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# -*- coding: utf-8 -*-
import pandas as pd
import os
from tqdm import tqdm
from utils.utils import (make_orig_folder,
move_file_to_originals,
rename_file_in_place)
def find_repeats(seed_alignment_dir: str):
"""
find names and sequences of repeats WITHIN and ACROSS seed files
Will iterate through every line of every seed file, so this might
take a while...
inputs:
-------
- seed_alignment_dir (str): where the .seed files are
returns:
--------
(None)
outputs:
--------
- repeats_ACROSS_families.tsv: names and sequences of repeats across
multiple pfams
- repeats_ACROSS_families.tsv: names and sequences of repeats within
single pfam
"""
### a container for all the within-family repeats
# key = prot seq (ungapped)
# value = pfam/seqname
RAW_repeats = {}
seen_seqs = set()
### scan all msa files for repeats
for idx,filename in tqdm(enumerate(os.listdir('seed_alignments'))):
if filename.endswith('.seed'):
pfam_name = filename.replace('.seed','')
with open(f'./seed_alignments/{filename}','r',
encoding='latin') as f:
for line in f:
if not line.startswith('#'):
samp_name, gapped_seq = line.strip().split()
seq = gapped_seq.replace('.','')
valname = f'{pfam_name}:{samp_name}'
# check if ungapped sequence is seen WITHIN this MSA
if seq in seen_seqs:
RAW_repeats[seq].append(valname)
else:
RAW_repeats[seq] = [valname]
seen_seqs.add(seq)
### remove anything that doesn't repeat
repeats = {}
for key, val_lst in RAW_repeats.items():
if len(val_lst) > 1:
repeats[key] = val_lst
# remove the raw dict and the intermediate set
del RAW_repeats, seen_seqs
### keep repeats across families in their own dictionary
### otherwise, place in repeats within familities
repeats_within_fams = {}
repeats_across_fams = {}
for key, val_lst in repeats.items():
pfams_in_lst = set()
for entry in val_lst:
pfam, _ = entry.split(':')
pfams_in_lst.add(pfam)
if len(pfams_in_lst) > 1:
repeats_across_fams[key] = val_lst
else:
repeats_within_fams[key] = val_lst
del repeats
### separately output these
if len(repeats_within_fams) > 0:
with open('repeats_WITHIN_families.tsv', 'w') as g:
for key, val_lst in repeats_within_fams.items():
pfam_name = val_lst[0].split(':')[0]
val_lst_without_pfam = ';'.join([elem.split(':')[1] for elem in val_lst])
g.write(f'{pfam_name}\t{val_lst_without_pfam}\t{key}\n')
if len(repeats_across_fams) > 0:
with open('repeats_ACROSS_families.tsv', 'w') as g:
for key, val_lst in repeats_across_fams.items():
to_write = ';'.join(val_lst)
g.write(f'{to_write}\t{key}\n')
def parse_within_families_file():
"""
read "repeats_WITHIN_families" to figure out which repeats to remove
inputs:
-------
(None)
returns:
--------
- to_remove_dict: dictionary of pfam values to remove
"""
# don't do anything if you don't generate this file
if 'repeats_WITHIN_families.tsv' not in os.listdir():
return dict()
all_pfams = []
all_samp_names = []
with open('repeats_WITHIN_families.tsv','r') as f:
for line in f:
pfam, samp_names, _ = line.strip().split('\t')
all_pfams.append(pfam)
all_samp_names.append(samp_names.split(';'))
# build dictionary from lists
to_remove_dict = {}
for i in range(len(all_pfams)):
pfam = all_pfams[i]
all_duplicates = all_samp_names[i]
# only keep the first instance
remove_samps = all_duplicates[1:]
if pfam in to_remove_dict.keys():
to_remove_dict[pfam] = to_remove_dict[pfam] + remove_samps
elif pfam not in to_remove_dict.keys():
to_remove_dict[pfam] = remove_samps
return to_remove_dict
def parse_across_families_file():
"""
read "repeats_ACROSS_families" to figure out which repeats to remove
inputs:
-------
(None)
returns:
--------
- to_remove_dict: dictionary of pfam values to remove
"""
# don't do anything if you don't generate this file
if 'repeats_ACROSS_families.tsv' not in os.listdir():
return dict()
to_remove_dict = {}
with open('repeats_ACROSS_families.tsv', 'r') as f:
for line in f:
line = line.strip().split('\t')[0]
raw_lst = line.split(';')
# only keep the first instance
remove_samps = raw_lst[1:]
for entry in remove_samps:
pfam, sample = entry.split(':')
if pfam not in to_remove_dict.keys():
to_remove_dict[pfam] = [sample]
elif pfam in to_remove_dict.keys():
to_remove_dict[pfam].append(sample)
return to_remove_dict
def remove_samples(seed_alignment_dir: str,
to_remove_dict: dict):
"""
given a list of pfams and samples to remove, trim samples from seed files
inputs:
-------
- seed_alignment_dir (str): where the .seed files are
- to_remove_dict: samples to remove from every pfam
> keys: pfam
> values: list of samples to remove
returns:
--------
(None)
outputs:
--------
- de-duplicated pfam files, new 'originals' folder
"""
### quit function, if there's nothing to be done
if len(to_remove_dict) == 0:
print('No duplicates found')
return
# make a folder to store originals, if it doesn't already exist
make_orig_folder(in_dir = seed_alignment_dir)
### start iterating through
for pfam, to_remove in tqdm(to_remove_dict.items()):
to_remove = set(to_remove)
# get the filenames
msa_file = f'{pfam}.seed'
assert msa_file in os.listdir(seed_alignment_dir), f'{msa_file} missing!'
# open the msa and remove duplicate sequences
with open(f'./{seed_alignment_dir}/DEDUPED_{msa_file}','w') as g_new:
with open(f'./{seed_alignment_dir}/{msa_file}','r') as f_msa:
for line in f_msa:
# filter
if line.startswith('#'):
g_new.write(line)
else:
this_samp_name = line.split()[0]
if this_samp_name not in to_remove:
g_new.write(line)
# move the original file, if it's not already there
move_file_to_originals(filename = msa_file,
in_dir = seed_alignment_dir)
# rename the new version (will overwrite original, if that's left
# in the folder)
rename_file_in_place(filename = msa_file,
in_dir = seed_alignment_dir,
prefix = 'DEDUPED')
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