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485 lines
22 KiB
Python
485 lines
22 KiB
Python
# Last updated Jan 2025
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# Authors: Auden Cote-L'Heureux, Mario Ceron-Romero.
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# This script contains the entirety of the contamination loop, an iterative tool to assess
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# and remove contamination based on analyses of single gene trees. This tool allows for the
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# use of one or both of two main methods of contamination assessment informed by tree topology.
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# The first method – “clade-based contamination removal” – is intended for cases when the
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# user is interested in genes present in a group of organisms with multiple representative
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# samples and/or species in the gene trees. For a given set of target taxa, this method identifies
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# robust, monophyletic clades containing those taxa within each gene tree, and removes all other
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# sequences belonging to the group of target taxa. The second available method is 'sister-based
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# contamination removal', where sequences are removed based on their sister relationship to
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# user-specified contaminants. After sequences are removed in each iteration, the loop re-aligns and
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# re-builds each tree excluding all removed sequences, and then repeats a specified number of times
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# (--n_loops). Running in botb of these modes requires the user to input several parameters,
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# which can be found in the manual, and in the 'CL' argument group in utils.py.
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#Dependencies
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import os, sys, re
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from Bio import SeqIO
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import ete3
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import guidance
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import trees
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from statistics import mean
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#Utility function to extract Newick strings from Nexus files.
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def get_newick(fname):
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newick = ''
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for line in open(fname):
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line = line.split(' ')[-1]
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if(line.startswith('(') or line.startswith('tree1=')):
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newick = line.split('tree1=')[-1].replace("'", '').replace('\\', '')
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return newick
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#This function reroots the tree on the largest Ba/Za clade. If there is no prokaryote clade,
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#it roots on the largest Op clade, then Pl, then Am, then Ex, then Sr.
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def reroot(tree):
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#This nested function returns the largest clade of a given taxonomic group
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def get_best_clade(taxon):
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best_size = 0; best_clade = []; seen_leaves = []
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#Traverse all nodes
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for node in tree.traverse('levelorder'):
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#If the node is big enough and not subsumed by a node we've already accepted
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if len(node) >= 3 and len(list(set(seen_leaves) & set([leaf.name for leaf in node]))) == 0:
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leaves = [leaf.name for leaf in node]
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#Create a record of leaves that belong to the taxonomic group
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target_leaves = set()
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for leaf in leaves[::-1]:
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if leaf[:2] in taxon:
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target_leaves.add(leaf[:10])
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leaves.remove(leaf)
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#If this clade is better than any clade we've seen before, grab it
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if len(target_leaves) > best_size and len(leaves) <= 2:
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best_clade = node
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best_size = len(target_leaves)
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seen_leaves.extend([leaf.name for leaf in node])
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return best_clade
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#Get the biggest clade for each taxonomic group (stops once it finds one)
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for taxon in [('Ba', 'Za'), ('Op'), ('Pl'), ('Am'), ('Ex'), ('Sr')]:
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clade = get_best_clade(taxon)
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if len([leaf for leaf in clade if leaf.name[:2] in taxon]) > 3:
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tree.set_outgroup( clade)
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break
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return tree
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#Clade-based contamination removal
