def extract_dbotu_otu_seqs(membershipfn, fasta_derep, otu_seqs_fn):
"""
Parameters
----------
membershipfn membership filename, made by dbotu.call_otus
has OTU representative seq IDs in first column, and
OTU member seq IDs in rest of row
fatas_derep fasta dereplicated; sequence IDs should match those
in membershipfn
out_seqs_fn output fasta file to write representative seqs to
"""
## Parse membership file
with open(membershipfn, 'r') as f:
lines = f.readlines()
otu_reps = [l.split('\t')[0] for l in lines]
## Grab OTU representative seqs in membership file from dereplicated fasta
## and write to output
with open(otu_seqs_fn, 'w') as out:
for record in util.iter_fst(fasta_derep):
sid = record[0][1:]
seq = record[1]
if sid in otu_reps:
out.write('>dbotu' + sid + '\n' + seq + '\n')
return None
def extract_dbotu_otu_seqs(membershipfn, fasta_derep, otu_seqs_fn):
"""
Parameters
----------
membershipfn membership filename, made by dbotu.call_otus
has OTU representative seq IDs in first column, and
OTU member seq IDs in rest of row
fatas_derep fasta dereplicated; sequence IDs should match those
in membershipfn
out_seqs_fn output fasta file to write representative seqs to
"""
## Parse membership file
with open(membershipfn, 'r') as f:
lines = f.readlines()
otu_reps = [l.split('\t')[0] for l in lines]
## Grab OTU representative seqs in membership file from dereplicated fasta
## and write to output
with open(otu_seqs_fn, 'w') as out:
for record in util.iter_fst(fasta_derep):
sid = record[0][1:]
seq = record[1]
if sid in otu_reps:
out.write('>dbotu' + sid + '\n' + seq + '\n')
return None
def load_db(self):
# Load existing SeqDB (if exists)
if os.path.exists(self.fn):
for tag, seq in util.iter_fst(self.fn):
otu, size = re.search('>(.*);size=(\d+)', tag).groups()
self.db[int(otu)] = seq
self.size[int(otu)] = int(size)
return self
def parse_files(f, q):
"""
Parse fasta and quality files, f and q
"""
sids = []
seqs = []
quals = []
for sid, seq in util.iter_fst(f):
sids.append(sid[1:])
seqs.append(seq)
for _, qual in util.iter_fst(q):
quals.append(qual.split(' '))
if len(sids) != len(seqs) != len(quals):
raise ValueError('fasta and quality files are not the same length!')
return sids, seqs, quals
def dist(fasta):
data = []
for i,record in enumerate(util.iter_fst(fasta)):
sid, seq = record[:2]
logfreq = np.log10(float(sid[1:]))
data.append(logfreq)
if i > 100000:
break
data = np.array(data)
np.savetxt('test100000.out', data, delimiter = '\t')
def dist(fasta):
data = []
for i, record in enumerate(util.iter_fst(fasta)):
sid, seq = record[:2]
logfreq = np.log10(float(sid[1:]))
data.append(logfreq)
if i > 100000:
break
data = np.array(data)
np.savetxt('test100000.out', data, delimiter='\t')
def parse_index_file(index_fn, format='fasta'):
# Map FASTQ sequences to their barcodes
s2b = {} # maps sequences to barcodes
# Case 1: index file is FASTA format
if format=='fasta':
for [s,b] in util.iter_fst(index_fn):
s2b[s] = b
# Case 2: index file is tab-delimited
elif format=='tab':
for line in open(index_fn):
[s,b] = line.rstrip().split()
s2b[s] = b
return s2b
def parse_index_file(index_fn, format='fasta'):
# Map FASTQ sequences to their barcodes
s2b = {} # maps sequences to barcodes
# Case 1: index file is FASTA format
if format == 'fasta':
for [s, b] in util.iter_fst(index_fn):
s2b[s] = b
# Case 2: index file is tab-delimited
elif format == 'tab':
