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adding exchange headers mode
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@Eslam-Samir-Ragab
Eslam-Samir-Ragab authored Sep 24, 2018
1 parent 4396960 commit ce80439
Showing 1 changed file with 95 additions and 57 deletions.
152 changes: 95 additions & 57 deletions sddc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,46 +17,55 @@ def parsing_file(filename):
return names, sequences


def file_writer_original_order(output_file, starting_names, starting_sequences, curated_sequences):
def get_new_names(filename):
# reading the csv file for new names
import csv
with open(filename, mode='r') as exchange:
reader = csv.reader(exchange)
new_names_dict = {str(row[0]): str(row[1]) for row in reader}
return new_names_dict


def file_writer_original_order(out_file, starting_names, starting_sequences, curated_sequences):
# write function by original order
print('\n-------\nfiltered sequences = %d from %d starting sequences\nresulting sequence = %d sequences' % (
len(starting_names) - len(curated_sequences), len(starting_names), len(curated_sequences)))
indeces = [starting_sequences.index(curated_sequences[i]) for i in range(len(curated_sequences))]
indeces.sort()
with open(output_file, 'w') as f:
name = starting_names[indeces[0]]
len(starting_names) - len(curated_sequences), len(starting_names), len(curated_sequences)))
indices = [starting_sequences.index(curated_sequences[i]) for i in range(len(curated_sequences))]
indices.sort()
with open(out_file, 'w') as out:
name = starting_names[indices[0]]
curated_names = [name]
f.write('%s\n%s' % (name, starting_sequences[indeces[0]]))
for i in indeces[1:]:
out.write('%s\n%s' % (name, starting_sequences[indices[0]]))
for i in indices[1:]:
name = starting_names[i]
curated_names.append(name)
f.write('\n%s\n%s' % (name, starting_sequences[i]))
out.write('\n%s\n%s' % (name, starting_sequences[i]))
deleted = list(set([name for name in starting_names if name not in curated_names]))
if len(deleted) > 0:
with open('names_of_deleted.txt', 'w') as f:
f.write('%s\n' % deleted[0])
with open('names_of_deleted.txt', 'w') as out:
out.write('%s\n' % deleted[0])
for i in range(1, len(deleted)):
f.write('\n%s\n' % deleted[i])
out.write('\n%s\n' % deleted[i])


def file_writer(output_file, starting_names, starting_sequences, curated_sequences):
def file_writer(out_file, starting_names, starting_sequences, curated_sequences):
# write function
print('\n-------\nfiltered sequences = %d from %d starting sequences\nresulting sequence = %d sequences' % (
len(starting_names) - len(curated_sequences), len(starting_names), len(curated_sequences)))
with open(output_file, 'w') as f:
len(starting_names) - len(curated_sequences), len(starting_names), len(curated_sequences)))
with open(out_file, 'w') as out:
name = starting_names[starting_sequences.index(curated_sequences[0])]
curated_names = [name]
f.write('%s\n%s' % (name, curated_sequences[0]))
out.write('%s\n%s' % (name, curated_sequences[0]))
for i in range(1, len(curated_sequences)):
name = starting_names[starting_sequences.index(curated_sequences[i])]
curated_names.append(name)
f.write('\n%s\n%s' % (name, curated_sequences[i]))
out.write('\n%s\n%s' % (name, curated_sequences[i]))
deleted = list(set([name for name in starting_names if name not in curated_names]))
if len(deleted) > 0:
with open('names_of_deleted.txt', 'w') as f:
f.write('%s\n' % deleted[0])
with open('names_of_deleted.txt', 'w') as out:
out.write('%s\n' % deleted[0])
for i in range(1, len(deleted)):
f.write('\n%s\n' % deleted[i])
out.write('\n%s\n' % deleted[i])


def cleaner(_list):
Expand All @@ -72,12 +81,12 @@ def kmer_gen(sequence, k, start):
return kmer


def remover_by_seq(start_file, remove_file, database):
def remover_by_seq(start_file, filtration_file, sequence_type):
# remover (by sequences)
starting_names, starting_sequences = parsing_file(start_file)
removing_sequences = set(parsing_file(remove_file)[1])
removing_sequences = set(parsing_file(filtration_file)[1])
if len(starting_sequences) < 1 or len(removing_sequences) < 1:
sys.exit("\n\nError in your input file or filteration file or incorrect filteration mode !\n")
sys.exit("\n\nError in your input file or filtration file or incorrect filtration mode !\n")

