def make_mutation(csv_file,save_folder,tru):
from Bio.Seq import Seq
from Bio.Alphabet import IUPAC
import re
import csv
import os
'Import CSV list of mutations with wt sequence as header'
mutations_list = csv.reader(open(csv_file,'rU'), delimiter=";")
mutations = []
for row in mutations_list:
mutations.append(row[0])
'split into sequence and mutations'
prot_seq = mutations[0].lower()
mutations.pop(0)
'Creates a folder for data-output'
directory = save_folder
if not os.path.exists(directory):
os.makedirs(directory)
'Makes a table with all mutations with their matching sequence'
table_of_mutations = [("aaawildtype",str(Seq(prot_seq)[int(tru):]))]
i = 0
for i in range(len(mutations)):
my_seq_un = Seq(prot_seq)
my_seq = my_seq_un.tomutable()
if mutations == 'false':
pass
else:
match = re.match(r"([a-z]+)([0-9]+)([a-z]+)", mutations[i], re.I)
if match:
position_id = match.groups()
position = position_id[1]
my_seq[int(position)-1] = position_id[2]
if mutations[i]:
table_of_mutations.append((mutations[i],my_seq[int(tru):]))
'save as single files, used for Scwrl'
with open(os.path.join(directory, str(mutations[i])), 'wb') as temp_file:
temp_file.write(str(my_seq[int(tru):]))
with open(os.path.join(directory, "aaawildtype"), 'wb') as temp_file:
temp_file.write(str(Seq(prot_seq)[int(tru):]))
'Saving the list as a file'
import csv
with open(os.path.join(directory,'sum_all_mutations.csv'),'w') as out:
csv_out = csv.writer(out)
csv_out.writerow(['Mutation','Sequence'])
for row in table_of_mutations:
csv_out.writerow(row)
def translate_using_sequence(self, contig):
"""
Translate the SNPs at this position and give the proportion.
:param contig: A Contig object with associated Gene(s)
:return:A line to stdout
"""
if type(contig).__name__ != "Contig":
Error.error("Genomic_environment: translate_using_sequence: The object passed is not of type Contig")
#For each gene in Contig... we search for the one that contain the position
gene = Gene.__init__()
for orf in contig.genes:
if orf.start <= self.position <= orf.end:
gene = orf
if gene.sequence == "":
Error.error("Genomic_environment: translate_using_sequence: There is no sequence in the selected gene")
orf_seq = Seq(gene.sequence, IUPAC.unambiguous_dna)
amino_acid_sequence = str(orf_seq.translate(table=11))
orf_seq = orf_seq.tomutable()
nucleotides_sequences = self.group_environment()
total = len(self.reads)
header = "Contig\tSNP position(contig)\tFrame\tAmino acid\tProportion\n"
#We put - in the frame number column.
print(header),
for entry in nucleotides_sequences:
mutation = entry[2]
mutated_seq = copy.copy(orf_seq)
mutated_seq[self.position-gene.start] = mutation
mutated_prot_seq = str(mutated_seq.translate(table=11))
changed_amino_acid_position = math.ceil(float(self.position-gene.start+1)/3)
changed_amino_acid = mutated_prot_seq[changed_amino_acid_position-1] #-1 cuz its a python string.
line = (self.contig+"\t"+self.position+"\t-\t"+changed_amino_acid+"\t" +
str(float(nucleotides_sequences[entry])/total))
print(line)
def evolution_of_a_genome(gen_size, number_of_generations, step):
t1 = time.time()
my_seq = Seq(genome_generation_v3(gen_size))
#print(my_seq)
y = []
print("J'ai fait le genome en %.4f secondes." % (time.time() - t1))
for i in range(number_of_generations): #number of generations
y.append(int(gen_size - i)) # size of genome - i
y = y[0:number_of_generations:step]
print("J'ai fait y")
my_seq1 = my_seq.tomutable()
hist_scor_align1 = []
old_seq = my_seq1
for i in range(number_of_generations):
new_seq = q3_muta_ponct(old_seq)
#print(new_seq)
if (i % step == 0):
hist_scor_align1.append(int(alignment_gen1(my_seq, new_seq)))
old_seq = new_seq
print("J'ai fait les alignements")
#if(np.absolute((hist_scor_align1[i/10]-y[i])/y[i]) > 0.05):
i = 0
#affiche l'évolution des paramètres
plt.plot(np.arange(0, number_of_generations, step),
hist_scor_align1,
label="score de pairwise2xx")
plt.plot(np.arange(0, number_of_generations, step),
y,
label="Nombre de bases identiques theorique")
plt.xlabel("Nombre de mutations")
plt.ylabel("Bases identiques")
plt.legend()
plt.show()
def test_padding_truncating():
from Bio.Seq import Seq
seq = Seq('ACTCGA')
norm_seq = padding_truncating(seq.tomutable(), segment_size=12)
assert str(norm_seq) == 'NNNACTCGANNN'
def RandomProbe(probe, MutateNum):
#Probe Seq
Probe = Seq("AGGCCACAACCTCCAAGTAG")
#convert probe string to mutable object
mutable_probe = Probe.tomutable()
global Pos
Pos = RandomPosition(probe, MutateNum)
#print(Pos)
for p in range(len(Pos)): #single position in mutaition positions
RB = mutable_probe[Pos[p]]
mutable_probe[Pos[p]] = RandomBase(RB)
return mutable_probe
def get_founction_Prokaryote(infile,outdir,outname,genomefile,anno_file):
result_file=open("%s/%s_result.txt"%(outdir,outname),"w")
result_file.write("Accession"+"\t"+"Position"+"\t"+"Old_base"+"\t"+"New_base"+"\t"+"Coverage"+"\t"+"Edit_level"+"\t"+"Gene_biotype"+"\t"+"Gene_name"+"\t"+"Product"+"\t"+"Amino acid_change"+"\n")
db = gffutils.create_db("%s"% anno_file, ':memory:', force=True, keep_order=True,merge_strategy='merge', id_spec="ID",sort_attribute_values=True)
with open('%s'% infile, 'r') as pileup:
data=pileup.readlines()
data=filter(None, data)
for line in data:
linsplit=line.split("\t")
accession=linsplit[0]
position=int(linsplit[1])
oldbase=linsplit[2]
newbase=linsplit[3]
for i in db.all_features(featuretype='gene'):
if position>=db[i.id].start and position<=db[i.id].end:
if db[i.id].seqid == accession and db[i.id].attributes['gene_biotype'][0]=="protein_coding":
change_loc=position-db[i.id].start
old_seq=Seq(i.sequence("%s"% genomefile, use_strand=False),IUPAC.unambiguous_dna)
new_seq = old_seq.tomutable()
new_seq[change_loc] = newbase
new_seq=new_seq.toseq()
CDS_id=[h.id for h in db.children(i.id,featuretype="CDS")][0]
product=db[CDS_id].attributes['product'][0]
if db[i.id].strand== "+":
old_pro=old_seq.translate()
new_pro=new_seq.translate()
for n in range(len(old_pro)):
if old_pro[n]==new_pro[n]:
pass
else:
result_file.write(str(accession)+"\t"+str(position)+"\t"+str(oldbase)+"\t"+str(newbase)+"\t"+str(linsplit[5])+"\t"+str(linsplit[4])+"\t"+"CDS"+"\t"+db[i.id].attributes['Name'][0]+"\t"+str(product)+"\t"+old_pro[n]+str(n+1)+new_pro[n]+"\n")
if db[i.id].strand== "-":
old_seq=old_seq.reverse_complement()
new_seq=new_seq.reverse_complement()
old_pro=old_seq.translate()
new_pro=new_seq.translate()
for n in range(len(old_pro)):
if old_pro[n]==new_pro[n]:
pass
else:
result_file.write(str(accession)+"\t"+str(position)+"\t"+str(oldbase)+"\t"+str(newbase)+"\t"+str(linsplit[5])+"\t"+str(linsplit[4])+"\t"+"CDS"+"\t"+db[i.id].attributes['Name'][0]+"\t"+str(product)+"\t"+old_pro[n]+str(n+1)+new_pro[n]+"\n")
