--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/scripts/ReMatCh/rematch.py	Fri Mar 11 15:50:35 2022 -0500
@@ -0,0 +1,746 @@
+#!/usr/bin/env python3
+
+# -*- coding: utf-8 -*-
+
+"""
+rematch.py - Reads mapping against target sequences, checking mapping
+and consensus sequences production
+<https://github.com/B-UMMI/ReMatCh/>
+
+Copyright (C) 2019 Miguel Machado <mpmachado@medicina.ulisboa.pt>
+
+Last modified: August 08, 2019
+
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with this program.  If not, see <http://www.gnu.org/licenses/>.
+"""
+
+import os
+import sys
+import time
+import argparse
+
+try:
+    from __init__ import __version__
+
+    import modules.utils as utils
+    import modules.seqFromWebTaxon as seq_from_web_taxon
+    import modules.download as download
+    import modules.rematch_module as rematch_module
+    import modules.checkMLST as check_mlst
+except ImportError:
+    from ReMatCh.__init__ import __version__
+
+    from ReMatCh.modules import utils as utils
+    from ReMatCh.modules import seqFromWebTaxon as seq_from_web_taxon
+    from ReMatCh.modules import download as download
+    from ReMatCh.modules import rematch_module as rematch_module
+    from ReMatCh.modules import checkMLST as check_mlst
+
+
+def search_fastq_files(directory):
+    files_extensions = ['.fastq.gz', '.fq.gz']
+    pair_end_files_separation = [['_R1_001.f', '_R2_001.f'], ['_1.f', '_2.f']]
+
+    list_ids = {}
+    directories = [d for d in os.listdir(directory) if
+                   not d.startswith('.') and os.path.isdir(os.path.join(directory, d, ''))]
+    for directory_found in directories:
+        if directory_found != 'pubmlst':
+            directory_path = os.path.join(directory, directory_found, '')
+
+            fastq_found = []
+            files = [f for f in os.listdir(directory_path) if
+                     not f.startswith('.') and os.path.isfile(os.path.join(directory_path, f))]
+            for file_found in files:
+                if file_found.endswith(tuple(files_extensions)):
+                    fastq_found.append(file_found)
+
+            if len(fastq_found) == 1:
+                list_ids[directory_found] = [os.path.join(directory_path, f) for f in fastq_found]
+            elif len(fastq_found) >= 2:
+                file_pair = []
+
+                # Search pairs
+                for pe_separation in pair_end_files_separation:
+                    for fastq in fastq_found:
+                        if pe_separation[0] in fastq or pe_separation[1] in fastq:
+                            file_pair.append(fastq)
+
+                    if len(file_pair) == 2:
+                        break
+                    else:
+                        file_pair = []
+
+                # Search single
+                if len(file_pair) == 0:
+                    for pe_separation in pair_end_files_separation:
+                        for fastq in fastq_found:
+                            if pe_separation[0] not in fastq or pe_separation[1] not in fastq:
+                                file_pair.append(fastq)
+
+                    if len(file_pair) >= 1:
+                        file_pair = file_pair[0]
+
+                if len(file_pair) >= 1:
+                    list_ids[directory_found] = [os.path.join(directory_path, f) for f in file_pair]
+
+    return list_ids
+
+
+def get_list_ids_from_file(file_list_ids):
+    list_ids = []
+
+    with open(file_list_ids, 'rtU') as lines:
+        for line in lines:
+            line = line.rstrip('\r\n')
+            if len(line) > 0:
+                list_ids.append(line)
+
+    if len(list_ids) == 0:
+        sys.exit('No runIDs were found in ' + file_list_ids)
+
+    return list_ids
+
+
+def get_taxon_run_ids(taxon_name, outputfile):
+    seq_from_web_taxon.run_seq_from_web_taxon(taxon_name, outputfile, True, True, True, False)
+
+    run_ids = []
+    with open(outputfile, 'rtU') as reader:
+        for line in reader:
+            line = line.rstrip('\r\n')
+            if len(line) > 0:
+                if not line.startswith('#'):
+                    line = line.split('\t')
+                    run_ids.append(line[0])
+
+    return run_ids
+
+
+def get_list_ids(workdir, file_list_ids, taxon_name):
+    searched_fastq_files = False
+    list_ids = []
+    if file_list_ids is None and taxon_name is None:
+        list_ids = search_fastq_files(workdir)
+        searched_fastq_files = True
+    elif file_list_ids is not None:
+        list_ids = get_list_ids_from_file(os.path.abspath(file_list_ids))
+    elif taxon_name is not None and file_list_ids is None:
+        list_ids = get_taxon_run_ids(taxon_name, os.path.join(workdir, 'IDs_list.seqFromWebTaxon.tab'))
