCAAGGGGGCACGTATCCCATCACCCGACCTGCGGTCAATGTTACGCTTAAATGCGCTGAGACTGTGGTGGAGAATTTCCCATATCTTGGACACCGAGTCCCTCGTGACAAGCCAACCTGTTACCTATGGGGAGTCCGCCTTCGGGGCGCGGCGATTTAG"
prot = "MQTKHEQFRAQSATAGSSSHWTTSTTFGTESLADKRGLDIPTSRFAVTPVSANGHDGFEIAHSDAPRHQGAMLPNTAVKATCLFDELVTVTVNPPRRKLIYSGYLEWMNMLEHYYETVSGPKLALYIYLPCLVTGSTSCIVNSPWSLINIGALKLRFRVGNAAAPYVKRKSLLTMSCITTHPVQKESSPPSRGECKPGAGYPGGEYLNIHPGLVVRTPGSARPLYLPWDSSSTSGVANKYKCFSASNIDDNGKLVGEAGLRTPNLTPYHMLQLRSAIPICTLDKRQTSANPSSISLPAKLPRITAAICPFREQSSSWNKPPPSSLCTLWVLWKYLMGCRENPPALSADQRWNPAHGSLVSIFTWTWGHARVDLADVVDEPPMVNGLAETMPQYSNNTTYGDNLLPTSMAYDEPTWIATLMLLTGCWVLLYLSTSPHELLLVDSLVLSDLDLSTCPEKSNDGEYPCRYMKPREKDLGTVKQSFAISLRLLMSNHWMAPSPEGPKSLRSYGLFTRNWSIYSPWLAPVYGYSTFFNIHSVELPLPSKSPLSIVSSTSLLSVCLRTTTRSGWYYDWMLSLLGWQDSFNYLFQATATSDVNELCRKWIFWSLLRCYPTEDKNGNNWSPFAINPPAKKSASPVPPSFVDWDEVVTIPPDGIYSQASFGEALGLNSAPNRIRNAIPNKAERTPTSMGSISCVDDHMAEITGQQSPLNRYEVAGWYPAETWIYVKDKVNAYICLAHLFHSHPSVSYLSGPNTYRLIRSMNSRSEILWPAYIPPVGCHRSMIQGSLPDQHAHLRTCCQLLSSAARDLVLSGLGFPVNWYLHTCSHSWIPTRKNQSMWDLGTVSGRLQVGLGCSSGRGMGSYKGQEGMNAFSREGVRRQGNPRDHAREVHRNATRSIHCSERVTGTHELGCPAYIPMLRPHDLKHGNPHRCDYEGPLSPRATLSDVRWVSCRSYELMSDVGPAGVFERSTTYIVSLATGNLCPRLENIRVGRRTLVAMDMSRVMLKRDTANGCLTRAAMTDLSSWQQGIVFRSSFLTERHNDCFLGDTRLEWQEVVALPAHFSAKNNVPLTHYASQQCYYLQPCLGTDMIAVSFTDPKGRPAPGTTSLPDDRRARSGTKFDEDANSAKPDDRMPKDRSLPKLTSLGFCVTQSPYVFFVEVSEHSWCLMSYHLWPSCSLYNMGTLAIMLPERPLAGKLARPGIKCPAVREIKFRPIGCGIFVKVPFSRCARGQFSGNFVGSRWPFGYSARGDIARKWYELDPSDGTSRFPVWLHFVMSSGSHPGKCLDPQQQFEVHFAGTFSLFVVTTASYWDWGPQCNLCISECCGQELSLCRDNVIYFTETQDMWLCAGLQGAARLMTLWEQSVAESSTVPWYRWIVRCPYKPDGFLGFADHGPYMLYYRISGGASDTNSEHRGGELMSERGVNEDYSSMFDMSSCGNDQRKMRNPGSWWYYEVMPRAGVRLLRIWCSVGLCYPSGHNSIPASSDIFSPGTVQLSWTQVLLSHSPKTNWVKFISRLSDLLAQSFCMKASSASWNGGLWADKAVTAIYRMFSADLSRGIAGLTLTGNRTMNRLDLSLIHSFGATSMYCDSRFMWFPAYVVYGAVRRWTNYETSGWTFHYASVAITCANTFVGSQGMLGFSNMSLLPLDRPVASPPLYRMYERSGSKARHTPSPFDAQNDGRHHRSLTFELFSGVGLLTWFSGLQRELDQHATDLFMMAVEPMIMLLFAYMVEFLSSGLNLSIARFAEEPTRSWIMLPASCEDDLWMRSRSSEFWSHEMLLLDASSGAYVYKAWTSRGAVSSTSFGRIWVPTTLLGMLPWSSVNHQSRTSPPFVLASMGLTAMQDWSLAYGQWHMEHWFLISNRVRRCDSSPEPGCVFRPVVGGCPMSACLEHSDLKSRLIPADNSSRGGRQSYATLHNTGNLWATRHTVVGRTIRCNALSQLFCRAFNNYVMTESSRPKHSDAKLSKGGLMSLKIIEVMRSMASSDPYAGSITLLFKQNTTRALMVYMLEELNFVGQSRHGSDPADLIFFCSPWLGQQRNKHITPHLTVVGCREYLIYDLTSNPEVAGIRLNNTESSTCSFSSGHHSAGVLTSSSGNLPGSGHCDLHGKSEMVVAVSHGKLQTWRVGVARAVGYTIPKWTTIGVHSQIHKFNRGGMAWDRKHQGQAFHLLLGLVWYGALVHRLKDGTYVHANIGQRLCLGNRTETLVRPDNSIGLWPFAMNMSSGSMYRFLEARAAYHHDCLGRSLCSIAEPWHVCAASLDMIATTQKTSSNRRACPFTECSGQDAQLHVALFPLLAQPHSWISYRFCGVHWVLYNSNHFPTPFIREQKTTKNKVNVTLYSWQGSVVGAMPWSVIHFFYLRAARLAVETWGTGKLAFMYPLHYVLWDNTQAILYRPKSLAPTSIMPNHCFALTGAMIELFLMWYTALRQSANMALAVHRQLWPRKTAEPKATHQKGATDEHTWELCPPGRPIRLEGWLSVLRKQKGQRAMAMTRWPEWDSRVTRLSRVLGFCGRLKNLRCFRLFHRSLPNWRLRHQSQDRLVLLWGDMYHLYDRYWGGHQIFWDSNHAVLYSDGPPTCVSFSTENASSMPRDSPTSTTRLIWSSSLSWCPTPSQGVDGTPDNGWRSSAPQTLRVSKHLWSDVHWPAGGNSRDFSGGADGMGVERQGSGSVYVVLAPRNYLRPILRTGRISCTAQARMLKVVSEIWMAFTFSIYGFASLYALNEIETAKPFKRKDAWWLYAGVNSLRWEQMTVLPLQNCLLLVWEYPFVPEAGVGDVGSIPIYMAECCPHYMQVNIMAGANGTALTFPLLSSGVRTATGRIHRKSYSLLPQQVILLYWNHALALATWWTGARQCTAAEFRVPMTRLRVLSWVQTPAAGVLKLHVQASCQPHHESANRLLPGVVPPVRAQLLFVARDRPSLGAAPMALSTELIPVDLMTKWEPLLMDEGASRHVTHGNLPDMYTGWGETWRLPTQGFELESQHFVWFVELSAPARTRKAHRSCATKGFRGPPTGPSLLYPMLKPRQVEVPSSDTVTVVRSQISLSGGQVTAILRVPRKRLPCFNSAVASWCGNFALRRGHCFTSGRYKNKRPALSTVWGSKISPVIYNNKQLTWTRQLNCECMKLVHGTNPQSLHVRAVAENRRIANGAPPTLVLSHPRFMDGSYLHYWHSRSQHVSKFASHLAQYPVNSCQCLHGARFLLINNAVRNYSVYTAGMNLPNSCTMYLTQGGTYPITRPAVNVTLKCAETVVENFPYLGHRVPRDKPTCYLWGVRLRGAAI"
for i in xrange(1, 16):
if prot in translate(dna, table=i):
print i
break
#!/usr/bin/env python
from __future__ import print_function
import os
from Bio.Seq import translate
if __name__ == "__main__":
with open(os.path.join('data', 'rosalind_ptra.txt')) as dataset:
dna_string = dataset.readline().rstrip()
protein_string = dataset.readline().rstrip()
translation = translate(dna_string)
print(translation.find(protein_string) + 1)
"""
# manually taken list from CodonTable.py (Biopython source),
# the list at http://www.bioinformatics.org/JaMBW/2/3/TranslationTables.html
# is incomplete (Last update of the Genetic Codes: Sep 26, 1996)
valid_tables = [1,2,3,4,5,6,9,10,11,12,13,14,15,16,21,22,23]
"""
# ok, it is better to get the valid tables list programatically
# print(CodonTable.unambiguous_dna_by_id)
valid_tables = [k for k, v in CodonTable.unambiguous_dna_by_id.items()]
# a list of the codes possibly used for translating our dna to our protein
# (yet empty)
used_codes = []
# now we translate using all valid tables and check whether the resulting
# protein is the same as our given master protein
for t in valid_tables:
# 'stop_symbol=""' and 'to_stop=False' to IGNORE STOP CODONS
# 'cds=False' to ignore coding sequence checking (whether the sequence
# starts with START, whether the sequence length is a multiple of three...
protein = translate(dna, table=t, stop_symbol="", to_stop=False, cds=False)
if protein == master_protein:
used_codes.append(t)
# if we had found some possible codes for our protein, print the first one
# otherwise, print None
if used_codes:
print(used_codes[0])
else:
print(None)
def count_codons(haps):
import pickle
from Bio.Seq import translate
from operator import itemgetter
from pythonlib import Alignment
from pythonlib import mystats
latex = False # print latex table
count = [{} for i in range(102)]
oh = open('all.dat', 'w')
hap_freq = {}
degeneracy = {}
mask_mupos = [] #[10, 11, 22, 25, 32, 46, 58, 62, 67, 74, 89]
mupos = []
# These sequences are HXB2 proteases
wt_protease = 'PQVTLWQRPLVTIKIGGQLKEALLDTGADDTVLEEMSLPGRWKPKMIGGIGGFIKVRQYDQILIEICGHKAIGTVLVGPTPVNIIGRNLLTQIGCTLNF'
wt_protease_nt = 'CCTCAGGTCACTCTTTGGCAACGACCCCTCGTCACAATAAAGATAGGGGGGCAACTAAAGGAAGCTCTATTAGATACAGGAGCAGATGATACAGTA\
TTAGAAGAAATGAGTTTGCCAGGAAGATGGAAACCAAAAATGATAGGGGGAATTGGAGGTTTTATCAAAGTAAGACAGTATGATCAGATACTCATAGAAATCTGTGGACATAAAGCTA\
TAGGTACAGTATTAGTAGGACCTACACCTGTCAACATAATTGGAAGAAATCTGTTGACTCAGATTGGTTGCACTTTAAATTTT'
ac_res = map(align_codons, haps)
protease = wt_protease
for ar in ac_res:
start, residues, freq = ar # start here is human (from 1)
start -= 1 # start here is pythonic (from 0)
if start == None and residues == None: continue
oh.write('%d %s\n' % (round(freq), wt_protease_nt[:start] + residues +
wt_protease_nt[len(residues) + start:]))
if start % 3 == 0:
read = residues
elif start % 3 == 1:
read = residues[2:]
elif start % 3 == 2:
read = residues[1:]
try:
aa = translate(read) # Biopython
except:
print 'error: read', read
continue
if start % 3 == 0:
start_a = start / 3 + 1
if start % 3:
start_a = start / 3 + 2
stop_a = len(aa) + start_a + 1
this_hap = str(protease[:start_a - 1] + aa + protease[stop_a - 2:])
print this_hap.ljust(100), str(freq).ljust(
8
) # this is used for resistance prediction, whole haplotype and reads
for i, c in enumerate(this_hap):
count[i + 1][c] = count[i + 1].get(c, 0) + freq
Alignment.needle_align('asis:%s' % wt_protease, 'asis:%s ' % this_hap,
'tmp', 10.0, 0.5)
d = Alignment.alignfile2dict(['tmp'], 'n', 10.0, 0.5,
Verbose=False)['asis']['asis']
os.remove('tmp')
mutations = []
for i, c in enumerate(zip(d.seq_a, d.seq_b)):
pos = i + 1
if '-' in c:
continue
if c[0] != c[1]:
mutations.append(c[0] + str(pos) + c[1])
if pos not in mask_mupos: mupos.append(pos)
signature = ', '.join(mutations)
hap_freq[signature] = hap_freq.get(signature, 0.0) + freq
degeneracy[signature] = degeneracy.get(signature, 0) + 1
print ''
for k, v in hap_freq.items():
print str(v).ljust(15), ' ', k
mupos = sorted(mupos)
spos = {}
for i, j in enumerate(mupos):
spos[j] = i