if db[i.id].seqid == accession and db[i.id].attributes['gene_biotype'][0]!="protein_coding":
result_file.write(str(accession)+"\t"+str(position)+"\t"+str(oldbase)+"\t"+str(newbase)+"\t"+str(linsplit[5])+"\t"+str(linsplit[4])+"\t"+db[i.id].attributes['gene_biotype'][0]+"\t"+db[i.id].attributes['Name'][0]+"\t"+"-"+"\t"+"-"+"\n")
start=[db[i.id].start for i in db.all_features(featuretype='gene')]
end=[db[i.id].end for i in db.all_features(featuretype='gene')]
ranges=zip(start,end)
if any(lower <= position <= upper for (lower, upper) in ranges):
continue
else:
result_file.write(str(accession)+"\t"+str(position)+"\t"+str(oldbase)+"\t"+str(newbase)+"\t"+str(linsplit[5])+"\t"+str(linsplit[4])+"\t"+"Intergenic region"+"\t"+"-"+"\t"+"-"+"\t"+"-"+"\n")
result_file.close
def MutableGeneSeq():
my_seq = Seq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna)
#my_seq[5] = "G" #error 'Seq' object does not support item assignment
mutable_seq = my_seq.tomutable()
mutable_seq[1] = 'T'
print('mutable_seq = ', mutable_seq)
mutable_seq = MutableSeq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA",
IUPAC.unambiguous_dna)
mutable_seq[0] = 'T'
print('mutable_seq = ', mutable_seq)
new_seq = mutable_seq.toseq() #convert to readonly seq
def test_seq():
print(f'\n\n{Bio.__version__}')
myseq = Seq("GATCGAAATGGGCCTAAAAATATAGGATCGAAAATCGC",
IUPAC.unambiguous_dna)
print(myseq.alphabet)
print(myseq)
print(myseq.__len__())
# You can calculate the GC ratio yourself or you can you use a special function to do so
print(f'The number of G\'s is: {myseq.count("G")}')
print(f'The number of C\'s is: {myseq.count("C")}')
print(100 * (myseq.count("G") + myseq.count("C")) / myseq.__len__())
print(f'The ratio GC in the string is: {GC(myseq)}')
# Sequences can be inverted and complemented
print(f'The string is:\t\t\t\t {myseq}')
print(f'The reverse is:\t\t\t\t {myseq[::-1]}')
print(f'The complement is:\t\t\t {myseq.complement()}')
print(f'The reverse complement is:\t {myseq.reverse_complement()}')
# A simple function to determine if a string is palindromic
print(f'GAAG is palindrome: {ispalindromic("GAAG")}')
print(f'GAAG is palindrome: {ispalindromic("GTAG")}')
# Find all the sequences of AAA
# Start with the first AAA and that start looping
positions = []
pos = myseq.find('AAA')
while pos != -1:
positions.append(pos)
pos = myseq.find('AAA', pos + 1)
print(positions)
count = len(positions)
# A demo to show that Seq is not mutable.
# If you need to change a Seq, make it mutable first
try:
myseq[0] = 'C'
except:
print("Oops! As Seq is immutable ")
im_seq = myseq.tomutable()
im_seq[0] = 'C'
seq = im_seq
print(seq)
def createMutantAllChromsInOneFastaFile(mutant):
"""
to construct a fastaFile for a mutant from ref and snp file
chroms seq are concatened
"""
snps=createSNPsListFromMutant(mutant)
mutname=mutant.nom
seqemblout= Seq("", IUPAC.unambiguous_dna)
seqemblout.tomutable()
for chr in ["0A","0B","0C","0D","0E","0F","0G","0H"]:
emblFile=chooseRightEMBLFile(mutant.strain.emblrep,mutant.strain.specy,chr)
record=SeqIO.read(emblFile,"embl")
seqemblin=record.seq
seqembl=seqemblin.tomutable()
for snp in snps:
if chr==snp.chrom:
seqembl[snp.pos-1]=snp.seqmut
print chr
seqemblout=seqemblout+seqembl
rec = SeqRecord(seqemblout,
id=mutname,
description= "wholegenome %s of mutant %s from strain %s"%(chr,mutname,mutant.strain.specy))
print "fini!"
return rec
def translate_using_sequence(self, contig):
"""
Translate the SNPs at this position and give the proportion.
:param contig: A Contig object with associated Gene(s)
:return:A line to stdout
"""
if type(contig).__name__ != "Contig":
Error.error(
"Genomic_environment: translate_using_sequence: The object passed is not of type Contig"
)
#For each gene in Contig... we search for the one that contain the position
gene = Gene.__init__()
for orf in contig.genes:
if orf.start <= self.position <= orf.end:
gene = orf
if gene.sequence == "":
Error.error(
"Genomic_environment: translate_using_sequence: There is no sequence in the selected gene"
)
orf_seq = Seq(gene.sequence, IUPAC.unambiguous_dna)
amino_acid_sequence = str(orf_seq.translate(table=11))
orf_seq = orf_seq.tomutable()
nucleotides_sequences = self.group_environment()
total = len(self.reads)
header = "Contig\tSNP position(contig)\tFrame\tAmino acid\tProportion\n"
#We put - in the frame number column.
print(header),
for entry in nucleotides_sequences:
mutation = entry[2]
mutated_seq = copy.copy(orf_seq)
mutated_seq[self.position - gene.start] = mutation
mutated_prot_seq = str(mutated_seq.translate(table=11))
changed_amino_acid_position = math.ceil(
float(self.position - gene.start + 1) / 3)
changed_amino_acid = mutated_prot_seq[
changed_amino_acid_position - 1] #-1 cuz its a python string.
line = (self.contig + "\t" + self.position + "\t-\t" +
changed_amino_acid + "\t" +
str(float(nucleotides_sequences[entry]) / total))
print(line)
# 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
# 3.10 Mutable Seqs
# convert existing sequence to mutable
mutable_seq = my_seq.tomutable()
# or directly create a mutable one
from Bio.Seq import MutableSeq
from Bio.Alphabet import IUPAC
mutable_seq = MutableSeq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna)
# now we can do
mutable_seq[5] = "T"
# and convert it back to an inmutable seq
new_seq = mutable_seq.toseq()
def _constructSNPAnnotation(self, session, snp_info, snps_context_wrapper, gene_annotation, snp_annotation_short_name2id):
"""
2009-2-5
bug fixed. when adding a box as UTR, make sure after the forloop above, the current box is still the UTR.
2009-1-5
"""
sys.stderr.write("Constructing SNPAnnotation ...\n")
standard_translator = Translate.unambiguous_dna_by_id[1]
counter = 0
real_counter = 0
for i in range(len(snp_info.chr_pos_ls)):
counter += 1
snp_db_entry = snp_info.data_ls[i]
snps_id=snp_db_entry.id
chr=snp_db_entry.chromosome
pos = snp_db_entry.position
allele1 = snp_db_entry.allele1
allele2 = snp_db_entry.allele2
snps_context_matrix = snps_context_wrapper.returnGeneLs(chr, pos)
snp_annotation_type_short_name_ls = [] #each element is (snp_annotation_type_short_name, gene_id, gene_commentary_id,
# which_exon_or_intron, pos_within_codon)
if snps_context_matrix:
for snps_context in snps_context_matrix:
snps_id, disp_pos, gene_id = snps_context
gene_model = gene_annotation.gene_id2model.get(gene_id)
if gene_model is None:
continue
for gene_commentary in gene_model.gene_commentaries:
if gene_commentary.protein_box_ls:
which_intron = -1 #which intron the SNP resides, starting from 1
which_coding_exon = -1 #which exon the SNP resides in terms of the CDS sequence, starting from 1