+
+    if len(list_ids) == 0:
+        sys.exit('No IDs were found')
+    return list_ids, searched_fastq_files
+
+
+def format_gene_info(gene_specific_info, minimum_gene_coverage, minimum_gene_identity, reported_data_type, summary,
+                     sample, genes_present):
+    info = None
+    if gene_specific_info['gene_coverage'] >= minimum_gene_coverage and \
+            gene_specific_info['gene_identity'] >= minimum_gene_identity:
+        if summary and sample not in genes_present:
+            genes_present[sample] = {}
+
+        if gene_specific_info['gene_number_positions_multiple_alleles'] == 0:
+            s = str(gene_specific_info[reported_data_type])
+            info = str(s)
+            if summary:
+                genes_present[sample][gene_specific_info['header']] = str(s)
+        else:
+            s = 'multiAlleles_' + str(gene_specific_info[reported_data_type])
+            info = str(s)
+            if summary:
+                genes_present[sample][gene_specific_info['header']] = str(s)
+    else:
+        info = 'absent_' + str(gene_specific_info[reported_data_type])
+
+    return info, genes_present
+
+
+def write_data_by_gene(gene_list_reference, minimum_gene_coverage, sample, data_by_gene, outdir, time_str, run_times,
+                       minimum_gene_identity, reported_data_type, summary, genes_present):
+    combined_report = \
+        os.path.join(outdir,
+                     'combined_report.data_by_gene.' + run_times + '.' + reported_data_type + '.' + time_str + '.tab')
+
+    if reported_data_type == 'coverage_depth':
+        reported_data_type = 'gene_mean_read_coverage'
+    elif reported_data_type == 'sequence_coverage':
+        reported_data_type = 'gene_coverage'
+
+    combined_report_exist = os.path.isfile(combined_report)
+    with open(combined_report, 'at') as writer:
+        seq_list = sorted(gene_list_reference.keys())
+        if not combined_report_exist:
+            writer.write('#sample' + '\t' + '\t'.join([gene_list_reference[seq] for seq in seq_list]) + '\n')
+
+        results = {}
+        headers = []
+        for i in data_by_gene:
+            results[data_by_gene[i]['header']], genes_present = format_gene_info(data_by_gene[i], minimum_gene_coverage,
+                                                                                 minimum_gene_identity,
+                                                                                 reported_data_type, summary, sample,
+                                                                                 genes_present)
+            headers.append(data_by_gene[i]['header'])
+
+        if len(headers) != gene_list_reference:
+            for gene in gene_list_reference:
+                if gene not in headers:
+                    results[gene] = 'NA'
+
+        writer.write(sample + '\t' + '\t'.join([results[seq] for seq in seq_list]) + '\n')
+
+    return genes_present
+
+
+def write_sample_report(sample, outdir, time_str, file_size, run_successfully_fastq, run_successfully_rematch_first,
+                        run_successfully_rematch_second, time_taken_fastq, time_taken_rematch_first,
+                        time_taken_rematch_second, time_taken_sample, sequencing_information, sample_data_general_first,
+                        sample_data_general_second, fastq_used):
+    sample_report = os.path.join(outdir, 'sample_report.' + time_str + '.tab')
+    report_exist = os.path.isfile(sample_report)
+
+    header_general = ['sample', 'sample_run_successfully', 'sample_run_time', 'files_size', 'download_run_successfully',
+                      'download_run_time', 'rematch_run_successfully_first', 'rematch_run_time_first',
+                      'rematch_run_successfully_second', 'rematch_run_time_second']
+    header_data_general = ['number_absent_genes', 'number_genes_multiple_alleles', 'mean_sample_coverage']
+    header_sequencing = ['run_accession', 'instrument_platform', 'instrument_model', 'library_layout', 'library_source',
+                         'extra_run_accession', 'nominal_length', 'read_count', 'base_count', 'date_download']
+
+    with open(sample_report, 'at') as writer:
+        if not report_exist:
+            writer.write('#' + '\t'.join(header_general) + '\t' + '_first\t'.join(header_data_general) + '_first\t' +
+                         '_second\t'.join(header_data_general) + '_second\t' + '\t'.join(header_sequencing) + '\t' +
+                         'fastq_used' + '\n')
+
+        writer.write('\t'.join([sample,
+                                str(all([run_successfully_fastq is not False,
