def write_annotation_for_orf(outputgff_file, candidatedbname, dbname_weight,
results_dictionary, orf_dictionary, contig,
candidate_orf_pos, orfid, compact_output):
global errorcode
try:
fields = [
'source', 'feature', 'start', 'end', 'score', 'strand', 'frame'
]
output_line = orf_dictionary[contig][candidate_orf_pos]['seqname']
#if compact_output:
#output_line = ShortenContigId(output_line)
for field in fields:
output_line += "\t" + str(
orf_dictionary[contig][candidate_orf_pos][field])
#if compact_output:
try:
attributes = "ID=" + ShortenORFId(
orf_dictionary[contig][candidate_orf_pos]['id'])
attributes += ";" + "locus_tag=" + ShortenORFId(
orf_dictionary[contig][candidate_orf_pos]['locus_tag'])
except:
attributes = "ID=" + orf_dictionary[contig][candidate_orf_pos]['id']
attributes += ";" + "locus_tag=" + orf_dictionary[contig][
candidate_orf_pos]['locus_tag']
attributes += ";" + "contig_length=" + orf_dictionary[contig][
candidate_orf_pos]['contig_length']
attributes += ";" + "orf_length=" + orf_dictionary[contig][
candidate_orf_pos]['orf_length']
attributes += ";" + "partial=" + orf_dictionary[contig][
candidate_orf_pos]['partial']
attributes += ";" + "sourcedb=" + candidatedbname
if candidatedbname in results_dictionary:
attributes += ";" + "annotvalue=" + str(
results_dictionary[candidatedbname][orfid]['value'])
attributes += ";" + "ec=" + str(
results_dictionary[candidatedbname][orfid]['ec'])
attributes += ";" + "product=" + results_dictionary[
candidatedbname][orfid]['product']
else:
attributes += ";" + "annotvalue=" + str('0')
attributes += ";" + "ec=" + str('')
attributes += ";" + "product=" + 'hypothetical protein'
output_line += '\t' + attributes
if candidatedbname in results_dictionary:
fprintf(outputgff_file, "%s\n", output_line)
except:
eprintf("ERROR : Failure to annotate in contig %s\n", contig)
#print orf_dictionary[contig]
print traceback.print_exc(10)
insert_error(errorcode)
exit_process()
def write_16S_tRNA_gene_info(rRNA_dictionary, outputgff_file, tag):
fields = [ 'source', 'feature', 'start', 'end', 'score', 'strand', 'frame' ]
for rRNA in rRNA_dictionary:
output_line= rRNA_dictionary[rRNA]['id']
for field in fields:
output_line += "\t"+ str(rRNA_dictionary[rRNA][field])
attributes = "ID="+ShortenORFId(rRNA_dictionary[rRNA]['seqname']) + tag
attributes += ";" + "locus_tag="+ShortenORFId(rRNA_dictionary[rRNA]['seqname']) + tag
attributes += ";" + "orf_length=" + str(rRNA_dictionary[rRNA]['orf_length'])
attributes += ";" + "contig_length=" + str(rRNA_dictionary[rRNA]['contig_length'])
attributes += ";" + "ec="
attributes += ";" + "product="+rRNA_dictionary[rRNA]['product']
output_line += '\t' + attributes
fprintf(outputgff_file, "%s\n", output_line);
def write_refscores(refscore_file, refscores, compact_output=False):
for key, value in refscores.items():
orfid = key
if compact_output:
orfid = ShortenORFId(key)
fprintf(refscore_file, "%s\t%s\n", orfid, value)
def next(self):
if self.i < self.size:
try:
fields = [x.strip() for x in self.lines[self.i].split('\t')]
#print self.fieldmap['ec'], fields, self.i, self.blastoutput
self.data['query'] = ShortenORFId(
fields[self.fieldmap['query']])
self.data['q_length'] = int(fields[self.fieldmap['q_length']])
self.data['bitscore'] = float(
fields[self.fieldmap['bitscore']])
self.data['bsr'] = float(fields[self.fieldmap['bsr']])
self.data['expect'] = float(fields[self.fieldmap['expect']])
self.data['identity'] = float(
fields[self.fieldmap['identity']])
self.data['ec'] = fields[self.fieldmap['ec']]
