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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/kraken_taxonomy_report commit 5b5fa1a3d9492fbbf01aa6ddceca9d4525c7cba5
author | iuc |
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date | Tue, 12 Mar 2024 09:52:55 +0000 |
parents | 27d65c78863c |
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#!/usr/bin/env python # Reports a summary of Kraken's results # and optionally creates a newick Tree # Copyright (c) 2016 Daniel Blankenberg # Licensed under the Academic Free License version 3.0 # https://github.com/blankenberg/Kraken-Taxonomy-Report from __future__ import print_function import optparse import os import re import sys __VERSION__ = '0.0.2' __URL__ = "https://github.com/blankenberg/Kraken-Taxonomy-Report" # Rank names were pulled from ncbi nodes.dmp on 02/02/2016 # cat nodes.dmp | cut -f 5 | sort | uniq # "root" is added manually NO_RANK_NAME = "no rank" RANK_NAMES = [ NO_RANK_NAME, "root", "superkingdom", "kingdom", "subkingdom", "superphylum", "phylum", "subphylum", "superclass", "class", "subclass", "infraclass", "superorder", "order", "suborder", "infraorder", "parvorder", "superfamily", "family", "subfamily", "tribe", "subtribe", "genus", "subgenus", "species group", "species subgroup", "species", "subspecies", "varietas", "forma" ] # NB: We put 'no rank' at top of list for generating trees, due to e.g. # root (root) -> cellular organisms (no rank) -> bacteria (superkingdom) RANK_NAME_TO_INTS = dict([(y, x) for (x, y) in enumerate(RANK_NAMES)]) RANK_NAMES_INTS = range(len(RANK_NAMES)) NO_RANK_INT = RANK_NAMES.index(NO_RANK_NAME) NO_RANK_CODE = 'n' PRIMARY_RANK_NAMES = ['species', 'genus', 'family', 'order', 'class', 'phylum', 'kingdom'] RANK_INT_TO_CODE = {} for name in PRIMARY_RANK_NAMES: RANK_INT_TO_CODE[RANK_NAMES.index(name)] = name[0] RANK_INT_TO_CODE[RANK_NAMES.index('superkingdom')] = 'd' PRIMARY_RANK_NAMES.append('superkingdom') NAME_STUB = "%s__%s" NAME_RE = re.compile(r"(\t| |\||\.;)") NAME_REPL = "_" def get_kraken_db_path(db): assert db, ValueError("You must provide a kraken database") k_db_path = os.getenv('KRAKEN_DB_PATH', None) if k_db_path: db = os.path.join(k_db_path, db) return db def load_taxonomy(db_path, sanitize_names=False): child_lists = {} name_map = {} rank_map = {} names = {} # Store names here to look for duplicates (id, True/False name fixed) with open(os.path.join(db_path, "taxonomy/names.dmp")) as fh: for line in fh: line = line.rstrip("\n\r") if line.endswith("\t|"): line = line[:-2] fields = line.split("\t|\t") node_id = fields[0] name = fields[1] if sanitize_names: name = NAME_RE.sub(NAME_REPL, name) name_type = fields[3] if name_type == "scientific name": if name in names: print('Warning: name "%s" found at node "%s" but already exists originally for node "%s".' % (name, node_id, names[name][0]), file=sys.stderr) new_name = "%s_%s" % (name, node_id) print('Transforming node "%s" named "%s" to "%s".' % (node_id, name, new_name), file=sys.stderr) assert new_name not in names, 'Transformed Name "%s" already exists. Cannot recover at this time.' % new_name if not names[name][1]: orig_new_name = "%s_%s" % (name, names[name][0]) print('Transforming node "%s" named "%s" to "%s".' % (names[name][0], name, orig_new_name), file=sys.stderr) assert orig_new_name not in names, 'Transformed Name "%s" already exists. Cannot recover at this time.' % orig_new_name name_map[names[name][0]] = orig_new_name names[name] = (names[name][0], True) name = new_name else: names[name] = (node_id, False) name_map[node_id] = name with open(os.path.join(db_path, "taxonomy/nodes.dmp")) as fh: for line in fh: line = line.rstrip("\n\r") fields = line.split("\t|\t") node_id = fields[0] parent_id = fields[1] rank = RANK_NAME_TO_INTS.get(fields[2].lower(), None) if rank is None: # This should never happen, unless new taxonomy ranks are created print('Unrecognized rank: Node "%s" is "%s", setting to "%s"' % (node_id, fields[2], NO_RANK_NAME), file=sys.stderr) rank = NO_RANK_INT if node_id == '1': parent_id = '0' if parent_id not in child_lists: child_lists[parent_id] = [] child_lists[parent_id].append(node_id) rank_map[node_id] = rank return (child_lists, name_map, rank_map) def dfs_summation(node, counts, child_lists): children = child_lists.get(node, None) if children: for child in children: dfs_summation(child, counts, child_lists) counts[node] = counts.get(node, 0) + counts.get(child, 0) def dfs_report(node, file_data, hit_taxa, rank_map, name_map, child_lists, output_lines, options, name=None, tax=None): rank_int = rank_map[node] code = RANK_INT_TO_CODE.get(rank_int, NO_RANK_CODE) if (code != NO_RANK_CODE or options.intermediate) and (options.show_zeros or node in hit_taxa): if name is None: name = "" else: name = "%s|" % name if tax is None: tax = '' else: tax = "%s;" % tax sanitized_name = name_map[node] name_stub = NAME_STUB % (code, sanitized_name) name = name + name_stub tax = tax + name_stub if options.name_id: output = node elif options.name_long: output = name else: output = sanitized_name for val in file_data: output = "%s\t%i" % (output, val.get(node, 0)) if options.show_rank: output = "%s\t%s" % (output, RANK_NAMES[rank_int]) if options.taxonomy: output = "%s\t%s" % (output, tax) output_lines[rank_int].append(output) children = child_lists.get(node) if children: for child in children: dfs_report(child, file_data, hit_taxa, rank_map, name_map, child_lists, output_lines, options, name=name, tax=tax) def write_tree(child_lists, name_map, rank_map, options, branch_length=1): # Uses Biopython, only load if making tree import Bio.Phylo from Bio.Phylo import BaseTree def _get_name(node_id): if options.name_id: return node_id return name_map[node_id] nodes = {} root_node_id = child_lists["0"][0] nodes[root_node_id] = BaseTree.Clade(name=_get_name(root_node_id), branch_length=branch_length) def recurse_children(parent_id): if options.cluster is not None and rank_map[parent_id] == options.cluster: # Short circuit if we found our rank, prevents 'hanging' no ranks from being output # e.g. clustering by "species" (Escherichia coli), but have "no rank" below (Escherichia coli K-12) in test_db return if parent_id not in nodes: nodes[parent_id] = BaseTree.Clade(name=_get_name(parent_id), branch_length=branch_length) for child_id in child_lists.get(parent_id, []): if options.cluster is None or (rank_map[child_id] <= options.cluster): if child_id not in nodes: nodes[child_id] = BaseTree.Clade(name=_get_name(child_id), branch_length=branch_length) nodes[parent_id].clades.append(nodes[child_id]) recurse_children(child_id) recurse_children(root_node_id) tree = BaseTree.Tree(root=nodes[root_node_id]) Bio.Phylo.write([tree], options.output_tree, 'newick') def __main__(): parser = optparse.OptionParser(usage="%prog [options] file1 file...fileN") parser.add_option('-v', '--version', dest='version', action='store_true', default=False, help='print version and exit') parser.add_option('', '--show-zeros', dest='show_zeros', action='store_true', default=False, help='Show empty nodes') parser.add_option('', '--header-line', dest='header_line', action='store_true', default=False, help='Provide a header on output') parser.add_option('', '--intermediate', dest='intermediate', action='store_true', default=False, help='Intermediate Ranks') parser.add_option('', '--name-id', dest='name_id', action='store_true', default=False, help='Use Taxa ID instead of Name') parser.add_option('', '--name-long', dest='name_long', action='store_true', default=False, help='Use Long taxa ID instead of base name') parser.add_option('', '--taxonomy', dest='taxonomy', action='store_true', default=False, help='Output taxonomy in last column') parser.add_option('', '--cluster', dest='cluster', action='store', type="string", default=None, help='Cluster counts to specified rank') parser.add_option('', '--summation', dest='summation', action='store_true', default=False, help='Add summation of child counts to each taxa') parser.add_option('', '--sanitize-names', dest='sanitize_names', action='store_true', default=False, help=r'Replace special chars (\t| |\||\.;) with underscore (_)') parser.add_option('', '--show-rank', dest='show_rank', action='store_true', default=False, help='Output column with Rank name') parser.add_option('', '--db', dest='db', action='store', type="string", default=None, help='Name of Kraken database') parser.add_option('', '--output', dest='output', action='store', type="string", default=None, help='Name of output file') parser.add_option('', '--output-tree', dest='output_tree', action='store', type="string", default=None, help='Name of output file to place newick tree') (options, args) = parser.parse_args() if options.version: print("Kraken Taxonomy Report (%s) version %s" % (__URL__, __VERSION__), file=sys.stderr) sys.exit() if not args: print(parser.get_usage(), file=sys.stderr) sys.exit() if options.cluster: cluster_name = options.cluster.lower() cluster = RANK_NAME_TO_INTS.get(cluster_name, None) assert cluster is not None, ValueError('"%s" is not a valid rank for clustering.' % options.cluster) if cluster_name not in PRIMARY_RANK_NAMES: assert options.intermediate, ValueError('You cannot cluster by "%s", unless you enable intermediate ranks.' % options.cluster) ranks_to_report = [cluster] options.cluster = cluster # When clustering we need to do summatation options.summation = True else: options.cluster = None # make empty string into None ranks_to_report = RANK_NAMES_INTS if options.output: output_fh = open(options.output, 'w') else: output_fh = sys.stdout db_path = get_kraken_db_path(options.db) (child_lists, name_map, rank_map) = load_taxonomy(db_path, sanitize_names=options.sanitize_names) file_data = [] hit_taxa = [] for input_filename in args: taxo_counts = {} with open(input_filename) as fh: for line in fh: fields = line.split("\t") taxo_counts[fields[2]] = taxo_counts.get(fields[2], 0) + 1 clade_counts = taxo_counts.copy() # fixme remove copying? if options.summation: dfs_summation('1', clade_counts, child_lists) for key, value in clade_counts.items(): if value and key not in hit_taxa: hit_taxa.append(key) file_data.append(clade_counts) if options.header_line: output_fh.write("#ID\t") output_fh.write("\t".join(args)) if options.show_rank: output_fh.write("\trank") if options.taxonomy: output_fh.write("\ttaxonomy") output_fh.write('\n') output_lines = dict([(x, []) for x in RANK_NAMES_INTS]) dfs_report('1', file_data, hit_taxa, rank_map, name_map, child_lists, output_lines, options, name=None, tax=None) for rank_int in ranks_to_report: for line in output_lines.get(rank_int, []): output_fh.write(line) output_fh.write('\n') fh.close() if options.output_tree: write_tree(child_lists, name_map, rank_map, options) if __name__ == "__main__": __main__()