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def get_subtrees(args, file):
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newick = get_newick(file)
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tree = ete3.Tree(newick)
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try:
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tree = reroot(tree)
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except:
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print('\nUnable to re-root the tree ' + file + ' (maybe it had only 1 major clade, or an inconvenient polytomy). Skipping this step and continuing to try to grab robust clades from the tree.\n')
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#Reading in clade grabbing exceptions
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exceptions = []
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if args.clade_grabbing_exceptions != None:
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if os.path.isfile(args.clade_grabbing_exceptions):
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exceptions = [line.strip() for line in open(args.clade_grabbing_exceptions)]
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else:
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print('\nError: it looks like you tried to input a clade grabbing exceptions file, but it could not be found.\n')
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exit()
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#Reading clade grabbing rules
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rules_per_clade = []
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if args.clade_grabbing_rules_file != None:
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if os.path.isfile(args.clade_grabbing_rules_file):
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lines = [line.strip().split('\t') for line in open(args.clade_grabbing_rules_file) if len(line.strip().split('\t')) == 5]
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for line in lines:
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if line[4].lower() == 'na':
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rules_per_clade.append({ 'target_taxa' : line[0], 'num_contams' : float(line[1]), 'min_target_presence' : int(line[2]), 'required_taxa' : line[3], 'required_taxa_num' : 0 })
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else:
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rules_per_clade.append({ 'target_taxa' : line[0], 'num_contams' : float(line[1]), 'min_target_presence' : int(line[2]), 'required_taxa' : line[3], 'required_taxa_num' : int(line[4]) })
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else:
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print('\nError: it looks like you tried to input a clade grabbing rules file, but it could not be found.\n')
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exit()
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else:
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rules_per_clade.append({ 'target_taxa' : args.target_taxa, 'num_contams' : args.num_contams, 'min_target_presence' : args.min_target_presence, 'required_taxa' : args.required_taxa, 'required_taxa_num' : args.required_taxa_num })
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#Reformatting rules
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for clade in rules_per_clade:
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if os.path.isfile(clade['target_taxa']):
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try:
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clade['target_taxa'] = [l.strip() for l in open(clade['target_taxa']).readlines() if l.strip() != '']
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except AttributeError:
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print('\nError: invalid "target_taxa" input (' + clade['target_taxa'] + '). This must be a comma-separated list of any number of digits/characters to describe focal taxa (e.g. Sr_ci_S,Am_t), or a file with the extension .txt containing a list of complete or partial taxon codes. All sequences containing the complete/partial code will be identified as belonging to target taxa.\n')
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exit()
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else:
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clade['target_taxa'] = [code.strip() for code in clade['target_taxa'].split(',') if code.strip() != '']
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if clade['required_taxa'] != None:
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if os.path.isfile(clade['required_taxa']):
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try:
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clade['required_taxa'] = [l.strip() for l in open(clade['required_taxa']).readlines() if l.strip() != '']
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except AttributeError:
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print('\nError: invalid "required_taxa" argument. This must be a comma-separated list of any number of digits/characters (e.g. Sr_ci_S,Am_t), or a file with the extension .txt containing a list of complete or partial taxon codes, to describe taxa that MUST be present in a clade for it to be selected (e.g. you may want at least one whole genome).\n')
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else:
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clade['required_taxa'] = [code.strip() for code in clade['required_taxa'].split(',') if code.strip() != '' and code.strip().lower() != 'na']
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clade['target_taxa'] = clade['target_taxa'] + clade['required_taxa']
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else:
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clade['required_taxa'] = []
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#Creating a record of selected subtrees, and all of the leaves in those subtrees
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selected_leaves = []
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#For each set of rules (set of target taxa)
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for clade in rules_per_clade:
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seen_leaves = []