self.data['product'] = re.sub(r'=', ' ',
fields[self.fieldmap['product']])
self.i = self.i + 1
return self.data
except:
print self.lines[self.i]
print data
sys.exit(0)
return None
else:
raise StopIteration()
def insert_attribute(attributes, attribStr):
rawfields = re.split('=', attribStr)
if len(rawfields) == 2:
if rawfields[0].strip().lower() == 'id':
orfid = ShortenORFId(rawfields[1].strip())
attributes[rawfields[0].strip().lower()] = orfid
else:
attributes[rawfields[0].strip().lower()] = rawfields[1].strip()
def create_refBitScores(self):
refscorefile = open(self.refscore_file,'r')
for line in refscorefile:
words =[ x.strip() for x in line.split('\t') ]
if len(words) == 2:
orfid = ShortenORFId(words[0])
try:
self.refBitScores[orfid]= int((self.Lambda*float(words[1]) - self.lnk )/self.ln2)
except:
self.refBitScores[orfid]= int(1)
refscorefile.close()
def next(self):
if self.i % self.Size == 0:
self.refillBuffer()
if self.i % self.Size < self.size:
words = [
x.strip()
for x in self.lines[self.i % self.Size].rstrip().split('\t')
]
if len(words) != 12:
self.i = self.i + 1
return None
'''shorten the ORF id'''
words[0] = ShortenORFId(words[0])
#if self.opts.algorithm =='LAST':
if self.needToPermute:
self.permuteForLAST(words)
if not words[0] in self.hits_counts:
self.hits_counts[words[0]] = 0
if self.hits_counts[words[0]] >= self.opts.limit:
self.i = self.i + 1
return None
if len(words) != 12 or not self.isWithinCutoffs(
words, self.data, self.opts, self.annot_map,
self.refBitScores):
self.i = self.i + 1
return None
self.hits_counts[words[0]] += 1
self.i = self.i + 1
try:
return self.data
except:
return None
else:
self.blastoutputfile.close()
raise StopIteration()
def create_annotation(results_dictionary, dbname, annotated_gff, output_dir, Taxons, orfsPicked, orfToContig, lca, compact_output= False, sample_name = ""):
meganTree = None
#lca.set_results_dictionary(results_dictionary)
if not path.exists(output_dir):
makedirs(output_dir)
orf_dictionary={}
#process_gff_file(annotated_gff, orf_dictionary)
gffreader = GffFileParser(annotated_gff)
output_table_name = output_dir + PATHDELIM + sample_name + ".functional_and_taxonomic_table.txt"
output_table_file = open(output_table_name, 'a')
count = 0
for contig in gffreader:
# shortORFId = getShortORFId(orf['id'])
for orf in gffreader.orf_dictionary[contig]:
shortORFId = getShortORFId(orf['id'])
count +=1
#shortORFId = ShortenORFId(orf['id'])
if shortORFId not in orfsPicked:
continue
orfToContig[shortORFId] = contig
taxonomy = None
#_results = re.search(r'refseq', opts_global.database_name, re.I)
if shortORFId in Taxons:
taxonomy1=Taxons[shortORFId]
#print taxonomy1, shortORFId
taxonomy_id=lca.get_supported_taxon(taxonomy1, return_id=True)
# print taxonomy_id
preferred_taxonomy = lca.get_preferred_taxonomy(taxonomy_id)
if preferred_taxonomy:
taxonomy = preferred_taxonomy
else:
taxonomy = Taxons[shortORFId]
else:
taxonomy = 'root'
product = orf['product'] # leave product as it is
# product = re.sub(r'\[{1,2}.+?\]{1,2}','', orf['product']).strip()
# product = re.sub(r'\[[^\[]+?\]','', orf['product']).strip()
# if "partial" in orf['product']:
# print orf['product'].strip()
# print product
orf_id = orf['id']
seqname = orf['seqname']
if compact_output:
orf_id = ShortenORFId(orf_id)
seqname = ShortenContigId(seqname)
fprintf(output_table_file, "%s", orf_id)
fprintf(output_table_file, "\t%s", orf['orf_length'])
fprintf(output_table_file, "\t%s", orf['start'])
fprintf(output_table_file, "\t%s", orf['end'])