+                                         run_successfully_rematch_first is not False,
+                                         run_successfully_rematch_second is not False])),
+                                str(time_taken_sample),
+                                str(file_size),
+                                str(run_successfully_fastq),
+                                str(time_taken_fastq),
+                                str(run_successfully_rematch_first),
+                                str(time_taken_rematch_first),
+                                str(run_successfully_rematch_second),
+                                str(time_taken_rematch_second)]) +
+                     '\t' + '\t'.join([str(sample_data_general_first[i]) for i in header_data_general]) +
+                     '\t' + '\t'.join([str(sample_data_general_second[i]) for i in header_data_general]) +
+                     '\t' + '\t'.join([str(sequencing_information[i]) for i in header_sequencing]) +
+                     '\t' + ','.join(fastq_used) + '\n')
+
+
+def concatenate_extra_seq_2_consensus(consensus_sequence, reference_sequence, extra_seq_length, outdir):
+    reference_dict, ignore, ignore = rematch_module.get_sequence_information(reference_sequence, extra_seq_length)
+    consensus_dict, genes, ignore = rematch_module.get_sequence_information(consensus_sequence, 0)
+    number_consensus_with_sequences = 0
+    for k, values_consensus in list(consensus_dict.items()):
+        for values_reference in list(reference_dict.values()):
+            if values_reference['header'] == values_consensus['header']:
+                if len(set(consensus_dict[k]['sequence'])) > 1:
+                    number_consensus_with_sequences += 1
+                    if extra_seq_length <= len(values_reference['sequence']):
+                        right_extra_seq = \
+                            '' if extra_seq_length == 0 else values_reference['sequence'][-extra_seq_length:]
+                        consensus_dict[k]['sequence'] = \
+                            values_reference['sequence'][:extra_seq_length] + \
+                            consensus_dict[k]['sequence'] + \
+                            right_extra_seq
+                        consensus_dict[k]['length'] += extra_seq_length + len(right_extra_seq)
+
+    consensus_concatenated = os.path.join(outdir, 'consensus_concatenated_extraSeq.fasta')
+    with open(consensus_concatenated, 'wt') as writer:
+        for i in consensus_dict:
+            writer.write('>' + consensus_dict[i]['header'] + '\n')
+            fasta_sequence_lines = rematch_module.chunkstring(consensus_dict[i]['sequence'], 80)
+            for line in fasta_sequence_lines:
+                writer.write(line + '\n')
+
+    return consensus_concatenated, genes, consensus_dict, number_consensus_with_sequences
+
+
+def clean_headers_reference_file(reference_file, outdir, extra_seq):
+    problematic_characters = ["|", " ", ",", ".", "(", ")", "'", "/", ":"]
+    print('Checking if reference sequences contain ' + str(problematic_characters) + '\n')
+    # headers_changed = False
+    new_reference_file = str(reference_file)
+    sequences, genes, headers_changed = rematch_module.get_sequence_information(reference_file, extra_seq)
+    if headers_changed:
+        print('At least one of the those characters was found. Replacing those with _' + '\n')
+        new_reference_file = \
+            os.path.join(outdir, os.path.splitext(os.path.basename(reference_file))[0] + '.headers_renamed.fasta')
+        with open(new_reference_file, 'wt') as writer:
+            for i in sequences:
+                writer.write('>' + sequences[i]['header'] + '\n')
+                fasta_sequence_lines = rematch_module.chunkstring(sequences[i]['sequence'], 80)
+                for line in fasta_sequence_lines:
+                    writer.write(line + '\n')
+    return new_reference_file, genes, sequences
+
+
+def write_mlst_report(sample, run_times, consensus_type, st, alleles_profile, loci_order, outdir, time_str):
+    mlst_report = os.path.join(outdir, 'mlst_report.' + time_str + '.tab')
+    mlst_report_exist = os.path.isfile(mlst_report)
+    with open(mlst_report, 'at') as writer:
+        if not mlst_report_exist:
+            writer.write('\t'.join(['#sample', 'ReMatCh_run', 'consensus_type', 'ST'] + loci_order) + '\n')
+        writer.write('\t'.join([sample, run_times, consensus_type, str(st)] + alleles_profile.split(',')) + '\n')
+
+
+def run_get_st(sample, mlst_dicts, consensus_sequences, mlst_consensus, run_times, outdir, time_str):
+    if mlst_consensus == 'all':
+        for consensus_type in consensus_sequences:
+            print('Searching MLST for ' + consensus_type + ' consensus')
+            st, alleles_profile = check_mlst.get_st(mlst_dicts, consensus_sequences[consensus_type])
+            write_mlst_report(sample, run_times, consensus_type, st, alleles_profile, mlst_dicts[2], outdir, time_str)
+            print('ST found: ' + str(st) + ' (' + alleles_profile + ')')
+    else:
+        st, alleles_profile = check_mlst.get_st(mlst_dicts, consensus_sequences[mlst_consensus])
+        write_mlst_report(sample, run_times, mlst_consensus, st, alleles_profile, mlst_dicts[2], outdir, time_str)
+        print('ST found for ' + mlst_consensus + ' consensus: ' + str(st) + ' (' + alleles_profile + ')')
+
+
+def write_summary_report(outdir, reported_data_type, time_str, gene_list_reference, genes_present):
+    with open(os.path.join(outdir,
+                           'summary.{reported_data_type}.{time_str}.tab'.format(reported_data_type=reported_data_type,
+                                                                                time_str=time_str)), 'wt') as writer:
+        seq_list = []
+        for info in list(genes_present.values()):
+            seq_list.extend(list(info.keys()))
+            seq_list = list(set(seq_list))
+        writer.write('#sample' + '\t' + '\t'.join([gene_list_reference[seq] for seq in sorted(seq_list)]) + '\n')
+        for sample, info in list(genes_present.items()):
+            data = []
+            for seq in sorted(seq_list):
+                if seq in info:
+                    data.append(info[seq])
+                else:
+                    data.append('NF')
+            writer.write(sample + '\t' + '\t'.join(data) + '\n')
+
+
+def run_rematch(args):
+    workdir = os.path.abspath(args.workdir)
+    if not os.path.isdir(workdir):
+        os.makedirs(workdir)
+
+    aspera_key = os.path.abspath(args.asperaKey.name) if args.asperaKey is not None else None
+
+    # Start logger
+    logfile, time_str = utils.start_logger(workdir)
+
+    # Get general information
+    script_path = utils.general_information(logfile, __version__, workdir, time_str, args.doNotUseProvidedSoftware,
+                                            aspera_key, args.downloadCramBam, args.SRA, args.SRAopt)
+
+    # Set list_ids
+    list_ids, searched_fastq_files = get_list_ids(workdir, args.listIDs.name if args.listIDs is not None else None,
+                                                  args.taxon)
+
+    mlst_sequences = None
+    mlst_dicts = None
+    if args.mlst is not None:
+        time_taken_pub_mlst, mlst_dicts, mlst_sequences = check_mlst.download_pub_mlst_xml(args.mlst,
+                                                                                           args.mlstSchemaNumber,
+                                                                                           workdir)
+        args.softClip_recodeRun = 'first'
+
+    if args.reference is None:
+        if args.mlst is not None:
+            reference_file = check_mlst.check_existing_schema(args.mlst, args.mlstSchemaNumber, script_path)
+            args.extraSeq = 200
+            if reference_file is None:
+                print('It was not found provided MLST scheme sequences for ' + args.mlst)
+                print('Trying to obtain reference MLST sequences from PubMLST')
+                if len(mlst_sequences) > 0:
+                    reference_file = check_mlst.write_mlst_reference(args.mlst, mlst_sequences, workdir, time_str)
+                    args.extraSeq = 0
+                else:
+                    sys.exit('It was not possible to download MLST sequences from PubMLST!')
+            else:
+                print('Using provided scheme as referece: ' + reference_file)
+        else:
+            sys.exit('Need to provide at least one of the following options: "--reference" and "--mlst"')
+    else:
+        reference_file = os.path.abspath(args.reference.name)
+
+    # Run ReMatCh for each sample
+    print('\n' + 'STARTING ReMatCh' + '\n')
+
+    # Clean sequences headers
+    reference_file, gene_list_reference, reference_dict = clean_headers_reference_file(reference_file, workdir,
+                                                                                       args.extraSeq)
+
+    if args.mlst is not None:
+        problem_genes = False
+        for header in mlst_sequences:
+            if header not in gene_list_reference:
+                print('MLST gene {header} not found between reference sequences'.format(header=header))
+                problem_genes = True
+        if problem_genes:
+            sys.exit('Missing MLST genes from reference sequences (at least sequences names do not match)!')