hf_sorted = sorted(hap_freq.items(), key=itemgetter(1), reverse=True)
tot_reads = sum([h[1] for h in haps])
tot_hap = sum(hap_freq.values())
print 'Tot reads after', tot_reads
print 'Tot', tot_hap
print 'Simpson\'s index on amino acid sequences = %f +/- %f' % mystats.Simpson(
hap_freq.values())
oh = open('degeneracy.pck', 'w')
pickle.dump(degeneracy, oh)
oh.close()
for c in count:
ts = sum(c.values())
for k in c.keys():
c[k] /= ts
plot_variation(count)
if not latex:
return hf_sorted
print ''
print '|c' * (1 + len(spos))
for i in mupos:
print '%s%d & ' % (wt_protease[i - 1], i),
print ''
return hf_sorted
from Bio.Seq import translate
def read_strings(fname):
""" read dataset and append distinct strings """
f = open(fname,'r')
return f.readlines()
if __name__ == '__main__':
dataset = read_strings('ptra.txt')
coding_dna = dataset[0].replace('\n','')
result_protein = dataset[1].replace('\n','')
protein = translate(coding_dna)
print protein.find(result_protein) % 3 +1
print result_protein
print protein
from Bio.Seq import translate
with open("rosalind_ptra.txt", "r") as f:
seq = f.readline().replace("\n", "")
res = f.readline().replace("\n", "")
for i in range(1, 16):
if translate(seq, table=i) == res + "*":
print(i)
break
#!/usr/bin/env python
'''
A solution to a ROSALIND bioinformatics problem from the Armory problem area,
which focuses on using prebuilt bioinformatics packages, in this case BioPython.
Problem Title: Finding Genes with ORFs
Rosalind Armory ID: ORFR
Rosalind Armory #: 015
URL: http://rosalind.info/problems/orfr/
'''
from Bio.Alphabet import IUPAC
from Bio.Seq import Seq, translate
from re import finditer
with open('data/armory/rosalind_orfr.txt') as input_data:
dna = Seq(input_data.read().strip(),IUPAC.unambiguous_dna)
# Get the starting position for each ORF in the dna sequence and translate.
ORFs = [translate(dna[x.start():], table = 1, stop_symbol = '', to_stop= True) for x in finditer('ATG', str(dna))]
# Get the starting position for each ORF in the reverse complement sequence and translate.
ORFs += [translate(dna.reverse_complement()[x.start():], table = 1, stop_symbol = '', to_stop= True) for x in finditer('ATG', str(dna.reverse_complement()))]
# Find the longest ORF.
longest_orf = max(map(str, ORFs), key=len)
# Print and save the answer.
print longest_orf
with open('output/armory/Armory_015_ORFR.txt', 'w') as output_data:
output_data.write(longest_orf)
def frame1(self, seq, translation_table=1):
"""Translate first reading frame."""