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#Iterating through all nodes in tree, starting at "root" then working towards leaves
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for node in tree.traverse('levelorder'):
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#If a node is large enough and is not contained in an already selected clade
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if len(node) >= clade['min_target_presence'] and len(list(set(seen_leaves) & set([leaf.name for leaf in node]))) == 0:
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leaves = [leaf.name for leaf in node]
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#Accounting for cases where e.g. one child is a contaminant, and the other child is a good clade with 1 fewer than the max number of contaminants
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children_keep = 0
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for child in node.children:
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for code in clade['target_taxa']:
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taken = False
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for leaf in child:
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if leaf.name.startswith(code):
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children_keep += 1
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taken = True
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break
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if taken:
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break
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if children_keep == len(node.children):
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#Creating a record of all leaves belonging to the target/"at least" group of taxa, and any other leaves are contaminants
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target_leaves = set(); at_least_leaves = set(); target_leaves_full_names = []
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for code in clade['target_taxa']:
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for leaf in leaves[::-1]:
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if leaf.startswith(code):
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target_leaves.add(leaf[:10])
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target_leaves_full_names.append(leaf)
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for req in clade['required_taxa']:
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if leaf.startswith(req):
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at_least_leaves.add(leaf[:10])
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break
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leaves.remove(leaf)
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#Grab a clade as a subtree if 1) it has enough target taxa; 2) it has enough "at least" taxa; 3) it does not have too many contaminants
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if len(target_leaves) >= clade['min_target_presence'] and len(at_least_leaves) >= clade['required_taxa_num'] and ((clade['num_contams'] < 1 and len(leaves) <= clade['num_contams'] * len(target_leaves)) or len(leaves) <= clade['num_contams']):
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selected_leaves.extend(target_leaves_full_names)
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seen_leaves.extend([leaf.name for leaf in node])
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all_clades = [clade for group in rules_per_clade for clade in group['target_taxa']]
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seqs2keep = [leaf.name for leaf in tree if leaf.name in selected_leaves or not any([leaf.name.startswith(clade) for clade in all_clades]) or any([leaf.name.startswith(ex) for ex in exceptions])]
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return seqs2keep
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#Sisters-based contamination removal
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def get_sisters(args, file, sister_contam_per_tax, subsister_contam_per_tax):
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seqs2remove = []
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#Read the tree using ete3 and reroot it using the above function
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newick = get_newick(file)
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tree = ete3.Tree(newick)
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try:
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tree = reroot(tree)
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except:
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print('\nUnable to re-root the tree ' + file + ' (maybe it had only 1 major clade, or an inconvenient polytomy). Skipping this step and continuing to try to grab robust clades from the tree.\n')
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mean_bl = mean([leaf.dist for leaf in tree])
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all_taxa_in_tree = [leaf.name[:10] for leaf in tree]
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#Reading in cocontaminants
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coconts = { }
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if args.cocontaminants != None:
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if os.path.isfile(args.cocontaminants):
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for line in open(args.cocontaminants):
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line = line.strip().split('\t')
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if len(line) == 2:
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if line[0] in all_taxa_in_tree:
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coconts.update({ line[0] : line[1] })
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else:
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print('\nERROR: It looks like you tried to input a co-contaminants file to the contamination loop, but the file could not be found.\n')
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exit()
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for tax in all_taxa_in_tree:
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if tax not in coconts:
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coconts.update({ tax : tax })
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#For each sequence
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for leaf in tree:
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bad_sisters = { contam[0] : contam[1] for tax in sister_contam_per_tax for contam in sister_contam_per_tax[tax] if leaf.name.startswith(tax) }
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bad_subsisters = [contam for tax in subsister_contam_per_tax for contam in subsister_contam_per_tax[tax] if leaf.name.startswith(tax)]
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if len(bad_sisters) > 0 or len(bad_subsisters) > 0:
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#This loop will keep moving towards the root of the tree until it finds a node that
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#has leaves from a cell other than the one for which we are looking for sisters
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parent_node = leaf; seen_taxa = {coconts[leaf.name[:10]]}; sisters = []
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while len(seen_taxa) == 1:
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parent_node = parent_node.up
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for l2 in parent_node:
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seen_taxa.add(coconts[l2.name[:10]])
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if coconts[l2.name[:10]] != coconts[leaf.name[:10]]:
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sisters.append(l2.name[:10])
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#Create a record of the subsister sequences
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sub_sisters = []
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if args.subsister_rules != None:
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new_parent_node = parent_node.up
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for l2 in new_parent_node:
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if l2.name not in [l.name for l in parent_node]:
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sub_sisters.append(l2.name)
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#Create a record of the sister sequences
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sisters = list(dict.fromkeys(sisters))
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#Getting list of removable sequences by sister relationships
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sisters_removable = []; bls = []
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for contam in bad_sisters:
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for sister in sisters:
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if sister.startswith(contam) and sister not in sisters_removable:
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sisters_removable.append(sister)
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bls.append(bad_sisters[contam])
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#Getting list of removable sequences by sub-sister relationships
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subsisters_removable = []
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for contam in bad_subsisters:
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for sub_sister in sub_sisters:
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if sub_sister.startswith(contam) and sub_sister not in subsisters_removable:
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subsisters_removable.append(sub_sister)
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if len(bls) > 0:
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bl_rule_min = min(bls)
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else:
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bl_rule_min = 0
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if len(sisters_removable) == len(sisters) and leaf.dist <= bl_rule_min*mean_bl and len(sisters_removable) > 0:
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seqs2remove.append(leaf.name)
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elif len(subsisters_removable) == len(sub_sisters) and len(subsisters_removable) > 0:
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seqs2remove.append(leaf.name)
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return [leaf.name for leaf in tree if leaf.name not in seqs2remove]
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#Creating new unaligned file without the removed sequences
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def write_new_preguidance(params, seqs2keep, seqs_per_og, tree_file):
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if params.cl_exclude_taxa != None:
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try:
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exclude_taxa = list(dict.fromkeys([line.strip() for line in open(params.cl_exclude_taxa)]))
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except (FileNotFoundError, TypeError) as e:
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print('\nERROR: Unable to read the file listing taxa to exclude in the first iteration of the contamination loop (--cl_exclude_taxa). Please make sure that the path is correct and that the file is formatted correctly.\n\n' + str(e) + '\n')
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exit()
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else:
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exclude_taxa = []
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prefix = tree_file.split('.')[0]
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seq_file = [file for file in seqs_per_og if file.startswith(prefix)]
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if len(seq_file) == 0:
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print('\nNo sequence file found for tree file ' + tree_file + '. Skipping this gene family.\n')
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return None, []
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elif len(seq_file) > 1:
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print('\nMore than one sequence file found matching the tree file ' + tree_file + '. Please make your file names more unique: there should be one sequence file for every tree file, with a matching unique prefix (everything before the first "."). Skipping this gene family.\n')
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return None, []
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elif len(seq_file) == 1:
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with open(params.output + '/Output/Pre-Guidance/' + seq_file[0], 'w') as o:
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for rec in seqs_per_og[seq_file[0]]:
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if rec in seqs2keep and rec[:10] not in exclude_taxa and rec[:2] not in exclude_taxa and rec[:5] not in exclude_taxa:
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o.write('>' + rec + '\n' + seqs_per_og[seq_file[0]][rec] + '\n\n')
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seqs_removed_from_og = [seq for seq in seqs_per_og[seq_file[0]] if seq not in seqs2keep]
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return seq_file[0], seqs_removed_from_og
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#Utility function to run MAFFT in between iterations (if this is the chosen alignment method)
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def cl_mafft(params):
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for file in os.listdir(params.output + '/Output/Pre-Guidance'):
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if file.split('.')[-1] in ('fasta', 'fas', 'faa'):
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os.system('mafft ' + params.output + '/Output/Pre-Guidance/' + file + ' > ' + params.output + '/Output/NotGapTrimmed/' + file)
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os.system('Scripts/trimal-trimAl/source/trimal -in ' + params.output + '/Output/NotGapTrimmed/' + file + ' -out ' + params.output + '/Output/Guidance/' + file.split('.')[0] + '.95gapTrimmed.fasta' + ' -gapthreshold ' + str(params.trimal_cutoff) + ' -fasta')
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#Utility function to run FastTree in between iterations (if this is the chosen tree-building method)
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def cl_fasttree(params):
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for file in os.listdir(params.output + '/Output/Guidance'):
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if file.split('.')[-1] in ('fasta', 'fas', 'faa'):
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os.system('FastTree ' + params.output + '/Output/Guidance/' + file + ' > ' + params.output + '/Output/Trees/' + file.split('.')[0] + '.FastTree.tre')
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#Utility function to run Iqtree in between iterations (if this is the chosen tree-building method)
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def cl_iqtree(params):
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for file in os.listdir(params.output + '/Output/Guidance'):
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if file.split('.')[-1] in ('fasta', 'fas', 'faa'):
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if not os.path.isdir(params.output + '/Output/Intermediate/IQTree'):
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os.mkdir(params.output + '/Output/Intermediate/IQTree')
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tax_iqtree_outdir = params.output + '/Output/Intermediate/IQTree/' + file.split('.')[0].split('_preguidance')[0]
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os.mkdir(tax_iqtree_outdir)
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os.system('iqtree2 -s ' + params.output + '/Output/Guidance/' + file + ' -m LG+G -T 10 --prefix ' + tax_iqtree_outdir + '/' + file.split('.')[0].split('_preguidance')[0] + '.IQTree')
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#Copy over the final output
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if os.path.isfile(tax_iqtree_outdir + '/' + file.split('.')[0].split('_preguidance')[0] + '.IQTree.treefile'):
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os.system('cp ' + tax_iqtree_outdir + '/' + file.split('.')[0].split('_preguidance')[0] + '.IQTree.treefile ' + params.output + '/Output/Trees/' + file.split('.')[0].split('_preguidance')[0] + '.IQTree.tree')
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os.system('rm -r ' + params.output + '/Output/Intermediate/IQTree/*')
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#Utility function to run Iqtree_fast in between iterations (if this is the chosen tree-building method)
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def cl_iqtree_fast(params):
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for file in os.listdir(params.output + '/Output/Guidance'):
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if file.split('.')[-1] in ('fasta', 'fas', 'faa'):
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if not os.path.isdir(params.output + '/Output/Intermediate/IQTree'):
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os.mkdir(params.output + '/Output/Intermediate/IQTree')
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tax_iqtree_outdir = params.output + '/Output/Intermediate/IQTree/' + file.split('.')[0].split('_preguidance')[0]
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os.mkdir(tax_iqtree_outdir)
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os.system('iqtree2 -s ' + params.output + '/Output/Guidance/' + file + ' -m LG+G -T 10 --fast --prefix ' + tax_iqtree_outdir + '/' + file.split('.')[0].split('_preguidance')[0] + '.IQTree')
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#Copy over the final output
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if os.path.isfile(tax_iqtree_outdir + '/' + file.split('.')[0].split('_preguidance')[0] + '.IQTree.treefile'):
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os.system('cp ' + tax_iqtree_outdir + '/' + file.split('.')[0].split('_preguidance')[0] + '.IQTree.treefile ' + params.output + '/Output/Trees/' + file.split('.')[0].split('_preguidance')[0] + '.IQTree.tree')
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os.system('rm -r ' + params.output + '/Output/Intermediate/IQTree/*')