+
+    if len(gene_list_reference) == 0:
+        sys.exit('No sequences left')
+
+    # To use in combined report
+
+    number_samples_successfully = 0
+    genes_present_coverage_depth = {}
+    genes_present_sequence_coverage = {}
+    for sample in list_ids:
+        sample_start_time = time.time()
+        print('\n\n' + 'Sample ID: ' + sample)
+
+        # Create sample outdir
+        sample_outdir = os.path.join(workdir, sample, '')
+        if not os.path.isdir(sample_outdir):
+            os.mkdir(sample_outdir)
+
+        run_successfully_fastq = None
+        time_taken_fastq = 0
+        sequencing_information = {'run_accession': None, 'instrument_platform': None, 'instrument_model': None,
+                                  'library_layout': None, 'library_source': None, 'extra_run_accession': None,
+                                  'nominal_length': None, 'read_count': None, 'base_count': None, 'date_download': None}
+        if not searched_fastq_files:
+            # Download Files
+            time_taken_fastq, run_successfully_fastq, fastq_files, sequencing_information = \
+                download.run_download(sample, args.downloadLibrariesType, aspera_key, sample_outdir,
+                                      args.downloadCramBam, args.threads, args.downloadInstrumentPlatform, args.SRA,
+                                      args.SRAopt)
+        else:
+            fastq_files = list_ids[sample]
+
+        file_size = None
+
+        run_successfully_rematch_first = None
+        run_successfully_rematch_second = None
+        time_taken_rematch_first = 0
+        time_taken_rematch_second = 0
+        sample_data_general_first = None
+        sample_data_general_second = None
+        if run_successfully_fastq is not False:
+            file_size = sum(os.path.getsize(fastq) for fastq in fastq_files)
+            # Run ReMatCh
+            time_taken_rematch_first, run_successfully_rematch_first, data_by_gene, sample_data_general_first, \
+            consensus_files, consensus_sequences = \
+                rematch_module.run_rematch_module(sample, fastq_files, reference_file, args.threads, sample_outdir,
+                                                  args.extraSeq, args.minCovPresence, args.minCovCall,
+                                                  args.minFrequencyDominantAllele, args.minGeneCoverage,
+                                                  args.debug, args.numMapLoc, args.minGeneIdentity,
+                                                  'first', args.softClip_baseQuality, args.softClip_recodeRun,
+                                                  reference_dict, args.softClip_cigarFlagRecode,
+                                                  args.bowtieAlgo, args.bowtieOPT,
+                                                  gene_list_reference, args.notWriteConsensus, clean_run=True)
+            if run_successfully_rematch_first:
+                if args.mlst is not None and (args.mlstRun == 'first' or args.mlstRun == 'all'):
+                    run_get_st(sample, mlst_dicts, consensus_sequences, args.mlstConsensus, 'first', workdir, time_str)
+                genes_present_coverage_depth = write_data_by_gene(gene_list_reference, args.minGeneCoverage, sample,
+                                                                  data_by_gene, workdir, time_str, 'first_run',
+                                                                  args.minGeneIdentity, 'coverage_depth', args.summary,
+                                                                  genes_present_coverage_depth)
+                if args.reportSequenceCoverage:
+                    genes_present_sequence_coverage = write_data_by_gene(gene_list_reference, args.minGeneCoverage,
+                                                                         sample, data_by_gene, workdir, time_str,
+                                                                         'first_run', args.minGeneIdentity,
+                                                                         'sequence_coverage', args.summary,
+                                                                         genes_present_sequence_coverage)
+                if args.doubleRun:
+                    rematch_second_outdir = os.path.join(sample_outdir, 'rematch_second_run', '')
+                    if not os.path.isdir(rematch_second_outdir):
+                        os.mkdir(rematch_second_outdir)
+                    consensus_concatenated_fasta, consensus_concatenated_gene_list, consensus_concatenated_dict, \
+                    number_consensus_with_sequences = \
+                        concatenate_extra_seq_2_consensus(consensus_files['noMatter'], reference_file, args.extraSeq,
+                                                          rematch_second_outdir)
+                    if len(consensus_concatenated_gene_list) > 0:
+                        if args.mlst is None or \
+                                (args.mlst is not None and number_consensus_with_sequences == len(gene_list_reference)):
+                            time_taken_rematch_second, run_successfully_rematch_second, data_by_gene, \
+                            sample_data_general_second, consensus_files, consensus_sequences = \
+                                rematch_module.run_rematch_module(sample, fastq_files, consensus_concatenated_fasta,
+                                                                  args.threads, rematch_second_outdir, args.extraSeq,
+                                                                  args.minCovPresence, args.minCovCall,
+                                                                  args.minFrequencyDominantAllele, args.minGeneCoverage,
+                                                                  args.debug, args.numMapLoc,
+                                                                  args.minGeneIdentity, 'second',
+                                                                  args.softClip_baseQuality, args.softClip_recodeRun,