editing = set(starting_sequences[:])
common = editing & removing_sequences
Expand All @@ -91,7 +100,7 @@ def remover_by_seq(start_file, remove_file, database):
if kmer in seq:
if comparing in seq:
editing[i] = ''
elif database == 'n' and reverse_complement(kmer) in seq:
elif sequence_type == 'n' and reverse_complement(kmer) in seq:
if reverse_complement(comparing) in seq:
editing[i] = ''
editing = cleaner(editing)
Expand All @@ -101,64 +110,64 @@ def remover_by_seq(start_file, remove_file, database):
file_writer(output_file, starting_names, starting_sequences, editing)


def remover_by_name(start_file, filter_file, filteration):
def remover_by_name(start_file, filter_file, filtration):
# remover (by names)
with open(filter_file, 'r') as f:
lines = f.readlines()
filter_names = [line.rstrip() for line in lines if '>' in line]
with open(filter_file, 'r') as filter_file:
lines = filter_file.readlines()
filter_names = [row.rstrip() for row in lines if '>' in row]

starting_names, starting_sequences = parsing_file(start_file)
data = [(starting_names[i] + '&&' + starting_sequences[i]) for i in range(len(starting_names))]
data = list(set(data))
if filteration == 'exclusive':
curated_data = [line for line in data for filter_name in filter_names if filter_name not in line]
elif filteration == 'inclusive':
curated_data = [line for line in data for filter_name in filter_names if filter_name in line]
if filtration == 'exclusive':
curated_data = [row for row in data for filter_name in filter_names if filter_name not in row]
else:
curated_data = [row for row in data for filter_name in filter_names if filter_name in row]
print('\n-------\nfiltered sequences = %d from %d starting sequences\nresulting sequence = %d sequences' % (
len(starting_names) - len(curated_data), len(starting_names), len(curated_data)))
with open(output_file, 'w') as f:
lines_to_write = [line.split('&&') for line in curated_data]
f.write('%s\n%s' % (lines_to_write[0][0], lines_to_write[0][1]))
len(starting_names) - len(curated_data), len(starting_names), len(curated_data)))
with open(output_file, 'w') as filter_file:
lines_to_write = [row.split('&&') for row in curated_data]
filter_file.write('%s\n%s' % (lines_to_write[0][0], lines_to_write[0][1]))
for i in range(1, len(lines_to_write)):
f.write('\n%s\n%s' % (lines_to_write[i][0], lines_to_write[i][1]))
filter_file.write('\n%s\n%s' % (lines_to_write[i][0], lines_to_write[i][1]))


def remover_by_keyword(start_file, filter_file, filteration):
# remover (by kewords in Fasta headers)
def remover_by_keyword(start_file, filter_file, filtration):
# remover (by keywords in FASTA headers)
filter_names = []
with open(filter_file, 'r') as f:
for line in f:
items = line.rstrip().split(",")
for row in f:
items = row.rstrip().split(",")
filter_names += items
filter_names = list(set(filter_names))
starting_names, starting_sequences = parsing_file(start_file)
data = [(starting_names[i] + '&&' + starting_sequences[i]) for i in range(len(starting_names))]
if not original_order:
data = list(set(data))
if filteration == 'exclusive':
if filtration == 'exclusive':
for i in range(len(data)):
for filter_name in filter_names:
if filter_name in data[i]:
data[i] = ''
break
data = cleaner(data)
print('\n-------\nfiltered sequences = %d from %d starting sequences\nresulting sequence = %d sequences' % (
len(starting_names) - len(data), len(starting_names), len(data)))
len(starting_names) - len(data), len(starting_names), len(data)))
with open(output_file, 'w') as f:
lines_to_write = [line.split('&&') for line in data]
lines_to_write = [row.split('&&') for row in data]
f.write('%s\n%s' % (lines_to_write[0][0], lines_to_write[0][1]))
for i in range(1, len(lines_to_write)):
f.write('\n%s\n%s' % (lines_to_write[i][0], lines_to_write[i][1]))
elif filteration == 'inclusive':
elif filtration == 'inclusive':
curated_data = []
for line in data:
for row in data:
for filter_name in filter_names:
if (filter_name in line) and (line not in curated_data):
curated_data.append(line)
if (filter_name in row) and (row not in curated_data):
curated_data.append(row)
print('\n-------\nfiltered sequences = %d from %d starting sequences\nresulting sequence = %d sequences' % (
len(starting_names) - len(curated_data), len(starting_names), len(curated_data)))
with open(output_file, 'w') as f:
lines_to_write = [line.split('&&') for line in curated_data]
lines_to_write = [row.split('&&') for row in curated_data]
f.write('%s\n%s' % (lines_to_write[0][0], lines_to_write[0][1]))
for i in range(1, len(lines_to_write)):
f.write('\n%s\n%s' % (lines_to_write[i][0], lines_to_write[i][1]))
Expand Down Expand Up @@ -194,7 +203,8 @@ def derep_longest(start_file, sequence_type):
file_writer(output_file, starting_names, starting_sequences, editing)