for line in open(index_fn):
[s, b] = line.rstrip().split()
s2b[s] = b
return s2b
def Freq_calculate(fasta, k, l, n, outfile):
# Open the fasta file
fn = fasta
f = open(outfile, 'w')
for record in util.iter_fst(fn):
sid, seq = record[:2]
C = float(sid[1:])
l = float(l)
n = float(n)
k = float(k)
freq = C / ((l - k + 1) * n)
#q = '< k:'+str(k)+' l:'+str(l)+' n:'+str(n)+' C:'+str(C)+' Freq='+str(freq)+'\n'+seq+'\n'
q = '<' + str(freq) + '\n' + seq + '\n'
f.write(q)
def Freq_calculate(fasta, k, l, n, outfile):
# Open the fasta file
fn = fasta
f = open(outfile,'w')
for record in util.iter_fst(fn):
sid, seq = record[:2]
C = float(sid[1:])
l = float(l)
n = float(n)
k = float(k)
freq = C/((l-k+1)*n)
#q = '< k:'+str(k)+' l:'+str(l)+' n:'+str(n)+' C:'+str(C)+' Freq='+str(freq)+'\n'+seq+'\n'
q = '<'+str(freq)+'\n'+seq+'\n'
f.write(q)
def Freq_calculate(fasta, k, l, n, outfile):
# Open the fasta file
fn = fasta
f = open(outfile, 'w')
for record in util.iter_fst(fn):
sid, seq = record[:2]
C = float(sid[1:])
l = float(l)
n = float(n)
k = float(k)
freq = C / ((l - k + 1) * n)
if np.log10(freq) > -8.5:
q = '>' + str(freq) + '\n' + seq + '\n'
f.write(q)
def load_db(fn, trim_len):
# Load OTU database (otu id -> sequence)
if not fn:
return {}
db = {}
for [sid, seq] in util.iter_fst(fn):
sid = int(sid)
if trim_len:
if len(seq) >= trim_len:
seq = seq[:trim_len]
else:
continue
db[sid] = seq
return db
def Freq_calculate(fasta, k, l, n, outfile):
# Open the fasta file
fn = fasta
f = open(outfile,'w')
for record in util.iter_fst(fn):
sid, seq = record[:2]
C = float(sid[1:])
l = float(l)
n = float(n)
k = float(k)
freq = C/((l-k+1)*n)
if np.log10(freq) > -8.5:
q = '>'+str(freq)+'\n'+seq+'\n'
f.write(q)
def parse_barcodes_file(map_fn, format='fasta', rc=False):
# Map barcodes to samples
b2s = {} # maps barcodes to samples
# Case 1: barcodes file is FASTA format
if format == 'fasta':
for [s, b] in util.iter_fst(map_fn):
if rc == True:
seq = reverse_complement(s)
b2s[b] = s
# Case 2: barcodes file is tab-delimited
elif format == 'tab':
for line in open(map_fn):
[s, b] = line.rstrip().split()
if rc == True:
b = reverse_complement(b)
b2s[b] = s
# Return map of barcodes to samples
return b2s
def remove_size_from_headers(raw_derep_in, raw_derep_out):
"""
Rename sequences in raw_dereplicated.fasta from 'seq;size=204' to 'seq'.
Parameters
----------
raw_derep_in fasta file with dereplicated, trimmed reads
This is the output from dereplicate_and_sort() which calls
3.dereplicate.py.
raw_derep_out file name for output file with renamed headers
"""
with open(raw_derep_out, 'w') as out:
for record in util.iter_fst(raw_derep_in):
sid = record[0].split(';')[0]
seq = record[1]
out.write(sid + '\n' + seq + '\n')
return None
def parse_barcodes_file(map_fn, format='fasta', rc=False):
# Map barcodes to samples
b2s = {} # maps barcodes to samples
# Case 1: barcodes file is FASTA format
if format == 'fasta':
for [s,b] in util.iter_fst(map_fn):
if rc == True:
seq = reverse_complement(s)
b2s[b] = s
# Case 2: barcodes file is tab-delimited
elif format == 'tab':
for line in open(bcode_fn):
[s,b] = line.rstrip().split()
if rc == True:
b = reverse_complement(b)
b2s[b] = s
# Return map of barcodes to samples
return b2s
def remove_size_from_headers(raw_derep_in, raw_derep_out):
"""
Rename sequences in raw_dereplicated.fasta from 'seq;size=204' to 'seq'.