return translate(seq, table=translation_table)
codonStatus = list()
codonStatusMN = list()
codonStatusMS = list()
snpStatus = list()
nsList = list()
majorCount = list()
snpPosition = list()
for i in range(0, aln.get_alignment_length(), 3):
if i % 1000 == 0:
print >> sys.stderr, i
codons = aln[:, i:i + 3]
codonSet = list(set([str(codon.seq) for codon in codons]))
codonList.append(codonSet)
aaList.append([translate(codon) for codon in codonSet])
codonCount.append(len(codonSet))
nsList.append(np.array([NSDict[str(codon.seq)] for codon in codons]))
#Conserved codons
if len(codonSet) == 1:
codonStatus.append("C")
snpStatus.extend("CCC")
#Multiple codons have NS status determined by all pairs within a single mutation of each other
if len(codonSet) > 2:
#For each codon in the set, calculate the distance to each other codon and determine NS status if 1 snp
changeSet = list()
for j in range(0, len(codonSet)):
aa = translate(codonSet[j])
for k in range(j, len(codonSet)):
def which_table(inp, out):
for i in range(1, 7) + range(9, 17) + range(21, 24):
trans = translate(inp, table=i, to_stop=True)
#if len(trans) == len(out):
if out == trans:
print 'Match: {0:d}'.format(i)
def codonChange(codon):
aa = translate(codon)
ncs = nearCodons(codon)
aas = [translate(nc) for nc in ncs]
ns = [("N", "S")[int(naa == aa)] for naa in aas]
return (ns)
def six_frame_translations(seq, genetic_code=1):
"""Formatted string showing the 6 frame translations and GC content.
nice looking 6 frame translation with GC content - code from xbbtools
similar to DNA Striders six-frame translation
>>> from Bio.SeqUtils import six_frame_translations
>>> print(six_frame_translations("AUGGCCAUUGUAAUGGGCCGCUGA"))
GC_Frame: a:5 t:0 g:8 c:5
Sequence: auggccauug ... gggccgcuga, 24 nt, 54.17 %GC
<BLANKLINE>
<BLANKLINE>
1/1
G H C N G P L
W P L * W A A
M A I V M G R *
auggccauuguaaugggccgcuga 54 %
uaccgguaacauuacccggcgacu
A M T I P R Q
H G N Y H A A S
P W Q L P G S
<BLANKLINE>
<BLANKLINE>
"""
from Bio.Seq import reverse_complement, translate
anti = reverse_complement(seq)
comp = anti[::-1]
length = len(seq)
frames = {}
for i in range(0, 3):
fragment_length = 3 * ((length - i) // 3)
frames[i + 1] = translate(seq[i:i + fragment_length], genetic_code)
frames[-(i + 1)] = translate(anti[i:i + fragment_length],
genetic_code)[::-1]
# create header
if length > 20:
short = '%s ... %s' % (seq[:10], seq[-10:])
else:
short = seq
header = 'GC_Frame: '
for nt in ['a', 't', 'g', 'c']:
header += '%s:%d ' % (nt, seq.count(nt.upper()))
header += '\nSequence: %s, %d nt, %0.2f %%GC\n\n\n' % (short.lower(),
length, GC(seq))
res = header
for i in range(0, length, 60):
subseq = seq[i:i + 60]
csubseq = comp[i:i + 60]
p = i // 3
res += '%d/%d\n' % (i + 1, i / 3 + 1)
res += ' ' + ' '.join(frames[3][p:p + 20]) + '\n'
res += ' ' + ' '.join(frames[2][p:p + 20]) + '\n'
res += ' '.join(frames[1][p:p + 20]) + '\n'
# seq
res += subseq.lower() + '%5d %%\n' % int(GC(subseq))
res += csubseq.lower() + '\n'
# - frames
res += ' '.join(frames[-2][p:p + 20]) + ' \n'
res += ' ' + ' '.join(frames[-1][p:p + 20]) + '\n'
res += ' ' + ' '.join(frames[-3][p:p + 20]) + '\n\n'
return res
def frame(self, seq, frame, translation_table=1):
"""Translate DNA sequence in a chosen frame."""
if frame < 0:
seq = reverse_complement(seq)
seq = seq[(abs(frame) - 1) :]
return translate(seq, table=translation_table)
def frame1(self, seq, translation_table=1):
return translate(seq, table=translation_table)