accum_intron_len = 0 #the cumulative length of all introns from the one \
# after the first coding exon up till the SNP's position (including the intron the SNP is in if it's under the rule).
exon_5_end_pos = -1 #5' end position of the whole CDS sequence. bad name 'exon'
UTR_2nd = 0 #whether this is the 2nd UTR
box_type = None
UTR_type = None
is_SNP_within_box = 0 #protect against the possibility that SNP overshoots box_ls
for i in range(len(gene_commentary.box_ls)):
box = gene_commentary.box_ls[i]
start, stop, box_type, is_translated, protein_box_index = box
if box_type=='exon' and is_translated==0:
if UTR_2nd==0:
if gene_model.strand=='-1':
UTR_type='3UTR'
else:
UTR_type='5UTR'
UTR_2nd += 1
else:
if gene_model.strand=='-1':
UTR_type='5UTR'
else:
UTR_type='3UTR'
elif box_type=='exon' and is_translated==1:
if exon_5_end_pos==-1:
exon_5_end_pos=start
which_coding_exon += 1
elif box_type=='intron':
if which_coding_exon!=-1: #exclude introns that stand before the 1st coding exon
accum_intron_len += abs(stop-start)+1 #+1 because stop-start is intron_length-1
which_intron += 1
if pos>=start and pos<=stop: #with this box
is_SNP_within_box = 1
break
if gene_model.strand=='-1':
#continue to read the box_ls to count no_of_introns
no_of_introns = which_intron+1
for j in range(i+1, len(gene_commentary.box_ls)):
box = gene_commentary.box_ls[i]
if box[2]=='intron':
no_of_introns += 1
if box_type!=None and is_SNP_within_box==1: #box_type is the type of the box where the SNP resides
if UTR_type!=None and box_type=='exon' and is_translated==0: #it's UTR. bug fixed. make sure after the forloop above,
# the current box is still the UTR.
snp_annotation_type_short_name_ls.append((UTR_type, gene_id, gene_commentary.gene_commentary_id))
else:
if gene_model.strand=='-1': #reverse the order of exon/intron
no_of_coding_exons = len(gene_commentary.protein_box_ls)
#no_of_introns = len(gene_commentary.mrna_box_ls)-no_of_coding_exons #not right
which_coding_exon = no_of_coding_exons-which_coding_exon
which_intron = no_of_introns-which_intron
else:
which_coding_exon += 1
which_intron += 1
if box_type=='intron':
snp_annotation_type_short_name_ls.append(('intron', gene_id, gene_commentary.gene_commentary_id, which_intron))
if pos-start<=1: #within the donor/acceptor two-nucleotide
if gene_model.strand=='-1':
snp_annotation_type_short_name = 'splice-acceptor' #on the 3' of this intron
else:
snp_annotation_type_short_name = 'splice-donor' #on the 5' of this intron
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, \
gene_commentary.gene_commentary_id, which_intron))
elif stop-pos<=1:
if gene_model.strand=='-1':
snp_annotation_type_short_name = 'splice-donor' #on the 5' of this intron
else:
snp_annotation_type_short_name = 'splice-acceptor' #on the 3' of this intron
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, \
gene_commentary.gene_commentary_id, which_intron))
elif box_type=='exon': #must be translated
try:
SNP_index_in_CDS = pos - exon_5_end_pos - accum_intron_len
if gene_model.strand=='-1': #reverse
SNP_index_in_CDS = len(gene_commentary.cds_sequence)-SNP_index_in_CDS-1 #-1 because SNP_index_in_CDS starts from 0
gene_allele1 = nt2complement[allele1]
gene_allele2 = nt2complement[allele2]
else:
gene_allele1 = allele1
gene_allele2 = allele2
SNP_index_in_CDS = int(SNP_index_in_CDS)
# SNP_index_in_CDS is type long. without int(), cds_seq[SNP_index_in_CDS] returns a Bio.Seq with one nucleotide,
# rather than a single-char string
SNP_index_in_peptide = SNP_index_in_CDS/3
SNP_index_in_peptide = int(SNP_index_in_peptide) #ditto as int(SNP_index_in_CDS), not necessary
pos_within_codon = SNP_index_in_CDS%3+1 #pos_within_codon starts from 1
cds_seq = Seq(gene_commentary.cds_sequence, IUPAC.unambiguous_dna)
if SNP_index_in_CDS>=len(cds_seq):
sys.stderr.write("Warning: SNP (%s, %s), SNP_index_in_CDS=%s, is beyond any of the boxes from gene %s (chr=%s, %s-%s), \
gene_commentary_id %s (%s-%s), box_ls=%s, cds-length=%s. counted as intergenic.\n"%\
(chr, pos, SNP_index_in_CDS, gene_id, gene_model.chromosome, gene_model.start, gene_model.stop, \
gene_commentary.gene_commentary_id, gene_commentary.start, gene_commentary.stop, repr(gene_commentary.box_ls), \
len(cds_seq)))
snp_annotation_type_short_name_ls.append(['intergenic'])
continue
if cds_seq[SNP_index_in_CDS]!=gene_allele1 and cds_seq[SNP_index_in_CDS]!=gene_allele2:
sys.stderr.write("Error: Neither allele (%s, %s) from SNP (%s,%s) matches the nucleotide, %s, from the cds seq of gene %s \
(gene_commentary_id=%s).\n"%\
(gene_allele1, gene_allele2, chr, pos, cds_seq[SNP_index_in_CDS], gene_id, gene_commentary.gene_commentary_id))
sys.exit(3)
cds_mut_ar = cds_seq.tomutable()
cds_mut_ar[SNP_index_in_CDS] = gene_allele1
peptide = standard_translator.translate(cds_mut_ar.toseq())
alt_cds_mut_ar = cds_seq.tomutable()
alt_cds_mut_ar[SNP_index_in_CDS] = gene_allele2
alt_peptide = standard_translator.translate(alt_cds_mut_ar.toseq())
aa = peptide[SNP_index_in_peptide]
alt_aa = alt_peptide[SNP_index_in_peptide]
if aa != alt_aa:
snp_annotation_type_short_name = 'non-synonymous'
comment = '%s->%s'%(aa, alt_aa)
else:
snp_annotation_type_short_name = 'synonymous'
comment = None
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, \
which_coding_exon, pos_within_codon, comment))
if aa != alt_aa:
if aa=='*' or alt_aa=='*':
snp_annotation_type_short_name = 'premature-stop-codon' #could also be the last stop codon changing to something else
# and thereby extending the cds
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, \
which_coding_exon, pos_within_codon, comment))
if SNP_index_in_peptide==0:
snp_annotation_type_short_name = 'init-Met'
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, \
which_coding_exon, pos_within_codon, comment))
except:
traceback.print_exc()
sys.stderr.write('%s.\n'%repr(sys.exc_info()))
sys.stderr.write("Except encountered for SNP (%s, %s), gene %s (chr=%s, %s-%s), gene_commentary_id %s (%s-%s), box_ls=%s.\n"%\
(chr, pos, gene_id, gene_model.chromosome, gene_model.start, gene_model.stop, \
gene_commentary.gene_commentary_id, gene_commentary.start, gene_commentary.stop, repr(gene_commentary.box_ls)))
elif box_type!=None and is_SNP_within_box==0:
#SNP is over the range of the gene. it happens when one gene has multiple alternative splicing forms.