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#Wrapper script to manage parameters and iteration
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def run(params):
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seqs_removed = []
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completed_ogs = []
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with open('SequencesRemoved_ContaminationLoop.txt', 'w') as o:
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o.write('Sequence\tLoopRemoved\n')
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#For each iteration
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for loop in range(params.nloops):
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seqs_removed_loop = []
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#Finding input files
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if params.start == 'raw':
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seqs_per_og = { file : { rec.id : str(rec.seq) for rec in SeqIO.parse(params.output + '/Output/Pre-Guidance/' + file, 'fasta') } for file in os.listdir(params.output + '/Output/Pre-Guidance') if file.split('.')[-1] in ('fasta', 'fas', 'faa') }
|
||
elif params.start in ('unaligned', 'aligned', 'trees'):
|
||
seqs_per_og = { file : { rec.id : str(rec.seq).replace('-', '') for rec in SeqIO.parse(params.data + '/' + file, 'fasta') } for file in os.listdir(params.data) if file.split('.')[-1] in ('fasta', 'fas', 'faa') }
|
||
|
||
if loop == 0:
|
||
for file in os.listdir(params.data):
|
||
if file.split('.')[-1] in ('tre', 'tree', 'treefile'):
|
||
os.system('cp ' + params.data + '/' + file + ' ' + params.output + '/Output/Trees')
|
||
if loop > 0 or params.start == 'raw':
|
||
os.system('mv ' + params.output + '/Output/Pre-Guidance ' + params.output + '/Output/Pre-Guidance_' + str(loop))
|
||
|
||
os.mkdir(params.output + '/Output/Pre-Guidance')
|
||
|
||
#Wrapper for running clade-based contamination removal on all trees
|
||
if params.contamination_loop == 'clade':
|
||
for tree_file in os.listdir(params.output + '/Output/Trees'):
|
||
if tree_file.split('.')[-1] in ('tre', 'tree', 'treefile', 'nex') and tree_file not in completed_ogs:
|
||
seqs2keep = get_subtrees(params, params.output + '/Output/Trees/' + tree_file)
|
||
|
||
seq_file, seqs_removed_from_og = write_new_preguidance(params, seqs2keep, seqs_per_og, tree_file)
|
||
|
||
if len(seqs_removed_from_og) == 0:
|
||
completed_ogs.append(tree_file)
|
||
else:
|
||
seqs_removed_loop += [seq for seq in seqs_per_og[seq_file] if seq not in seqs2keep and seq not in seqs_removed]
|
||
#Wrapper for running sisters-based contamination removal on all trees
|
||
elif params.contamination_loop == 'seq':
|
||
|
||
sister_contam_per_tax = { }
|
||
if params.sister_rules != None:
|
||
for line in open(params.sister_rules):
|
||
if line.strip().split('\t')[0] not in sister_contam_per_tax:
|
||
sister_contam_per_tax.update({ line.strip().split('\t')[0] : [] })
|
||
|
||
try:
|
||
sister_contam_per_tax[line.strip().split('\t')[0]].append((line.strip().split('\t')[1], float(line.strip().split('\t')[2])))
|
||
except ValueError:
|
||
sister_contam_per_tax[line.strip().split('\t')[0]].append((line.strip().split('\t')[1], float('inf')))
|
||
except IndexError:
|
||
if line.strip() != '':
|
||
print('\nWarning: the line "' + line.strip() + '" in the sister rules file could not be processed\n')
|
||
|
||
subsister_contam_per_tax = { }
|
||
if params.subsister_rules != None:
|
||
if os.path.isfile(params.subsister_rules):
|
||
for line in open(params.subsister_rules):
|
||
if line.strip().split('\t')[0] not in subsister_contam_per_tax and len(line.strip().split('\t')) == 2:
|
||
subsister_contam_per_tax.update({ line.strip().split('\t')[0] : [] })
|
||
|
||
subsister_contam_per_tax[line.strip().split('\t')[0]].append(line.strip().split('\t')[1])
|
||
else:
|
||
print('\nERROR: It looks like you tried to input a sub-sister rules file to the contamination loop, but the file could not be found.\n')
|
||
exit()
|
||
|
||
for tree_file in os.listdir(params.output + '/Output/Trees'):
|
||
if tree_file.split('.')[-1] in ('tre', 'tree', 'treefile', 'nex') and tree_file not in completed_ogs:
|
||
seqs2keep = get_sisters(params, params.output + '/Output/Trees/' + tree_file, sister_contam_per_tax, subsister_contam_per_tax)
|
||
|
||
seq_file, seqs_removed_from_og = write_new_preguidance(params, seqs2keep, seqs_per_og, tree_file)
|
||
|
||
if len(seqs_removed_from_og) == 0:
|
||
completed_ogs.append(tree_file)
|
||
else:
|
||
seqs_removed_loop += [seq for seq in seqs_per_og[seq_file] if seq not in seqs2keep and seq not in seqs_removed]
|
||
|
||
#Keeping record of removed sequences
|
||
seqs_removed += seqs_removed_loop
|
||
with open(params.output + '/Output/SequencesRemoved_ContaminationLoop.txt', 'a') as o:
|
||
for seq in seqs_removed_loop:
|
||
o.write(seq + '\t' + str(loop) + '\n')
|
||
|
||
#Writing output files with sequences removed, with the iteration labeled
|
||
os.system('mv ' + params.output + '/Output/Trees ' + params.output + '/Output/Trees_' + str(loop))
|
||
os.mkdir(params.output + '/Output/Trees')
|
||
|
||
os.system('mv ' + params.output + '/Output/Guidance ' + params.output + '/Output/Guidance_' + str(loop))
|
||
os.mkdir(params.output + '/Output/Guidance')
|
||
|
||
os.system('mv ' + params.output + '/Output/NotGapTrimmed ' + params.output + '/Output/NotGapTrimmed_' + str(loop))
|
||
os.mkdir(params.output + '/Output/NotGapTrimmed')
|
||
|
||
params.start = 'unaligned'
|
||
params.end = 'trees'
|
||
params.tree_method = params.cl_tree_method
|
||
|
||
#Re-aligning and building trees without contaminant sequences... then ready for next iteration.
|
||
if params.cl_alignment_method == 'mafft_only':
|
||
cl_mafft(params)
|
||
else:
|
||
guidance.run(params)
|
||
|
||
if params.cl_tree_method == 'fasttree':
|
||
cl_fasttree(params)
|
||
elif params.cl_tree_method == 'iqtree':
|
||
cl_iqtree(params)
|
||
os.system('rm -r ' + params.output + '/Output/Intermediate/IQTree/*')
|
||
elif params.cl_tree_method == 'iqtree_fast':
|
||
cl_iqtree_fast(params)
|
||
os.system('rm -r ' + params.output + '/Output/Intermediate/IQTree/*')
|
||
elif params.cl_tree_method == 'raxml':
|
||
os.system('rm -r ' + params.output + '/Output/Intermediate/RAxML/*')
|
||
|
||
|
||
|
||
|