Parameters
----------
raw_derep_in fasta file with dereplicated, trimmed reads
This is the output from dereplicate_and_sort() which calls
3.dereplicate.py.
raw_derep_out file name for output file with renamed headers
"""
with open(raw_derep_out, 'w') as out:
for record in util.iter_fst(raw_derep_in):
sid = record[0].split(';')[0]
seq = record[1]
out.write(sid + '\n' + seq + '\n')
return None
def Create_table(inlist):
# initiate dictionary
dict = {}
# read in each file:
for i, fasta in enumerate(open(inlist)):
fastafile = fasta[:-1]
print i
for item in dict:
dict[item] += [-20]
for record in util.iter_fst(fastafile):
sid, seq = record[:2]
sfreq = float(sid[1:])
if dict.has_key(seq) == False:
dict[seq] = [-20]*i + [sfreq]
else:
dict[seq][-1]= sfreq
# print dict
return dict
def Create_table(inlist):
# initiate dictionary
dict = {}
# read in each file:
for i, fasta in enumerate(open(inlist)):
fastafile = fasta[:-1]
print i
for item in dict:
dict[item] += [-20]
for record in util.iter_fst(fastafile):
sid, seq = record[:2]
sfreq = float(sid[1:])
if dict.has_key(seq) == False:
dict[seq] = [-20] * i + [sfreq]
else:
dict[seq][-1] = sfreq
# print dict
return dict
def fasta2table(fastaIn, tableOut):
# Converts a set of fasta sequences into a table format with the first column
# corresponding to label lines beginning with > and the second column to the sequence.
keep = {}
seqs = {}
for [otu_number, seq] in util.iter_fst(fastaIn):
otu_number = otu_number[1:]
keep[otu_number] = 1
seqs[otu_number] = seq
# Sort and organize into a new tab-delimited file with OTU_ID and Sequence as columns
fid = open(tableOut,'w')
headerline = "OTU_ID" + '\t' + 'Sequence'
fid.write(headerline+'\n')
for otu_number in keep:
line = str(otu_number) + '\t' + seqs[otu_number]
fid.write(line+'\n')
fid.close()
return None
def parse_index_file(index_fn, format='fasta'):
# Map FASTQ sequences to their barcodes
s2b = {} # maps sequences to barcodes
# Case 1: index file is FASTA format
if format=='fasta':
for [s,b] in util.iter_fst(index_fn):
# note: I'm pretty sure this won't work for downstream, because you need
# to remove the first character from sequence ID
s2b[s] = b
# Case 2: index file is tab-delimited
elif format=='tab':
for line in open(index_fn):
[s,b] = line.rstrip().split()
s2b[s] = b
# Case 3: index file is FASTQ format
elif format=='fastq':
for [s,b,_,_] in util.iter_fsq(index_fn):
# If sequence ID has :Y:0: thing at the end (standard Illumina format), remove it
# For this kind of fastq line: @SL-MAJ:AY3TB170104:AY3TB:1:1101:10000:7854 :N:0:
s = s.rsplit(' ', 1)[0]
s2b[s[1:]] = b
return s2b
def parse_index_file(index_fn, format='fasta'):
# Map FASTQ sequences to their barcodes
s2b = {} # maps sequences to barcodes
# Case 1: index file is FASTA format
if format == 'fasta':
for [s, b] in util.iter_fst(index_fn):
# note: I'm pretty sure this won't work for downstream, because you need
# to remove the first character from sequence ID
s2b[s] = b
# Case 2: index file is tab-delimited
elif format == 'tab':
for line in open(index_fn):
[s, b] = line.rstrip().split()
s2b[s] = b
# Case 3: index file is FASTQ format
elif format == 'fastq':
for [s, b, _, _] in util.iter_fsq(index_fn):
# If sequence ID has :Y:0: thing at the end (standard Illumina format), remove it
# For this kind of fastq line: @SL-MAJ:AY3TB170104:AY3TB:1:1101:10000:7854 :N:0:
s = s.rsplit(' ', 1)[0]
s2b[s[1:]] = b
return s2b
import argparse, util
parser = argparse.ArgumentParser()
parser.add_argument('--fst', default='input fasta file')
parser.add_argument('--otus', default='list of otus')
args = parser.parse_args()
otus = [line.rstrip() for line in open(args.otus)]
for [sid, seq] in util.iter_fst(args.fst):
if sid in otus:
print '>%s\n%s' %(sid, seq)
"GGA": "G",
"TGG": "W",
"CGG": "R",
"AGG": "R",
"GGG": "G"
}
def get_codons(nt):
if len(nt) % 3 != 0:
quit('error: len(nt) not divisible by 3')
for i in range(int(len(nt) / 3)):
beg = i * 3
end = beg + 3
yield nt[beg:end]
def translate(nt):
nt = nt.upper()
aa = ''
for codon in get_codons(nt):
aa += codon_table[codon]
return aa
if __name__ == '__main__':
import sys
for record in util.iter_fst(sys.argv[1]):
record[1] = translate(record[1])
print('\n'.join(record))
help='print command',
default=False,
action='store_true')
args = parser.parse_args()
# auto settings
if args.lax == True:
args.b1 = .5
args.b2 = .5
args.b3 = 10
args.b4 = 5
args.b5 = 'all'
args.cut = 25