fprintf(output_table_file, "\t%s", seqname)
fprintf(output_table_file, "\t%s", orf['contig_length'])
fprintf(output_table_file, "\t%s", orf['strand'])
fprintf(output_table_file, "\t%s", orf['ec'])
# fprintf(output_table_file, "\t%s", str(species))
fprintf(output_table_file, "\t%s", taxonomy)
fprintf(output_table_file, "\t%s\n", product)
# adding taxons to the megan tree
#if meganTree and taxonomy != '':
# meganTree.insertTaxon(taxonomy)
#print meganTree.getChildToParentMap()
output_table_file.close()
def write_ptinput_files(output_dir_name, contig_dict, sample_name,
nucleotide_seq_dict, protein_seq_dict, compact_output):
try:
#print output_dir_name
removeDir(output_dir_name)
#print output_dir_name
makedirs(output_dir_name)
genetic_elements_file = open(
output_dir_name + "/.tmp.genetic-elements.dat", 'w')
reducedpffile = open(output_dir_name + "/tmp.reduced.txt", 'w')
except:
print "cannot create the pathway tools files"
print "perhaps there is already a folder " + output_dir_name
traceback.print_exc(file=sys.stdout)
count = 0
outputStr = ""
# iterate over every contig sequence
first_hits = {}
for key in contig_dict:
first = True
if count % 10000 == 0:
#print "count " + str(count)
#outputfile.write(outputStr)
outputStr = ""
count += 1
for attrib in contig_dict[key]:
id = attrib['id']
shortid = ""
if attrib['feature'] == 'CDS':
shortid = 'O_' + ShortenORFId(attrib['id'])
if attrib['feature'] == 'tRNA':
shortid = 'O_' + ShortentRNAId(attrib['id'])
try:
protein_seq = protein_seq_dict[id]
except:
protein_seq = ""
try:
if attrib['product'] == 'hypothetical protein':
continue
except:
print attrib
sys.exit(0)
if attrib['product'] in first_hits:
if attrib['ec']:
if attrib['ec'] in first_hits[attrib['product']]:
fprintf(reducedpffile, "%s\t%s\n", shortid,
first_hits[attrib['product']]['n'])
# to remove redundancy add "continue "
# continue
else:
first_hits[attrib['product']]['ec'] = attrib['ec']
first_hits[attrib['product']]['n'] = shortid
else:
fprintf(reducedpffile, "%s\t%s\n", shortid,
first_hits[attrib['product']]['n'])
# to remove redundancy add "continue "
#continue
else:
first_hits[attrib['product']] = {}
first_hits[attrib['product']]['n'] = shortid
first_hits[attrib['product']]['ec'] = attrib['ec']
# create the pf file
write_to_pf_file(output_dir_name, shortid, attrib)
# append to the gen elements file
append_genetic_elements_file(genetic_elements_file,
output_dir_name, shortid)
#endfor
#write the sequence now only once per contig
try:
contig_seq = nucleotide_seq_dict[key]
except:
printf(
"ERROR: Contig %s missing file in \"preprocessed\" folder for sample\n",
key)
continue
fastaStr = wrap("", 0, 62, contig_seq)
#write_ptools_input_files(genetic_elements_file, output_dir_name, shortid, fastaStr)
write_input_sequence_file(output_dir_name, shortid, fastaStr)
#endif
rename(output_dir_name + "/tmp.reduced.txt",
output_dir_name + "/reduced.txt")
# Niels: removing annotated.gff from sample_name
sample_name = re.sub(".annot.gff", '', sample_name)
sample_name = re.sub('.*/', '', sample_name)
sample_name = re.sub(r'[\\].', '', sample_name)
# Niels: trim sample_name to less than 35 characters
# as it causes PGDB creation to fail
if (len(sample_name) > 35):
sample_name = sample_name[0:35]
if not sample_name[0].isalpha():
sample_name = 'E' + sample_name
write_organisms_dat_file(output_dir_name, sample_name)
genetic_elements_file.close()
rename(output_dir_name + "/.tmp.genetic-elements.dat",
output_dir_name + "/genetic-elements.dat")