# snps_context_wrapper uses the largest span to represent the gene.
snp_annotation_type_short_name_ls.append(['intergenic'])
else:
sys.stderr.write("Warning: SNP (%s, %s) not in any of the boxes from gene %s (chr=%s, %s-%s), gene_commentary_id %s (%s-%s), box_ls=%s.\n"%\
(chr, pos, gene_id, gene_model.chromosome, gene_model.start, gene_model.stop, \
gene_commentary.gene_commentary_id, gene_commentary.start, gene_commentary.stop, repr(gene_commentary.box_ls)))
else:
if gene_model.type_of_gene=='pseudo':
snp_annotation_type_short_name = gene_model.type_of_gene
else:
snp_annotation_type_short_name = gene_commentary.gene_commentary_type
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, None))
else: #integenic
snp_annotation_type_short_name_ls.append(['intergenic'])
#now save everything into db
for snp_annotation_type_tup in snp_annotation_type_short_name_ls:
snp_annotation_type_short_name = snp_annotation_type_tup[0]
if snp_annotation_type_short_name not in snp_annotation_short_name2id:
ty = Stock_250kDB.SNPAnnotationType(short_name=snp_annotation_type_short_name)
session.add(ty)
session.flush()
snp_annotation_short_name2id[snp_annotation_type_short_name] = ty.id
if len(snp_annotation_type_tup)>=3:
gene_id = snp_annotation_type_tup[1]
gene_commentary_id = snp_annotation_type_tup[2]
else:
gene_id = None
gene_commentary_id = None
if len(snp_annotation_type_tup)>=4:
which_exon_or_intron = snp_annotation_type_tup[3]
else:
which_exon_or_intron = None
if len(snp_annotation_type_tup)>=5:
pos_within_codon = snp_annotation_type_tup[4]
else:
pos_within_codon = None
if len(snp_annotation_type_tup)>=6:
comment = snp_annotation_type_tup[5]
else:
comment = None
entry = Stock_250kDB.SNPAnnotation(snps_id=snps_id, gene_id=gene_id, gene_commentary_id=gene_commentary_id, \
which_exon_or_intron=which_exon_or_intron, pos_within_codon=pos_within_codon,\
comment=comment)
entry.snp_annotation_type_id = snp_annotation_short_name2id[snp_annotation_type_short_name]
session.add(entry)
real_counter += 1
if self.report and counter%2000==0:
sys.stderr.write("%s%s\t%s"%('\x08'*40, counter, real_counter))
session.flush()
if self.report:
sys.stderr.write("%s%s\t%s\n"%('\x08'*40, counter, real_counter))
sys.stderr.write("Done.\n")
print("str(seq1) == str(seq2)")
else:
print("str(seq1) != str(seq2)")
#MutableSeq 对象
"""
就像正常的 Python 字符串，Seq 对象是“只读的”，在 Python 术语上就是不可变的。除了想要 Seq 对
象表现得向一个字符串之外，这是一个很有用的默认，因为在生物学应用上你往往需要确保你没有改动你的
序列数据
"""
print("\n###############\n8. 可变对象\n---------------")
my_seq = Seq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna)
try:
my_seq[5] = "G"
print("可以改变碱基")
except:
print("无法改变碱基")
mutable_seq = my_seq.tomutable() #转换为可变对象
print("可变对象(转变):", repr(mutable_seq))
from Bio.Seq import MutableSeq
mutable_seq = MutableSeq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna) #直接创建可变对象
print("可变对象(创建):", repr(mutable_seq))
try:
mutable_seq[5] = "C"
print("可以改变碱基")
except:
print("无法改变碱基")
#转换为只读对象
new_seq = mutable_seq.toseq()
5' ATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAG 3'
|||||||||||||||||||||||||||||||||||||||
3' TACCGGTAACATTACCCGGCGACTTTCCCACGGGCTATC 5'
|
Transcription
↓
5’ AUGGCCAUUGUAAUGGGCCGCUGAAAGGGUGCCCGAUAG 3’
messenger-RNA
"""
from Bio.Seq import Seq, MutableSeq
from Bio.Alphabet import IUPAC
dna = Seq("TACATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAGTAA",
IUPAC.unambiguous_dna)
print(repr(dna))
dna_m = dna.tomutable() #mutable DNA
dna_m[8] = "A"
print(repr(dna_m))
m_rna = dna.complement().transcribe() #transcribtion
print(repr(m_rna))
protein = m_rna.translate() #translation
print(repr(protein))
mitochondrial_protein = m_rna.translate("Bacterial")
print(repr(mitochondrial_protein))
# my_seq = Seq("GATCG", IUPAC.unambiguous_dna)
# for index, letter in enumerate(my_seq):
# print("%i %s" % (index, letter))
standard_table = CodonTable.unambiguous_dna_by_name["Standard"]
# or by_id[1]
mito_table = CodonTable.unambiguous_dna_by_name["Vertebrate Mitochondrial"]
# or by_id[2]
# standard_table.stop_codons
# print(standard_table.stop_codons)
# compare sequences as strings
j1 = Seq("ATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAG", IUPAC.unambiguous_dna)
j2 = Seq("ATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATTG", IUPAC.unambiguous_dna)
str(j1) == str(j2)
# You cant index and change regular sequences, but if you make them mutable you can do basically anything you want
j3 = j2.tomutable()
j3[0::1]
j3.pop()
# or do this
mutable_seq = MutableSeq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA",
IUPAC.unambiguous_dna)
# print(mutable_seq.remove("G"))
def read_ref(ref_path, ref_inds_i, n_handling, n_unknowns=True, quiet=False):
tt = time.time()
if not quiet:
print('reading ' + ref_inds_i[0] + '... ')
absolute_reference_path = pathlib.Path(ref_path)
if absolute_reference_path.suffix == '.gz':
ref_file = gzip.open(absolute_reference_path, 'rt')
else:
ref_file = open(absolute_reference_path, 'r')
# TODO convert to SeqIO containers
# for seq_record in SeqIO.parse(ref_file, "fasta"):
# pass
ref_file.seek(ref_inds_i[1])
my_dat = ''.join(ref_file.read(ref_inds_i[2] - ref_inds_i[1]).split('\n'))
my_dat = Seq(my_dat.upper())
# Mutable seqs have a number of disadvantages. I'm going to try making them immutable and see if that helps
# my_dat = my_dat.tomutable()
# find N regions
# data explanation: my_dat[n_atlas[0][0]:n_atlas[0][1]] = solid block of Ns
prev_ni = 0
n_count = 0
n_atlas = []
for i in range(len(my_dat)):
if my_dat[i] == 'N' or (n_unknowns and my_dat[i] not in OK_CHR_ORD):
if n_count == 0:
prev_ni = i
n_count += 1
if i == len(my_dat) - 1:
n_atlas.append((prev_ni, prev_ni + n_count))
else:
if n_count > 0:
n_atlas.append((prev_ni, prev_ni + n_count))