# fix arguments
n = len([record for record in util.iter_fst(args.aln)])
args.b1 = int(args.b1 * n) + 1
args.b2 = int(args.b2 * n) + 1
args.b5 = {'none': 'N', 'half': 'H', 'all': 'A'}[args.b5]
# encode gblocks input
gmap = {}
temp = open('%s.temp.aln' % (args.aln), 'w')
print('writing alignmnet to %s.temp.aln' % (args.aln))
for i, record in enumerate(util.iter_fst(args.aln)):
old = record[0]
new = 'seq%d' % (i)
gmap[new] = old
record[0] = '>%s' % (new)
temp.write('\n'.join(record) + '\n')
temp.close()
cds = sorted(translate.codon_table.keys())
aas = sorted('G A L M F W K Q E S P V I C Y H R N D T'.split())
alphabet = nts + cds + aas
header = ['gene'] + ['count_nt_%s' %(li) for li in nts] + ['count_cd_%s' %(li) for li in cds] + ['count_aa_%s' %(li) for li in aas] + \
['freq_nt_%s' %(li) for li in nts] + ['freq_cd_%s' %(li) for li in cds] + ['freq_aa_%s' %(li) for li in aas]
print('\t'.join(header))
# read sequence id map
smap = {}
if args.map:
for line in open(args.map):
line = line.rstrip().split()
smap[line[0]] = line[1]
# iterate over sequences
for record in util.iter_fst(args.fst):
sid, seq = record
if len(seq) % 3 != 0:
continue
# map sequence ids
sid = sid.split()[0][1:]
if args.map:
if sid in smap:
sid = smap[sid]
else:
continue
# count fna features
# ------------------
args = parser.parse_args()
filemap = args.fmap
with open(filemap, 'r') as f:
lines = f.readlines()
lines = [line.strip().split('\t') for line in lines]
sids = [line[1] for line in lines]
fastas = [line[0] for line in lines]
## Relabel sequences in individual fastas. Save each one as *.sb
## Also concatenate all of these fastas into one large fasta, named myDataset.raw_concat.fasta
concat_fasta = args.dataset + '.raw_concat.fasta'
with open(concat_fasta, 'w') as concat:
for fasta, newsid in zip(fastas, sids):
new_fasta = fasta + '.sb'
counter = 0
with open(new_fasta, 'w') as f:
print(new_fasta)
for oldsid, seq in util.iter_fst(fasta):
counter += 1
f.write('>' + newsid + '_' + str(counter) + '\n')
f.write(seq + '\n')
# @Thomas: I think concatenating at the same time as relabeling will be fastest, but I'm not sure!
concat.write('>' + newsid + '_' + str(counter) + '\n')
concat.write(seq + '\n')
"""
Relabel sequences in *.raw_trimmed.fasta to have
datasetID--sampleID_N
"""
import os
import argparse
import util
parser = argparse.ArgumentParser()
parser.add_argument('trimmed_dir',
help='directory with *.raw_trimmed.fasta files')
args = parser.parse_args()
files = [
os.path.join(args.trimmed_dir, i) for i in os.listdir(args.trimmed_dir)
if i.endswith('.raw_trimmed.fasta')
]
for fname in files:
dataset = fname.split('/')[-1].split('.')[0]
with open(fname + '.relabeled', 'w') as fnew:
for sid, seq in util.iter_fst(fname):
sid = '>' + dataset + '--' + sid[1:]
fnew.write('\n'.join([sid, seq]) + '\n')
help='Input fasta sequences (optional)',
default='')
parser.add_argument('--map', help='Input mapping file', required=True)
parser.add_argument('--min_count', help='Minimum read count', type=int)
parser.add_argument('--min_samples',
help='Minimum number of samples',
type=int)
parser.add_argument('--out', help='Output counts matrix')
# Parse command line arguments
args = parser.parse_args()
# Load valid fst seqs
keep = {}
if args.fst:
for [otu, seq] in util.iter_fst(args.fst):
otu = otu[1:]
keep[otu] = 1
# Keep track of samples and otus
samples = {}
otus = {}
# For every line in the mapping file
for line in open(args.map):
# Load otu name and table of sample counts
otu, table = line.rstrip().split('\t')
if len(keep) > 0 and otu not in keep:
continue
entries = table.split(' ')
count = sum(
import argparse
import util
# parse args
parser = argparse.ArgumentParser()
parser.add_argument('-f', help='FASTA file')
parser.add_argument('-q', help='FASTQ file')
parser.add_argument('-s', help='Subset ids')
args = parser.parse_args()
# load subset
subset = [line.rstrip() for line in open(args.s)]
# get iterator
iter_seq = ''
if args.f:
iter_seq = util.iter_fst(args.f)
if args.q:
iter_seq = util.iter_fsq(args.q)
# subset file
for record in iter_seq:
sid = record[0][1:].split(';')[0]
if sid in subset:
print '\n'.join(record)
parser.add_argument('--minlen', help='Minimum length', type=int, default=0)
parser.add_argument('--num', help='Number to keep', type=int, default=0)
parser.add_argument('--prefix', help='Prefix to add', type=str, default='')
parser.add_argument('--prefix_sep',
help='Prefix separator',
type=str,
default='.')
