def write_reads(self, out_file_handle, output_format='fasta', filter_expression=None,
startidx=0, rowbuffer=100000, overwrite=False):
""" Write records returned by the querry to one large fasta or fastq
Defaults is to search by GLOBing the individual descriptions with the search_query.
If sql_query = True, search_query is passed as a full sql statment.
If use_type_column=True, search is done by GLOBing the individual type column instead.
out_file_handle -- A file object or string specifying a filename.
startidx -- starting base index of DNA sequence that is written, used to miss out
cutsite if necessary.
"""
# Output check
out_file_handle = outputfile_check(out_file_handle, mode='a', overwrite=overwrite)
query = '''SELECT seqid, seq, phred
FROM seqs INNER JOIN samples ON seqs.sampleId=samples.sampleId'''
if filter_expression:
query += ' WHERE {0}'.format(filter_expression)
with self.con as con:
toc = time.time()
print >> sys.stderr, 'Writing records to {0} format....'.format(output_format),
c = con.execute(query)
returned_records = c.fetchmany(rowbuffer)
rec_count = 0
while returned_records:
for rec in returned_records:
seq_rec = SeqRecord(Seq(rec['seq'][startidx:]), id=str(rec['seqid']), description='')
if output_format == 'fastq':
seq_rec.letter_annotations['phred_quality'] = [ord(x) - 33 for x in rec['phred']]
SeqIO.write(seq_rec, out_file_handle, format=output_format)
rec_count += 1
# Fetch next batch of records from cursor
returned_records = c.fetchmany(rowbuffer)
print >> sys.stderr, ' Done!'
print >> sys.stderr, '\n{0} records written successfully to {1}\nin {2}'.format(rec_count,
out_file_handle.name, time.strftime('%H:%M:%S', time.gmtime(time.time() - toc)))
if out_file_handle.name not in ['<stdout>', '<stderr>']:
out_file_handle.close()
return out_file_handle
def run(self, infile_handle):
''' Run CD-HIT in parallel on list of fasta files. Each file is clustered seperately.
Other flags used:
-d 0 --> No limit on description written to cluster file (goes to first space in seq ID).
-r 0 --> DO Only +/+ and not -/+ alignment comparisons as reads are done in both directions but on different strands.
-s 0.8 --> If shorter sequence is less than 80% of the representative sequence, dont cluster.
infile_handle -- Takes file object or string of the file path/filename
ouput -- Defines output location and file name.
Writes stdout to console.
Counter dictionary and summary logfile are generated after each run.
'''
# input checks
infile_handle = inputfile_check(infile_handle)
logfile_path = os.path.join(os.path.split(self.args.output)[0], 'clusterfile.log')
infile_path = os.path.abspath(infile_handle.name)
logfile = outputfile_check(logfile_path)
# setup internal vars
start_time = time.time()
#=======================================================================
# Run CDHIT
#=======================================================================
cmd = ('cd-hit-est -i {0} -o {1} -c {2} -n {3} -d 0 -r 0 -s 0.8 -M {4} '
'-T {5}').format(infile_path, self.args.output,
self.args.similarity,
self.args.n_gram,
self.args.maxmemory,
self.args.threads)
if self.args.maskN:
cmd = cmd + ' -mask N'
if self.args.allvall:
cmd = cmd + ' -g 1'
cdhitpath = os.path.expanduser(self.args.cdhitpath)
# Spawn Process to run CD-HIT
subprocess.check_call(shlex.split(os.path.join(cdhitpath, cmd)))
finish_time = time.time()
#=======================================================================
# Generate a summary log file
#=======================================================================
# Get cluster size summary counter
total_counter, by_seqlen_counter = self.cluster_summary_counter(infile_path=self.args.output,
mode='both', report=True)
st_idx = cmd.find('-c ')
CDHIT_parameters = cmd[st_idx:]
# Write summary logfile
with logfile as f:
program_name = os.path.join(self.args.cdhitpath, cmd).split(' -i ')[0]
f.write('=========================================================\n')
f.write('Program : {0}\n'.format(program_name))
f.write('Input File : {0}\n'.format(infile_path))
f.write('Output File : {0}\n'.format(self.args.output))
f.write('Commands : {0}\n'.format(CDHIT_parameters))
f.write('\n')
f.write('Started : {0}\n'.format(time.strftime('%a, %d %b %Y, %H:%M:%S',
time.gmtime(start_time))))
f.write('=========================================================\n')
f.write('\n')
f.write(' Report Log\n')
f.write('---------------------------------------------------------\n')
reads_per_cluster = {key: int(key)*value for key, value in total_counter.iteritems()}
total_reads = sum(reads_per_cluster.values())
total_clusters = sum(total_counter.values())
f.write('Total number of reads : {0}\n'.format(total_reads))
f.write('Total number of clusters : {0}\n'.format(total_clusters))
read_lengths = [int(key) for key in by_seqlen_counter.keys()]
f.write('Read length Min and Max : {0} and {1}\n'.format(min(read_lengths), max(read_lengths)))
f.write('Time taken : {0}\n'.format(time.strftime('%H:%M:%S',
time.gmtime(finish_time - start_time))))
f.write('\n')
f.write('Top 20 Percentage Reads per cluster \n')
f.write('---------------------------------------------------------\n')
f.write('Cluster Size No. Clusters Total Reads % \n')
f.write('---------------------------------------------------------\n')
top_reads_per_cluster = sorted(reads_per_cluster.iteritems(),
key=lambda tup: int(tup[1]), reverse=True)[:20]
for tup in top_reads_per_cluster:
if total_reads == 0:
perc = 0.0
else:
perc = float(tup[1]) / total_reads
f.write("{clust_size: <16}{num_clust: <16}{total_reads: <18d}{percentage:.2%}\n".format(
clust_size=tup[0], num_clust=total_counter[tup[0]], total_reads=tup[1],
percentage=perc))
cluster_file_handle = open(self.args.output, 'rb')
return cluster_file_handle, total_counter