n_count = 0
# handle N base-calls as desired
# TODO this seems to randomly replace an N with a base. Is this necessary? How to do this in an immutable seq?
n_info = {'all': [], 'big': [], 'non_N': []}
if n_handling[0] == 'random':
for region in n_atlas:
n_info['all'].extend(region)
if region[1] - region[0] <= n_handling[1]:
for i in range(region[0], region[1]):
temp = my_dat.tomutable()
temp[i] = random.choice(ALLOWED_NUCL)
my_dat = temp.toseq()
else:
n_info['big'].extend(region)
elif n_handling[0] == 'allChr' and n_handling[2] in OK_CHR_ORD:
for region in n_atlas:
n_info['all'].extend(region)
if region[1] - region[0] <= n_handling[1]:
for i in range(region[0], region[1]):
temp = my_dat.tomutable()
temp[i] = n_handling[2]
my_dat = temp.toseq()
else:
n_info['big'].extend(region)
elif n_handling[0] == 'ignore':
for region in n_atlas:
n_info['all'].extend(region)
n_info['big'].extend(region)
else:
print('\nERROR: UNKNOWN N_HANDLING MODE\n')
sys.exit(1)
habitable_regions = []
if not n_info['big']:
n_info['non_N'] = [(0, len(my_dat))]
else:
for i in range(0, len(n_info['big']), 2):
if i == 0:
habitable_regions.append((0, n_info['big'][0]))
else:
habitable_regions.append((n_info['big'][i - 1], n_info['big'][i]))
habitable_regions.append((n_info['big'][-1], len(my_dat)))
for n in habitable_regions:
if n[0] != n[1]:
n_info['non_N'].append(n)
ref_file.close()
if not quiet:
print('{0:.3f} (sec)'.format(time.time() - tt))
return my_dat, n_info
seq=Seq('CCGGUU',IUPAC.IUPACUnambiguousRNA()) #constructor class IUPAC...RNA
print seq
print seq.back_transcribe() #must be RNA to backtranscribe to DNA
seq=Seq('ATGGTCTTTCCAGACGCG',IUPAC.unambiguous_dna)
print Seq.transcribe(seq) #as function, up is as method
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')
if codon_1.translate(table="Bacterial") != (Seq(str(codon_1_ms),generic_dna)).translate(table="Bacterial"):
nonsyn_subst_int.append(1)
nonsyn_position_int[str(perm[l][l2]+1)] = nonsyn_position_int[str(perm[l][l2]+1)]+1
if (CODON[perm[l][l2]] == "A" or CODON[perm[l][l2]] == "T") and (codon_1_ms[perm[l][l2]] == "G" or codon_1_ms[perm[l][l2]] == "C"):
nonsyn_subst_to_gc_int.append(1)
nonsyn_position_to_gc_int[str(perm[l][l2]+1)] = nonsyn_position_to_gc_int[str(perm[l][l2]+1)]+1
gc_dict_int[str(perm[l][l2]+1)] = gc_dict_int[str(perm[l][l2]+1)]+1
else:
syn_subst_int.append(1)
syn_position_int[str(perm[l][l2]+1)] = syn_position_int[str(perm[l][l2]+1)]+1
if (CODON[perm[l][l2]] == "A" or CODON[perm[l][l2]] == "T") and (codon_1_ms[perm[l][l2]] == "G" or codon_1_ms[perm[l][l2]] == "C"):
syn_subst_to_gc_int.append(1)
syn_position_to_gc_int[str(perm[l][l2]+1)] = syn_position_to_gc_int[str(perm[l][l2]+1)]+1
gc_dict_int[str(perm[l][l2]+1)] = gc_dict_int[str(perm[l][l2]+1)]+1
codon_1 = Seq(str(codon_1_ms))
codon_1_ms, codon_2_ms = codon_1.tomutable(), codon_2.tomutable()
# Score correction
syn_subst.append(sum(syn_subst_int)*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int))))
nonsyn_subst.append((sum(nonsyn_subst_int)*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int)))))
syn_subst_to_gc.append((sum(syn_subst_to_gc_int)*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int)))))
nonsyn_subst_to_gc.append((sum(nonsyn_subst_to_gc_int)*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int)))))
for x in range(0,3):
gc_dict[str(x+1)] = gc_dict[str(x+1)]+(gc_dict_int[str(x+1)]*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int))))
codon_gc_dict[str(x+1)] = codon_gc_dict[str(x+1)]+(codon_gc_dict_int[str(x+1)]*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int))))
syn_position[str(x+1)] = syn_position[str(x+1)]+(syn_position_int[str(x+1)]*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int))))
nonsyn_position[str(x+1)] = nonsyn_position[str(x+1)]+(nonsyn_position_int[str(x+1)]*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int))))
syn_position_to_gc[str(x+1)] = syn_position_to_gc[str(x+1)]+(syn_position_to_gc_int[str(x+1)]*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int))))
nonsyn_position_to_gc[str(x+1)] = nonsyn_position_to_gc[str(x+1)]+(nonsyn_position_to_gc_int[str(x+1)]*(float(len(perm))/(sum(syn_subst_int)+sum(nonsyn_subst_int))))
my_gene = Seq("ACTAGCAGCGGA", generic_dna)
print(type(my_gene))
attributes = [a for a in dir(my_gene) if not a.startswith("_")]
print(attributes)
my_transcript = my_gene.transcribe()
print(my_transcript)
print(my_transcript.alphabet)
my_protein = my_gene.translate()
print(my_protein)
print(my_protein.alphabet)
coding_dna = Seq("ATGGCCATTGTAATGGGCCGCTGAAAGGGTGCCCGATAG", generic_dna)
myprot = coding_dna.translate(to_stop=True)
print(myprot)
seq1 = Seq("AAACGGA", generic_dna)
seq2 = Seq("GGAGAT", generic_dna)
mut_seq = seq1.tomutable()
mut_seq
mut_seq[0] = "G"
print(mut_seq)
myseq = Seq("CCAGAAACCCGGAA", generic_dna)
#find the first occurence of the pattern
print(myseq.find("GAA"))
#find the number of non-overlapping occurrences of a pattern
print(myseq.count("GAA"))
dna_seq = Seq("ACGT", generic_dna)
prot_seq = Seq("ACGT", generic_protein)
dna_seq == prot_seq
## BiopythonWarning: Incompatible alphabets DNAAlphabet() and ProteinAlphabet()
# MutableSeq objects
from Bio.Seq import Seq
from Bio.Alphabet import IUPAC
my_seq = Seq("GCCATTGTAATGGGCCGCTGAAAGGGTGCCCGA", IUPAC.unambiguous_dna)
#my_seq[5] = "G"
## Error expected
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
from Bio.Seq import Seq
seq1 = Seq("ACSA")
seq2 = Seq("AST")
seq3 = Seq("ACCST")
hmm1 = Seq("")
hmm1 = hmm1.tomutable()
batas = 4
def kurangDari(seqAwal,seqAkhir):
y = 0
for x in range(len(seqAwal)):
if seqAwal[x] == seqAkhir[y]:
hmm1.append('M')
y = y + 1
elif x + 1 < len(seqAwal):
if seqAwal[x + 1] == seqAkhir[y]:
hmm1.append('D')
else:
hmm1.append('D')
hmm1.append('I')
y = y + 1
else:
hmm1.append('M')
def lebihDari(seqAwal,seqAkhir):
y = 0
for x in range(len(seqAkhir)):
if seqAwal[y] == seqAkhir[x]:
hmm1.append('M')
y = y + 1
elif x + 1 < len(seqAkhir):
my_seq = Seq("GCCATTGTAATGGAATTAGTGGGTAACCCAGGGTAAACCTACCACCCCAGCCACCTCAG",
IUPAC.unambiguous_dna)
#my_seq[5]="G" This line won't work becuase the object(Seq) is immutable
from Bio.Seq import MutableSeq
mutable_seq = MutableSeq(
"GCCATTGTAATGGAATTAGTGGGTAACCCAGGGTAAACCTACCACCCCAGCCACCTCAG",
IUPAC.unambiguous_dna)
mutable_seq[5] = "C"
mutable_seq.remove("T")
mutable_seq.reverse()
k = my_seq.count('G')
mut_newseq = my_seq.tomutable()
for i in range(k):
mut_newseq.remove("G")
my_seq = Seq("AGCTTCCATTTGGGTCATGATCC")
print(my_seq.complement())
my_seq.count("T")
GC_count = 100 * float(my_seq.count("G")) + my_seq.count("C") / len(my_seq)
print(GC_count)
#Slicing a sequence
my_seq1 = Seq("GATTATTTCCCCGCGCCCAGTCAAGGTAGTGCCATAACCGTCCCTG",
IUPAC.unambiguous_dna)
print(my_seq1[4:12])
# Transcription and Tanslation
coding_dna = Seq("ATGGCCATTGTAATG")
template_dna = coding_dna.reverse_complement()
messenger_rna = transcribe(coding_dna)
print(messenger_rna)
print(back_transcribe(messenger_rna))
print(translate(messenger_rna))
myThirdSequence = Seq("GATCGATGGGGGCTATCC")
print(GC(myThirdSequence))
# MutableSeq objects
print(dna_seq)
#dna_seq[0]="T" --> Nicht veränderbar!
mutable_seq = dna_seq.tomutable()
mutable_seq[0] = "T"
print(mutable_seq)
mutableSeq = MutableSeq("GCCCATC")
mutableSeq[1] = "A"
print(mutableSeq)
print('\n')
#----------------------------------------
print("FASTA File")
handle = open("ecoli.fasta")
for seq_record in SeqIO.parse(handle, 'fasta'):
print(seq_record.id)
def _constructSNPAnnotation(self, session, snp_info, snps_context_wrapper, gene_annotation, snp_annotation_short_name2id):
"""
2009-2-5
bug fixed. when adding a box as UTR, make sure after the forloop above, the current box is still the UTR.