+                                                                  consensus_concatenated_dict,
+                                                                  args.softClip_cigarFlagRecode,
+                                                                  args.bowtieAlgo, args.bowtieOPT,
+                                                                  gene_list_reference, args.notWriteConsensus,
+                                                                  clean_run=True)
+                            if not args.debug:
+                                os.remove(consensus_concatenated_fasta)
+                            if run_successfully_rematch_second:
+                                if args.mlst is not None and (args.mlstRun == 'second' or args.mlstRun == 'all'):
+                                    run_get_st(sample, mlst_dicts, consensus_sequences, args.mlstConsensus, 'second',
+                                               workdir, time_str)
+                                _ = write_data_by_gene(gene_list_reference, args.minGeneCoverage, sample, data_by_gene,
+                                                       workdir, time_str, 'second_run', args.minGeneIdentity,
+                                                       'coverage_depth', False, {})
+                                if args.reportSequenceCoverage:
+                                    _ = write_data_by_gene(gene_list_reference, args.minGeneCoverage, sample,
+                                                           data_by_gene, workdir, time_str, 'second_run',
+                                                           args.minGeneIdentity, 'sequence_coverage', False, {})
+                        else:
+                            print('Some sequences missing after ReMatCh module first run. Second run will not be'
+                                  ' performed')
+                            if os.path.isfile(consensus_concatenated_fasta):
+                                os.remove(consensus_concatenated_fasta)
+                            if os.path.isdir(rematch_second_outdir):
+                                utils.remove_directory(rematch_second_outdir)
+                    else:
+                        print('No sequences left after ReMatCh module first run. Second run will not be performed')
+                        if os.path.isfile(consensus_concatenated_fasta):
+                            os.remove(consensus_concatenated_fasta)
+                        if os.path.isdir(rematch_second_outdir):
+                            utils.remove_directory(rematch_second_outdir)
+
+        if not searched_fastq_files and not args.keepDownloadedFastq and fastq_files is not None:
+            for fastq in fastq_files:
+                if os.path.isfile(fastq):
+                    os.remove(fastq)
+
+        time_taken = utils.run_time(sample_start_time)
+
+        write_sample_report(sample, workdir, time_str, file_size, run_successfully_fastq,
+                            run_successfully_rematch_first, run_successfully_rematch_second, time_taken_fastq,
+                            time_taken_rematch_first, time_taken_rematch_second, time_taken, sequencing_information,
+                            sample_data_general_first if run_successfully_rematch_first else
+                            {'number_absent_genes': None, 'number_genes_multiple_alleles': None,
+                             'mean_sample_coverage': None},
+                            sample_data_general_second if run_successfully_rematch_second else
+                            {'number_absent_genes': None, 'number_genes_multiple_alleles': None,
+                             'mean_sample_coverage': None},
+                            fastq_files if fastq_files is not None else '')
+
+        if all([run_successfully_fastq is not False,
+                run_successfully_rematch_first is not False,
+                run_successfully_rematch_second is not False]):
+            number_samples_successfully += 1
+
+    if args.summary:
+        write_summary_report(workdir, 'coverage_depth', time_str, gene_list_reference, genes_present_coverage_depth)
+        if args.reportSequenceCoverage:
+            write_summary_report(workdir, 'sequence_coverage', time_str, gene_list_reference,
+                                 genes_present_sequence_coverage)
+
+    return number_samples_successfully, len(list_ids)
+
+
+def main():
+    if sys.version_info[0] < 3:
+        sys.exit('Must be using Python 3. Try calling "python3 rematch.py"')
+
+    parser = argparse.ArgumentParser(prog='rematch.py',
+                                     description='Reads mapping against target sequences, checking mapping and'
+                                                 ' consensus sequences production',
+                                     formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+    parser.add_argument('--version', help='Version information', action='version',
+                        version='{prog} v{version}'.format(prog=parser.prog, version=__version__))
+
+    parser_optional_general = parser.add_argument_group('General facultative options')
+    parser_optional_general.add_argument('-r', '--reference', type=argparse.FileType('r'),
+                                         metavar='/path/to/reference_sequence.fasta',
+                                         help='Fasta file containing reference sequences', required=False)
+    parser_optional_general.add_argument('-w', '--workdir', type=str, metavar='/path/to/workdir/directory/',
+                                         help='Path to the directory where ReMatCh will run and produce the outputs'
+                                              ' with reads (ended with fastq.gz/fq.gz and, in case of PE data, pair-end'
+                                              ' direction coded as _R1_001 / _R2_001 or _1 / _2) already'
+                                              ' present (organized in sample folders) or to be downloaded',
+                                         required=False, default='.')
