#!/usr/bin/env python3 # -*- 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')