2009-1-5
"""
sys.stderr.write("Constructing SNPAnnotation ...\n")
standard_translator = Translate.unambiguous_dna_by_id[1]
counter = 0
real_counter = 0
for i in range(len(snp_info.chr_pos_ls)):
counter += 1
snps_id, chr, pos, allele1, allele2 = snp_info.data_ls[i]
snps_context_matrix = snps_context_wrapper.returnGeneLs(chr, pos)
snp_annotation_type_short_name_ls = [] #each element is (snp_annotation_type_short_name, gene_id, gene_commentary_id, which_exon_or_intron, pos_within_codon)
if snps_context_matrix:
for snps_context in snps_context_matrix:
snps_id, disp_pos, gene_id = snps_context
gene_model = gene_annotation.gene_id2model.get(gene_id)
if gene_model is None:
continue
for gene_commentary in gene_model.gene_commentaries:
if gene_commentary.protein_box_ls:
which_intron = -1 #which intron the SNP resides, starting from 1
which_coding_exon = -1 #which exon the SNP resides in terms of the CDS sequence, starting from 1
accum_intron_len = 0 #the cumulative length of all introns from the one after the first coding exon up till the SNP's position (including the intron the SNP is in if it's under the rule).
exon_5_end_pos = -1 #5' end position of the whole CDS sequence. bad name 'exon'
UTR_2nd = 0 #whether this is the 2nd UTR
box_type = None
UTR_type = None
is_SNP_within_box = 0 #protect against the possibility that SNP overshoots box_ls
for i in range(len(gene_commentary.box_ls)):
box = gene_commentary.box_ls[i]
start, stop, box_type, is_translated, protein_box_index = box
if box_type=='exon' and is_translated==0:
if UTR_2nd==0:
if gene_model.strand=='-1':
UTR_type='3UTR'
else:
UTR_type='5UTR'
UTR_2nd += 1
else:
if gene_model.strand=='-1':
UTR_type='5UTR'
else:
UTR_type='3UTR'
elif box_type=='exon' and is_translated==1:
if exon_5_end_pos==-1:
exon_5_end_pos=start
which_coding_exon += 1
elif box_type=='intron':
if which_coding_exon!=-1: #exclude introns that stand before the 1st coding exon
accum_intron_len += abs(stop-start)+1 #+1 because stop-start is intron_length-1
which_intron += 1
if pos>=start and pos<=stop: #with this box
is_SNP_within_box = 1
break
if gene_model.strand=='-1':
#continue to read the box_ls to count no_of_introns
no_of_introns = which_intron+1
for j in range(i+1, len(gene_commentary.box_ls)):
box = gene_commentary.box_ls[i]
if box[2]=='intron':
no_of_introns += 1
if box_type!=None and is_SNP_within_box==1: #box_type is the type of the box where the SNP resides
if UTR_type!=None and box_type=='exon' and is_translated==0: #it's UTR. bug fixed. make sure after the forloop above, the current box is still the UTR.
snp_annotation_type_short_name_ls.append((UTR_type, gene_id, gene_commentary.gene_commentary_id))
else:
if gene_model.strand=='-1': #reverse the order of exon/intron
no_of_coding_exons = len(gene_commentary.protein_box_ls)
#no_of_introns = len(gene_commentary.mrna_box_ls)-no_of_coding_exons #not right
which_coding_exon = no_of_coding_exons-which_coding_exon
which_intron = no_of_introns-which_intron
else:
which_coding_exon += 1
which_intron += 1
if box_type=='intron':
snp_annotation_type_short_name_ls.append(('intron', gene_id, gene_commentary.gene_commentary_id, which_intron))
if pos-start<=1: #within the donor/acceptor two-nucleotide
if gene_model.strand=='-1':
snp_annotation_type_short_name = 'splice-acceptor' #on the 3' of this intron
else:
snp_annotation_type_short_name = 'splice-donor' #on the 5' of this intron
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, which_intron))
elif stop-pos<=1:
if gene_model.strand=='-1':
snp_annotation_type_short_name = 'splice-donor' #on the 5' of this intron
else:
snp_annotation_type_short_name = 'splice-acceptor' #on the 3' of this intron
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, which_intron))
elif box_type=='exon': #must be translated
try:
SNP_index_in_CDS = pos - exon_5_end_pos - accum_intron_len
if gene_model.strand=='-1': #reverse
SNP_index_in_CDS = len(gene_commentary.cds_sequence)-SNP_index_in_CDS-1 #-1 because SNP_index_in_CDS starts from 0
gene_allele1 = nt2complement[allele1]
gene_allele2 = nt2complement[allele2]
else:
gene_allele1 = allele1
gene_allele2 = allele2
SNP_index_in_CDS = int(SNP_index_in_CDS) #SNP_index_in_CDS is type long. without int(), cds_seq[SNP_index_in_CDS] returns a Bio.Seq with one nucleotide, rather than a single-char string
SNP_index_in_peptide = SNP_index_in_CDS/3
SNP_index_in_peptide = int(SNP_index_in_peptide) #ditto as int(SNP_index_in_CDS), not necessary
pos_within_codon = SNP_index_in_CDS%3+1 #pos_within_codon starts from 1
cds_seq = Seq(gene_commentary.cds_sequence, IUPAC.unambiguous_dna)
if SNP_index_in_CDS>=len(cds_seq):
sys.stderr.write("Warning: SNP (%s, %s), SNP_index_in_CDS=%s, is beyond any of the boxes from gene %s (chr=%s, %s-%s), gene_commentary_id %s (%s-%s), box_ls=%s, cds-length=%s. counted as intergenic.\n"%\
(chr, pos, SNP_index_in_CDS, gene_id, gene_model.chromosome, gene_model.start, gene_model.stop, \
gene_commentary.gene_commentary_id, gene_commentary.start, gene_commentary.stop, repr(gene_commentary.box_ls), len(cds_seq)))
snp_annotation_type_short_name_ls.append(['intergenic'])
continue
if cds_seq[SNP_index_in_CDS]!=gene_allele1 and cds_seq[SNP_index_in_CDS]!=gene_allele2:
sys.stderr.write("Error: Neither allele (%s, %s) from SNP (%s,%s) matches the nucleotide, %s, from the cds seq of gene %s (gene_commentary_id=%s).\n"%\
(gene_allele1, gene_allele2, chr, pos, cds_seq[SNP_index_in_CDS], gene_id, gene_commentary.gene_commentary_id))
sys.exit(3)
cds_mut_ar = cds_seq.tomutable()
cds_mut_ar[SNP_index_in_CDS] = gene_allele1
peptide = standard_translator.translate(cds_mut_ar.toseq())
alt_cds_mut_ar = cds_seq.tomutable()
alt_cds_mut_ar[SNP_index_in_CDS] = gene_allele2
alt_peptide = standard_translator.translate(alt_cds_mut_ar.toseq())
aa = peptide[SNP_index_in_peptide]
alt_aa = alt_peptide[SNP_index_in_peptide]
if aa != alt_aa:
snp_annotation_type_short_name = 'non-synonymous'
comment = '%s->%s'%(aa, alt_aa)
else:
snp_annotation_type_short_name = 'synonymous'
comment = None
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, which_coding_exon, pos_within_codon, comment))
if aa != alt_aa:
if aa=='*' or alt_aa=='*':
snp_annotation_type_short_name = 'premature-stop-codon' #could also be the last stop codon changing to something else and thereby extending the cds
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, which_coding_exon, pos_within_codon, comment))
if SNP_index_in_peptide==0:
snp_annotation_type_short_name = 'init-Met'
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, which_coding_exon, pos_within_codon, comment))
except:
traceback.print_exc()
sys.stderr.write('%s.\n'%repr(sys.exc_info()))
sys.stderr.write("Except encountered for SNP (%s, %s), gene %s (chr=%s, %s-%s), gene_commentary_id %s (%s-%s), box_ls=%s.\n"%\
(chr, pos, gene_id, gene_model.chromosome, gene_model.start, gene_model.stop, \
gene_commentary.gene_commentary_id, gene_commentary.start, gene_commentary.stop, repr(gene_commentary.box_ls)))
elif box_type!=None and is_SNP_within_box==0: #SNP is over the range of the gene. it happens when one gene has multiple alternative splicing forms. snps_context_wrapper uses the largest span to represent the gene.