+    parser_optional_general.add_argument('-j', '--threads', type=int, metavar='N', help='Number of threads to use',
+                                         required=False, default=1)
+    parser_optional_general.add_argument('--mlst', type=str, metavar='"Streptococcus agalactiae"',
+                                         help='Species name (same as in PubMLST) to be used in MLST'
+                                              ' determination. ReMatCh will use Bowtie2 very-sensitive-local mapping'
+                                              ' parameters and will recode the soft clip CIGAR flags of the first run',
+                                         required=False)
+    parser_optional_general.add_argument('--doNotUseProvidedSoftware', action='store_true',
+                                         help='Tells ReMatCh to not use Bowtie2, Samtools and Bcftools that are'
+                                              ' provided with it')
+
+    parser_optional_download_exclusive = parser.add_mutually_exclusive_group()
+    parser_optional_download_exclusive.add_argument('-l', '--listIDs', type=argparse.FileType('r'),
+                                                    metavar='/path/to/list_IDs.txt',
+                                                    help='Path to list containing the IDs to be'
+                                                         ' downloaded (one per line)', required=False)
+    parser_optional_download_exclusive.add_argument('-t', '--taxon', type=str, metavar='"Streptococcus agalactiae"',
+                                                    help='Taxon name for which ReMatCh will download fastq files',
+                                                    required=False)
+
+    parser_optional_rematch = parser.add_argument_group('ReMatCh module facultative options')
+    parser_optional_rematch.add_argument('--extraSeq', type=int, metavar='N',
+                                         help='Sequence length added to both ends of target sequences (usefull to'
+                                              ' improve reads mapping to the target one) that will be trimmed in'
+                                              ' ReMatCh outputs', required=False, default=0)
+    parser_optional_rematch.add_argument('--minCovPresence', type=int, metavar='N',
+                                         help='Reference position minimum coverage depth to consider the position to be'
+                                              ' present in the sample', required=False, default=5)
+    parser_optional_rematch.add_argument('--minCovCall', type=int, metavar='N',
+                                         help='Reference position minimum coverage depth to perform a base call. Lower'
+                                              ' coverage will be coded as N', required=False, default=10)
+    parser_optional_rematch.add_argument('--minFrequencyDominantAllele', type=float, metavar='0.6',
+                                         help='Minimum relative frequency of the dominant allele coverage depth (value'
+                                              ' between [0, 1]). Positions with lower values will be considered as'
+                                              ' having multiple alleles (and will be coded as N)', required=False,
+                                         default=0.6)
+    parser_optional_rematch.add_argument('--minGeneCoverage', type=int, metavar='N',
+                                         help='Minimum percentage of target reference gene sequence covered'
+                                              ' by --minCovPresence to consider a gene to be present (value'
+                                              ' between [0, 100])', required=False, default=70)
+    parser_optional_rematch.add_argument('--minGeneIdentity', type=int, metavar='N',
+                                         help='Minimum percentage of identity of reference gene sequence covered'
+                                              ' by --minCovCall to consider a gene to be present (value'
+                                              ' between [0, 100]). One INDEL will be considered as one difference',
+                                         required=False, default=80)
+    parser_optional_rematch.add_argument('--numMapLoc', type=int, metavar='N', help=argparse.SUPPRESS, required=False,
+                                         default=1)
+    # parser_optional_rematch.add_argument('--numMapLoc', type=int, metavar='N', help='Maximum number of locations to which a read can map (sometimes useful when mapping against similar sequences)', required=False, default=1)
+    parser_optional_rematch.add_argument('--doubleRun', action='store_true',
+                                         help='Tells ReMatCh to run a second time using as reference the noMatter'
+                                              ' consensus sequence produced in the first run. This will improve'
+                                              ' consensus sequence determination for sequences with high percentage of'
+                                              ' target reference gene sequence covered')
+    parser_optional_rematch.add_argument('--reportSequenceCoverage', action='store_true',
+                                         help='Produce an extra combined_report.data_by_gene with the sequence coverage'
+                                              ' instead of coverage depth')
+    parser_optional_rematch.add_argument('--summary', action='store_true',
+                                         help='Produce extra report files containing only sequences present in at least'
+                                              ' one sample (usefull when using a large number of reference'
+                                              ' sequences, and only for first run)')
+    parser_optional_rematch.add_argument('--notWriteConsensus', action='store_true',
+                                         help='Do not write consensus sequences')
+    parser_optional_rematch.add_argument('--bowtieAlgo', type=str, metavar='"--very-sensitive-local"',
+                                         help='Bowtie2 alignment mode. It can be an end-to-end alignment (unclipped'
+                                              ' alignment) or local alignment (soft clipped alignment). Also, can'
+                                              ' choose between fast or sensitive alignments. Please check Bowtie2'
+                                              ' manual for extra'
+                                              ' information: http://bowtie-bio.sourceforge.net/bowtie2/index.shtml .'
