# HG changeset patch # User iuc # Date 1647161105 0 # Node ID 031f84cb2fd3d50c84bcf85c4cec4525f48d3dd5 # Parent 06c0eb0330251d27198cd4cee8f5ad255e32fb1e "planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/concoct commit 40a09cbfd6052f7b0295946621db1bdf58228b09" diff -r 06c0eb033025 -r 031f84cb2fd3 concoct.xml --- a/concoct.xml Fri Feb 18 14:18:11 2022 +0000 +++ b/concoct.xml Sun Mar 13 08:45:05 2022 +0000 @@ -109,8 +109,9 @@ sample (the values are the average coverage for this contig in that sample) and a file containing sequences in fasta format. -Three are produced; clustering of the > 1000 kmer count, the PCA transformed matrix and the PCA components. +Three outputs are produced; clustering of the > 1000 kmer count, the PCA transformed matrix and the PCA components. +@HELP_OVERVIEW@ ]]> diff -r 06c0eb033025 -r 031f84cb2fd3 coverage_table.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/coverage_table.py Sun Mar 13 08:45:05 2022 +0000 @@ -0,0 +1,83 @@ +#!/usr/bin/env python + +import argparse +import gzip +from functools import partial + +from Bio import SeqIO + + +def generate_coverage_table(input_fasta, input_tabular, gzipped, output): + # Read input file into a dict and return everything + # in the table format required by CONCOCT. + gc_and_len_dict = get_gc_and_len_dict(input_fasta, gzipped) + assert(len(gc_and_len_dict) > 0) + bed_coverage_dict = get_bed_coverage_dict(input_tabular) + + with open(output, 'w') as fh: + # Output the header. + fh.write("contig\tlength") + t = tuple(range(len(bed_coverage_dict))) + fh.write("\tcov_mean_sample_%d\n" % len(t)) + # Output the content. + for acc in gc_and_len_dict: + # Fasta stats. + fh.write("%s\t%s" % (acc, gc_and_len_dict[acc]['length'])) + # Mean + try: + # Coverage mean + fh.write("\t%f" % (bed_coverage_dict[acc]["cov_mean"])) + except KeyError: + # No reads mapped to this contig + fh.write("\t0") + fh.write("\n") + + +def get_bed_coverage_dict(input_tabular): + # Ddetermine mean coverage and percentage covered + # for each contig, returning a dict with fasta id + # as key and percentage covered and cov_mean as keys + # for the inner dict. + out_dict = {} + + with open(input_tabular, 'r') as fh: + for line in fh: + line = line.rstrip('\r\n') + cols = line.split('\t') + try: + d = out_dict[cols[0]] + except KeyError: + d = {} + out_dict[cols[0]] = d + if int(cols[1]) == 0: + d["percentage_covered"] = 100 - float(cols[4]) * 100.0 + else: + d["cov_mean"] = d.get("cov_mean", 0) + int(cols[1]) * float(cols[4]) + return out_dict + + +def get_gc_and_len_dict(input_fasta, gzipped): + # Creates a dictionary with the fasta id as key + # and GC and length as keys for the inner dictionary. + if gzipped: + _open = partial(gzip.open, mode='rt') + else: + _open = open + + out_dict = {} + with _open(input_fasta) as input_fh: + for rec in SeqIO.parse(input_fh, "fasta"): + out_dict[rec.id] = {} + out_dict[rec.id]["length"] = len(rec.seq) + return out_dict + + +parser = argparse.ArgumentParser(description=__doc__) +parser.add_argument('--input_tabular', action='store', dest='input_tabular', help='bedtools genomeCoverageBed bed file') +parser.add_argument('--input_fasta', action='store', dest='input_fasta', help='Contigs fasta file') +parser.add_argument("--gzipped", action="store_true", dest="gzipped", default=False, help="input_fasta is gzipped") +parser.add_argument('--output', action='store', dest='output', help='Output file') + +args = parser.parse_args() + +generate_coverage_table(args.input_fasta, args.input_tabular, args.gzipped, args.output) diff -r 06c0eb033025 -r 031f84cb2fd3 cut_up_fasta.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cut_up_fasta.py Sun Mar 13 08:45:05 2022 +0000 @@ -0,0 +1,58 @@ +#!/usr/bin/env python + +import argparse +import gzip +from functools import partial + +from Bio import SeqIO + + +def cut_up_fasta(input_fasta, chunk_size, overlap, merge_last, output_fasta, output_bed, gzipped): + if gzipped: + _open = partial(gzip.open, mode='rt') + else: + _open = open + + fasta_fh = open(output_fasta, 'w') + + if output_bed is not None: + bed_fh = open(output_bed, 'w') + + with _open(input_fasta) as input_fh: + for record in SeqIO.parse(input_fh, "fasta"): + if (not merge_last and len(record.seq) > chunk_size) or (merge_last and len(record.seq) >= 2 * chunk_size): + for index, split_seq in enumerate(chunks(record.seq, chunk_size, overlap, merge_last)): + fasta_fh.write(f">{record.id}.concoct_part_{index}\n{split_seq}\n") + if output_bed is not None: + bed_fh.write(f"{record.id}\t{chunk_size * index}\t{chunk_size * index + len(split_seq)}\t{record.id}.concoct_part_{index}\n") + else: + fasta_fh.write(f">{record.id}.concoct_part_0\n{record.seq}\n") + if output_bed is not None: + bed_fh.write(f"{record.id}\t0\t{len(record.seq)}\t{record.id}.concoct_part_0\n") + if output_bed is not None: + bed_fh.close() + + +def chunks(seq, chunk_size, overlap_size, merge_last): + # Yield successive chunk_size-sized chunks from seq + # with given overlap overlap_size between the chunks. + assert chunk_size > overlap_size + if merge_last: + for i in range(0, len(seq) - chunk_size + 1, chunk_size - overlap_size): + yield seq[i:i + chunk_size] if i + chunk_size + chunk_size - overlap_size <= len(seq) else seq[i:] + else: + for i in range(0, len(seq), chunk_size - overlap_size): + yield seq[i:i + chunk_size] + + +parser = argparse.ArgumentParser() +parser.add_argument("--input_fasta", action="store", dest="input_fasta", help="Fasta files with contigs") +parser.add_argument("--gzipped", action="store_true", dest="gzipped", help="Input file is gzipped") +parser.add_argument("--chunk_size", action="store", dest="chunk_size", type=int, help="Chunk size\n") +parser.add_argument("--overlap_size", action="store", dest="overlap_size", type=int, help="Overlap size\n") +parser.add_argument("--merge_last", default=False, action="store_true", dest="merge_last", help="Concatenate final part to last contig\n") +parser.add_argument("--output_bed", action="store", dest="output_bed", default=None, help="BED file to be created with exact regions of the original contigs corresponding to the newly created contigs") +parser.add_argument("--output_fasta", action="store", dest="output_fasta", help="Output fasta file with cut contigs") + +args = parser.parse_args() +cut_up_fasta(args.input_fasta, args.chunk_size, args.overlap_size, args.merge_last, args.output_fasta, args.output_bed, args.gzipped) diff -r 06c0eb033025 -r 031f84cb2fd3 macros.xml --- a/macros.xml Fri Feb 18 14:18:11 2022 +0000 +++ b/macros.xml Sun Mar 13 08:45:05 2022 +0000 @@ -4,11 +4,20 @@ 21.01 + biopython concoct pandas - biopython + + +The intended use of the CONCOCT tools is shown in the following image. + +.. image:: pipeline.png + +More information may be found on the CONCOCT homepage:: https://github.com/BinPro/CONCOCT + + 10.1038/nmeth.3103 diff -r 06c0eb033025 -r 031f84cb2fd3 merge_cut_up_clustering.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/merge_cut_up_clustering.py Sun Mar 13 08:45:05 2022 +0000 @@ -0,0 +1,56 @@ +#!/usr/bin/env python + +import argparse +import re +import sys +from collections import Counter +from collections import defaultdict + + +CONTIG_PART_EXPR = re.compile(r'(.*)\.concoct_part_([0-9]*)') + + +def original_contig_name_special(contig_id): + try: + original_id, part_index = CONTIG_PART_EXPR.match(contig_id).group(1, 2) + return original_id, part_index + except AttributeError: + # No matches for concoct_part regex. + return contig_id, 0 + + +parser = argparse.ArgumentParser() +parser.add_argument("--input", action="store", dest="input", help="Tabular file with cut up clusters") +parser.add_argument("--output", action="store", dest="output", help="Output file with merged clusters") + +args = parser.parse_args() + +# Get cut up clusters +all_seqs = {} +all_originals = defaultdict(dict) +with open(args.input, 'r') as ifh: + for i, line in enumerate(ifh): + if i == 0: + if 'contig_id' not in line: + sys.stderr.write("ERROR nvalid clustering file, 'contig_id' is not found in the header.") + sys.exit(-1) + # Skip header. + continue + line = line.rstrip('\r\n') + contig_id, cluster_id = line.split('\t') + original_contig_name, part_id = original_contig_name_special(contig_id) + all_originals[original_contig_name][part_id] = cluster_id + +# Merge cut up clusters. +with open(args.output, 'w') as ofh: + ofh.write("contig_id\tcluster_id\n") + for original_contig_id, part_ids_d in all_originals.items(): + if len(part_ids_d) > 1: + c = Counter(part_ids_d.values()) + cluster_id = c.most_common(1)[0][0] + c_string = [(a, b) for a, b in c.items()] + # Here if len(c.values()) > 1, + # then no cluster for contig. + else: + cluster_id = list(part_ids_d.values())[0] + ofh.write(f"{original_contig_id}\t{cluster_id}\n") diff -r 06c0eb033025 -r 031f84cb2fd3 static/images/pipeline.png Binary file static/images/pipeline.png has changed diff -r 06c0eb033025 -r 031f84cb2fd3 test-data/input.fasta.gz Binary file test-data/input.fasta.gz has changed diff -r 06c0eb033025 -r 031f84cb2fd3 test-data/input_coverage_table.fasta.gz Binary file test-data/input_coverage_table.fasta.gz has changed diff -r 06c0eb033025 -r 031f84cb2fd3 test-data/input_coverage_table.tabular --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/input_coverage_table.tabular Sun Mar 13 08:45:05 2022 +0000 @@ -0,0 +1,422 @@ +NODE_100_length_1535_cov_6.691205 0 1605 1605 1 +NODE_101_length_153_cov_4.235294 0 223 223 1 +NODE_103_length_20202_cov_8.395357.0 0 10000 10000 1 +NODE_103_length_20202_cov_8.395357.1 0 10272 10272 1 +NODE_104_length_823_cov_8.356014 0 893 893 1 +NODE_105_length_260_cov_4.142308 0 330 330 1 +NODE_106_length_2172_cov_16.183702 0 2242 2242 1 +NODE_107_length_7609_cov_8.569195 0 7679 7679 1 +NODE_108_length_1232_cov_16.167208 0 1302 1302 1 +NODE_109_length_178_cov_16.084270 0 248 248 1 +NODE_10_length_186_cov_4.327957 0 256 256 1 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