snp_annotation_type_short_name_ls.append(['intergenic'])
else:
sys.stderr.write("Warning: SNP (%s, %s) not in any of the boxes from gene %s (chr=%s, %s-%s), gene_commentary_id %s (%s-%s), box_ls=%s.\n"%\
(chr, pos, gene_id, gene_model.chromosome, gene_model.start, gene_model.stop, \
gene_commentary.gene_commentary_id, gene_commentary.start, gene_commentary.stop, repr(gene_commentary.box_ls)))
else:
if gene_model.type_of_gene=='pseudo':
snp_annotation_type_short_name = gene_model.type_of_gene
else:
snp_annotation_type_short_name = gene_commentary.gene_commentary_type
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary.gene_commentary_id, None))
else: #integenic
snp_annotation_type_short_name_ls.append(['intergenic'])
#now save everything into db
for snp_annotation_type_tup in snp_annotation_type_short_name_ls:
snp_annotation_type_short_name = snp_annotation_type_tup[0]
if snp_annotation_type_short_name not in snp_annotation_short_name2id:
ty = Stock_250kDB.SNPAnnotationType(short_name=snp_annotation_type_short_name)
session.save(ty)
session.flush()
snp_annotation_short_name2id[snp_annotation_type_short_name] = ty.id
if len(snp_annotation_type_tup)>=3:
gene_id = snp_annotation_type_tup[1]
gene_commentary_id = snp_annotation_type_tup[2]
else:
gene_id = None
gene_commentary_id = None
if len(snp_annotation_type_tup)>=4:
which_exon_or_intron = snp_annotation_type_tup[3]
else:
which_exon_or_intron = None
if len(snp_annotation_type_tup)>=5:
pos_within_codon = snp_annotation_type_tup[4]
else:
pos_within_codon = None
if len(snp_annotation_type_tup)>=6:
comment = snp_annotation_type_tup[5]
else:
comment = None
entry = Stock_250kDB.SNPAnnotation(snps_id=snps_id, gene_id=gene_id, gene_commentary_id=gene_commentary_id, \
which_exon_or_intron=which_exon_or_intron, pos_within_codon=pos_within_codon,\
comment=comment)
entry.snp_annotation_type_id = snp_annotation_short_name2id[snp_annotation_type_short_name]
session.save(entry)
session.flush()
real_counter += 1
if self.report and counter%2000==0:
sys.stderr.write("%s%s\t%s"%('\x08'*40, counter, real_counter))
if self.report:
sys.stderr.write("%s%s\t%s\n"%('\x08'*40, counter, real_counter))
sys.stderr.write("Done.\n")
#from Bio import motifs
from Bio import SeqIO
from Bio.Seq import Seq
from Bio.Seq import MutableSeq
#Parse 16S Seq
for rna in SeqIO.parse("vibrio.fasta", "fasta"):
#print(rna.seq)
#print(rna.id)
print(len(rna))
#Probe Seq
Probe = Seq("AGGCCACAACCTCCAAGTAG")
#convert probe string to mutable object
mutable_probe = Probe.tomutable()
global MutNum
#generate the random mutation position
def RandomPosition(Probe, MutateNum):
rp = np.random.choice(range(len(Probe)), MutateNum, replace=False)
RP = rp.tolist()
RP.sort() #sort the random position in convenient of checking
return RP
#generate the random mutation base
def RandomBase(ExistBase):
Base = ["A", "T", "C", "G"]
Base.remove(ExistBase)
def _constructSNPAnnotation(self, db_vervet, locus=None, oneGeneData=None, locus_context=None, locus_annotation_short_name2db_entry=None,\
geneCommentaryRBDict=None, geneSegmentKey = None, compareIns=None, param_obj=None):
"""
2012.5.18
add which_codon into the db_vervet.getLocusAnnotation()
2012.5.14
adapted from variation/src/ConstructSNPAnnotation.py
locus is of type VervetDB.Locus
oneGeneData = PassingData(strand = row.strand, gene_id = row.id, gene_start = row.start, \
gene_stop = row.stop, geneCommentaryRBDictLs=[],\
ncbi_gene_id=row.ncbi_gene_id)
2009-2-5
bug fixed. when adding a box as UTR, make sure after the forloop above, the current box is still the UTR.
2009-1-5
"""
sys.stderr.write("Constructing LocusAnnotation for SNP ...\n")
#standard_translator = Translate.unambiguous_dna_by_id[1] #2012.5.23 Translate is to be deprecated.
counter = 0
real_counter = 0
counter += 1
chr=locus.chromosome
pos = locus.start
allele1 = locus.ref_seq.sequence.encode('ascii') #2012.5.17 unicode is not accepted by cds_seq.tomutable()
allele2 = locus.alt_seq.sequence.encode('ascii')
snp_annotation_type_short_name_ls = [] #each element is (snp_annotation_type_short_name, gene_id, gene_commentary_id,
# which_exon_or_intron, pos_within_codon)
disp_pos = locus_context.disp_pos
gene_id = locus_context.gene_id
#gene_box_node_ls = []
#geneCommentaryRBDict.findNodes(segmentKey, node_ls=gene_box_node_ls, compareIns=compareIns)
gene_commentary_id = geneCommentaryRBDict.gene_commentary_id
box_ls = geneCommentaryRBDict.box_ls
protein_box_ls = geneCommentaryRBDict.protein_box_ls
#gene_commentary = GeneCommentary.get(gene_commentary_id)
#box_ls = gene_commentary.construct_annotated_box()
cds_sequence = geneCommentaryRBDict.cds_sequence
geneCommentaryRBDict.gene_commentary_type_name
CDS_5_end_pos = geneCommentaryRBDict.CDS_5_end_pos
no_of_introns = geneCommentaryRBDict.no_of_introns
detailed_box_type = geneSegmentKey.label
is_translated = geneSegmentKey.is_translated
which_intron = geneSegmentKey.intron_number #which intron the SNP resides, starting from 1
which_coding_exon = geneSegmentKey.cds_number #which exon the SNP resides in terms of the CDS sequence, starting from 1
cumulativeWithinCDSUTRAndIntronLen = geneSegmentKey.cumulativeWithinCDSUTRAndIntronLen
gene_segment_id = geneSegmentKey.gene_segment_id
if protein_box_ls: #this is a protein coding gene
if detailed_box_type.find('UTR')>=0 and detailed_box_type=='exon' and is_translated==0: #it's UTR. bug fixed. make sure after the forloop above,