parser.add_argument('--debug',
help='Debug mode',
action='store_true',
default=False)
args = parser.parse_args()
# get iterator
if args.fst:
iter_seq = util.iter_fst(args.fst)
elif args.fsq:
iter_seq = util.iter_fsq(args.fsq)
elif args.FST:
iter_seq = util.iter_fst(sys.stdin)
elif args.FSQ:
iter_seq = util.iter_fsq(sys.stdin)
else:
quit('error: must specify fst, fsq, FST, or FSQ')
# initialize variables
keep = {}
remove = {}
# load IDs/coordinates to keep
if args.keep:
import util, sys
fn = sys.argv[1]
k = int(sys.argv[2])
for [sid, seq] in util.iter_fst(fn):
if len(seq) >= k:
print '>%s\n%s' %(sid, seq[:k])
import util
parser = argparse.ArgumentParser()
parser.add_argument('--fst', help='Input fasta sequences (optional)', default='')
parser.add_argument('--map', help='Input mapping file', required=True)
parser.add_argument('--min_count', help='Minimum read count', type=int)
parser.add_argument('--min_samples', help='Minimum number of samples', type=int)
parser.add_argument('--out', help='Output counts matrix')
# Parse command line arguments
args = parser.parse_args()
# Load valid fst seqs
keep = {}
if args.fst:
for [otu, seq] in util.iter_fst(args.fst):
otu = otu[1:]
keep[otu] = 1
# Keep track of samples and otus
samples = {}
otus = {}
# For every line in the mapping file
for line in open(args.map):
# Load otu name and table of sample counts
otu, table = line.rstrip().split('\t')
if len(keep) > 0 and otu not in keep:
continue
entries = table.split(' ')
count = sum([int(entry.split(':')[1]) >= args.min_count for entry in entries])
print('Parsing dereplication map: {}'.format(args.map_file))
seq_sizes = {}
with open(args.map_file, 'r') as f:
lines = f.readlines()
for line in lines:
line = line.strip().split('\t')
seqID = line[0]
total_size = sum([int(i.split('size=')[1].split(':1')[0]) for i in line[1].split(' ')])
seq_sizes[seqID] = total_size
## Read in the entire fasta file into a dict {seqID: sequence}
print('Reading fasta file: {}'.format(args.fasta_in))
fasta = {}
for sid, seq in util.iter_fst(args.fasta_in):
# sid in the fasta is something like >444;size=8
# sid.split(';')[0][1:] returns 444, which is a key in seq_sizes
sid = sid.split(';')[0][1:]
newsid = '>' + sid + ';size=' + str(seq_sizes[sid])
fasta[sid] = {}
fasta[sid]['new_sid'] = newsid
fasta[sid]['seq'] = seq
## Get list of sequence IDs in descending size (i.e. largest first)
ordered_seqs = sorted(seq_sizes, key=lambda k: seq_sizes[k], reverse=True)
## Write new fasta file in descending size
print('Writing sorted and relabled fasta: {}'.format(args.fasta_out))
with open(args.fasta_out, 'w') as f:
f.write('\n'.join([fasta[s]['new_sid'] + '\n' + fasta[s]['seq'] for s in ordered_seqs]))