def derep_optimum(start_file, protein_length): # dereplication (optimum approach)
def derep_optimum(start_file, protein_length):
# dereplication (optimum approach)
starting_names, starting_sequences = parsing_file(start_file)
if len(starting_sequences) < 1:
sys.exit("\n\nError in your input file !\n")
Expand Down Expand Up @@ -230,13 +240,33 @@ def derep_optimum(start_file, protein_length): # dereplication (optimum approac
else:
file_writer(output_file, starting_names, starting_sequences, editing)

# begining of the code !!!
# beginning of the code !!!


def exchange_names(start_file, exchange_file, out_file):
ex_dict = get_new_names(exchange_file)
starting_names, starting_sequences = parsing_file(start_file)
mod_names = "&&".join(starting_names)
for old in ex_dict:
tempo = old
if ">" in tempo:
tempo = tempo.replace(">", "")
mod_names = mod_names.replace(tempo, ex_dict[old])
starting_names = mod_names.split("&&")
with open(out_file, 'w') as out:
out.write('%s\n%s' % (starting_names[0], starting_sequences[0]))
for i in range(1, len(starting_names)):
out.write('\n%s\n%s' % (starting_names[i], starting_sequences[i]))
print('\n-------\nexchanged headers = %d from %d total headers\n' % (len(ex_dict), len(starting_names)))


parser = argparse.ArgumentParser(prog='Sequence Database Dereplicator and Curator (SDDC) program',
usage='\n%(prog)s : dereplicates and/or filter nucleotide and/or protein database from a list of names or sequences (by exact match).\n\n Eslam S.Ibrahim\n\n eslam.ebrahim@pharma.cu.edu.eg')
parser.add_argument('-mode', dest='mode', required=True, choices=['derep', 'filter'],
help='dereplicate your file/files or filter your file from specific sequences or names')
usage='\n%(prog)s : dereplicates and/or filter nucleotide and/or protein database '
'from a list of names or sequences (by exact match).\n\n Eslam S.Ibrahim\n\n '
'eslam.ebrahim@pharma.cu.edu.eg')
parser.add_argument('-mode', dest='mode', required=True, choices=['derep', 'filter', 'exchange_headers'],
help='dereplicate your file/files, filter your file from specific sequences or names, or exchange '
'the FASTA headers')
parser.add_argument('-approach', dest='filter', choices=['inclusive', 'exclusive'], default='exclusive',
help='if you want to filter your file(s) by names or sequences either inclusively or exclusively')
parser.add_argument('-kw', dest='keywords', default=False, action='store_true',
Expand All @@ -246,6 +276,8 @@ def derep_optimum(start_file, protein_length): # dereplication (optimum approac
help='Input file containing your original data to be dereplicated and/or filtered')
parser.add_argument('-flt_file', dest='flt_file',
help='Input file containing your listed names or sequences to be filtered from your original file')
parser.add_argument('-ex_file', dest='ex_file',
help='Exchange file containing the old names to be replaced with the new names in the FASTA format')
parser.add_argument('-flt_by', dest='filter_approach', choices=['seq', 'name'], default='seq',
help='The approach by which you wan your input file to be filtered')
parser.add_argument('-p', dest='database', action='store_const', const='p', help='protein sequences')
Expand All @@ -271,6 +303,7 @@ def derep_optimum(start_file, protein_length): # dereplication (optimum approac
output_file = args.output_file
input_file = args.input_file
remove_file = args.flt_file
ex_file = args.ex_file
filter_approach = args.filter_approach
keywords = args.keywords
database = args.database
Expand Down Expand Up @@ -343,8 +376,13 @@ def derep_optimum(start_file, protein_length): # dereplication (optimum approac
elif mode == 'derep' and not optimum:
derep_longest(input_file, database)

# Finishing !!!
elif mode == "exchange_headers":
exchange_names(input_file, ex_file, output_file)

# Finishing !!!

time_of_calc = time.clock() - start_time
print(time_of_calc, "seconds") # in case if we want the time
print('-------\nThanks for using SDDC\n-------\nfor contact ==> eslam.ebrahim@pharma.cu.edu.eg\n-------')
print(time_of_calc, "seconds")
print(
'-------\nThanks for using SDDC\n-------\nfor contact ==> eslam.ebrahim@pharma.cu.edu.eg\nPlease cite: '
'10.1007/s00284-017-1327-6\n-------')

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