# the current box is still the UTR.
snp_annotation_type_short_name_ls.append((detailed_box_type, gene_id, gene_commentary_id, None , None, None))
else:
if oneGeneData.strand=='-1': #reverse the order of exon/intron
no_of_coding_exons = len(protein_box_ls)
#no_of_introns = len(gene_commentary.mrna_box_ls)-no_of_coding_exons #not right
which_coding_exon = no_of_coding_exons-which_coding_exon+1
which_intron = no_of_introns-which_intron + 1
if detailed_box_type=='intron':
snp_annotation_type_short_name_ls.append(('intron', gene_id, gene_commentary_id, which_intron, None, None))
if pos-geneSegmentKey.start<=1: #within the donor/acceptor two-nucleotide
if oneGeneData.strand=='-1':
snp_annotation_type_short_name = 'splice-acceptor' #on the 3' of this intron
else:
snp_annotation_type_short_name = 'splice-donor' #on the 5' of this intron
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, \
gene_commentary_id, which_intron, None, None))
elif geneSegmentKey.stop-pos<=1:
if oneGeneData.strand=='-1':
snp_annotation_type_short_name = 'splice-donor' #on the 5' of this intron
else:
snp_annotation_type_short_name = 'splice-acceptor' #on the 3' of this intron
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, \
gene_commentary_id, which_intron, None, None))
elif detailed_box_type=='CDS': #must be translated
SNP_index_in_CDS = pos - CDS_5_end_pos - cumulativeWithinCDSUTRAndIntronLen
if oneGeneData.strand=='-1': #reverse
SNP_index_in_CDS = len(cds_sequence)-SNP_index_in_CDS-1 #-1 because SNP_index_in_CDS starts from 0
gene_allele1 = nt2complement[allele1]
gene_allele2 = nt2complement[allele2]
else:
gene_allele1 = allele1
gene_allele2 = allele2
SNP_index_in_CDS = int(SNP_index_in_CDS)
# SNP_index_in_CDS is type long. without int(), cds_seq[SNP_index_in_CDS] returns a Bio.Seq with one nucleotide,
# rather than a single-char string
SNP_index_in_peptide = SNP_index_in_CDS/3
SNP_index_in_peptide = int(SNP_index_in_peptide) #ditto as int(SNP_index_in_CDS), not necessary
pos_within_codon = SNP_index_in_CDS%3+1 #pos_within_codon starts from 1
cds_seq = Seq(cds_sequence, IUPAC.unambiguous_dna)
if SNP_index_in_CDS>=len(cds_seq):
sys.stderr.write("Error: SNP (%s, %s), SNP_index_in_CDS=%s, is beyond any of the boxes from gene %s (chr=%s, %s-%s), \
gene_commentary_id %s (%s-%s), box_ls=%s, cds-length=%s. counted as intergenic.\n"%\
(chr, pos, SNP_index_in_CDS, gene_id, oneGeneData.chromosome, oneGeneData.gene_start, oneGeneData.gene_stop, \
gene_commentary_id, geneCommentaryRBDict.start, geneCommentaryRBDict.stop, repr(box_ls), \
len(cds_seq)))
sys.exit(3)
snp_annotation_type_short_name_ls.append(['intergenic'])
if cds_seq[SNP_index_in_CDS]!=gene_allele1 and cds_seq[SNP_index_in_CDS]!=gene_allele2:
sys.stderr.write("Error: Neither allele (%s, %s) from SNP (%s,%s) matches the nucleotide, %s, from the cds seq of gene %s \
(gene_commentary_id=%s).\n"%\
(gene_allele1, gene_allele2, chr, pos, cds_seq[SNP_index_in_CDS], gene_id, gene_commentary_id))
sys.exit(3)
cds_mut_ar = cds_seq.tomutable()
cds_mut_ar[SNP_index_in_CDS] = gene_allele1
peptide = cds_mut_ar.toseq().translate() #2012.5.23 no more translator. table=1
alt_cds_mut_ar = cds_seq.tomutable()
alt_cds_mut_ar[SNP_index_in_CDS] = gene_allele2
alt_peptide = alt_cds_mut_ar.toseq().translate()
aa = peptide[SNP_index_in_peptide]
alt_aa = alt_peptide[SNP_index_in_peptide]
if aa != alt_aa:
snp_annotation_type_short_name = 'non-synonymous'
comment = '%s->%s'%(aa, alt_aa)
else:
snp_annotation_type_short_name = 'synonymous'
comment = None
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary_id, \
which_coding_exon, pos_within_codon, comment, SNP_index_in_peptide))
if aa != alt_aa:
if aa=='*' or alt_aa=='*':
snp_annotation_type_short_name = 'premature-stop-codon' #could also be the last stop codon changing to something else
# and thereby extending the cds
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary_id, \
which_coding_exon, pos_within_codon, comment, SNP_index_in_peptide))
if SNP_index_in_peptide==0:
snp_annotation_type_short_name = 'init-Met'
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary_id, \
which_coding_exon, pos_within_codon, comment, SNP_index_in_peptide))
"""
except:
traceback.print_exc()
sys.stderr.write('%s.\n'%repr(sys.exc_info()))
sys.stderr.write("Except encountered for SNP (%s, %s), gene %s (chr=%s, %s-%s), gene_commentary_id %s (%s-%s), box_ls=%s.\n"%\
(chr, pos, gene_id, locus.chromosome, oneGeneData.start, oneGeneData.stop, \
gene_commentary_id, geneCommentaryRBDict.start, geneCommentaryRBDict.stop, repr(box_ls)))
"""
else:
if oneGeneData.type_of_gene=='pseudo':
snp_annotation_type_short_name = oneGeneData.type_of_gene
else:
snp_annotation_type_short_name = geneCommentaryRBDict.gene_commentary_type_name
snp_annotation_type_short_name_ls.append((snp_annotation_type_short_name, gene_id, gene_commentary_id, \
None, None, None))
#else: #integenic
# snp_annotation_type_short_name_ls.append(['intergenic'])
#now save everything into db
locus_annotation_ls = []
for snp_annotation_type_tup in snp_annotation_type_short_name_ls:
snp_annotation_type_short_name = snp_annotation_type_tup[0]
if snp_annotation_type_short_name not in locus_annotation_short_name2db_entry:
ty = db_vervet.getLocusAnnotationType(locus_annotation_type_short_name=snp_annotation_type_short_name)
locus_annotation_short_name2db_entry[snp_annotation_type_short_name] = ty
if len(snp_annotation_type_tup)>=3:
gene_id = snp_annotation_type_tup[1]
gene_commentary_id = snp_annotation_type_tup[2]
else:
gene_id = None
gene_commentary_id = None
if len(snp_annotation_type_tup)>=4:
which_exon_or_intron = snp_annotation_type_tup[3]
else:
which_exon_or_intron = None
if len(snp_annotation_type_tup)>=5:
pos_within_codon = snp_annotation_type_tup[4]
else:
pos_within_codon = None
if len(snp_annotation_type_tup)>=6:
comment = snp_annotation_type_tup[5]
else:
comment = None
if len(snp_annotation_type_tup)>=7:
which_codon = snp_annotation_type_tup[6] +1 #[6] is the SNP_index_in_peptide
else:
which_codon = None
locus_annotation_type = locus_annotation_short_name2db_entry.get(snp_annotation_type_short_name)
locus_annotation = db_vervet.getLocusAnnotation(locus_id=locus.id, locus_context_id=locus_context.id, \
locus_context=locus_context, gene_id=gene_id, \
gene_commentary_id=gene_commentary_id, \
gene_segment_id=gene_segment_id, \
locus_annotation_type=locus_annotation_type, locus_annotation_type_id=locus_annotation_type.id,\
which_exon_or_intron=which_exon_or_intron, pos_within_codon=pos_within_codon, \
which_codon=which_codon, label=geneSegmentKey.label, \
utr_number=geneSegmentKey.utr_number, cds_number=geneSegmentKey.cds_number, \
intron_number=geneSegmentKey.intron_number,\
exon_number=geneSegmentKey.exon_number, overlap_length=None, \
overlap_fraction_in_locus=None, overlap_fraction_in_gene=None,\
comment=comment)
if locus_annotation:
param_obj.no_of_locus_annotations_already_in_db += 1
else:
param_obj.no_of_into_db += 1
param_obj.no_of_total_annotations += 1
locus_annotation_ls.append(locus_annotation)
real_counter += 1
"""
if self.report and counter%2000==0:
sys.stderr.write("%s%s\t%s"%('\x08'*40, counter, real_counter))
session.flush()
if self.report:
sys.stderr.write("%s%s\t%s\n"%('\x08'*40, counter, real_counter))
"""
sys.stderr.write("Done.\n")
return locus_annotation_ls
#print CodonTable.unambiguous_dna_by_id[2]
print CodonTable.unambiguous_dna_by_id[1].stop_codons
print CodonTable.unambiguous_dna_by_id[2].start_codons
print CodonTable.unambiguous_dna_by_id[1].forward_table['ACG'] # which aminoacid for this codon
#Comparing Sequences
seq1 = Seq('ACGT',IUPAC.unambiguous_dna)
seq2 = Seq('ACGT',IUPAC.unambiguous_dna)
seq3 = Seq('ACGT',IUPAC.protein)
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