+                                              ' This option should be provided between quotes and starting with'
+                                              ' an empty space (like --bowtieAlgo " --very-fast") or using equal'
+                                              ' sign (like --bowtieAlgo="--very-fast")',
+                                         required=False, default='--very-sensitive-local')
+    parser_optional_rematch.add_argument('--bowtieOPT', type=str, metavar='"--no-mixed"',
+                                         help='Extra Bowtie2 options. This option should be provided between quotes and'
+                                              ' starting with an empty space (like --bowtieOPT " --no-mixed") or using'
+                                              ' equal sign (like --bowtieOPT="--no-mixed")',
+                                         required=False)
+    parser_optional_rematch.add_argument('--debug', action='store_true',
+                                         help='DeBug Mode: do not remove temporary files')
+
+    parser_optional_mlst = parser.add_argument_group('MLST facultative options')
+    parser_optional_rematch.add_argument('--mlstReference', action='store_true',
+                                         help='If the curated scheme for MLST alleles is available, tells ReMatCh to'
+                                              ' use these as reference (force Bowtie2 to run with very-sensitive-local'
+                                              ' parameters, and sets --extraSeq to 200), otherwise ReMatCh uses the'
+                                              ' first alleles of each MLST gene fragment in PubMLST as reference'
+                                              ' sequences (force Bowtie2 to run with very-sensitive-local parameters,'
+                                              ' and sets --extraSeq to 0)')
+    parser_optional_mlst.add_argument('--mlstSchemaNumber', type=int, metavar='N',
+                                      help='Number of the species PubMLST schema to be used in case of multiple schemes'
+                                           ' available (by default will use the first schema)', required=False)
+    parser_optional_mlst.add_argument('--mlstConsensus', choices=['noMatter', 'correct', 'alignment', 'all'], type=str,
+                                      metavar='noMatter',
+                                      help='Consensus sequence to be used in MLST'
+                                           ' determination (available options: %(choices)s)', required=False,
+                                      default='noMatter')
+    parser_optional_mlst.add_argument('--mlstRun', choices=['first', 'second', 'all'], type=str, metavar='first',
+                                      help='ReMatCh run outputs to be used in MLST determination (available'
+                                           ' options: %(choices)s)', required=False, default='all')
+
+    parser_optional_download = parser.add_argument_group('Download facultative options')
+    parser_optional_download.add_argument('-a', '--asperaKey', type=argparse.FileType('r'),
+                                          metavar='/path/to/asperaweb_id_dsa.openssh',
+                                          help='Tells ReMatCh to download fastq files from ENA using Aspera'
+                                               ' Connect. With this option, the path to Private-key file'
+                                               ' asperaweb_id_dsa.openssh must be provided (normaly found in'
+                                               ' ~/.aspera/connect/etc/asperaweb_id_dsa.openssh).', required=False)
+    parser_optional_download.add_argument('-k', '--keepDownloadedFastq', action='store_true',
+                                          help='Tells ReMatCh to keep the fastq files downloaded')
+    parser_optional_download.add_argument('--downloadLibrariesType', type=str, metavar='PAIRED',
+                                          help='Tells ReMatCh to download files with specific library'
+                                               ' layout (available options: %(choices)s)',
+                                          choices=['PAIRED', 'SINGLE', 'BOTH'], required=False, default='BOTH')
+    parser_optional_download.add_argument('--downloadInstrumentPlatform', type=str, metavar='ILLUMINA',
+                                          help='Tells ReMatCh to download files with specific library layout (available'
+                                               ' options: %(choices)s)', choices=['ILLUMINA', 'ALL'], required=False,
+                                          default='ILLUMINA')
+    parser_optional_download.add_argument('--downloadCramBam', action='store_true',
+                                          help='Tells ReMatCh to also download cram/bam files and convert them to fastq'
+                                               ' files')
+
+    parser_optional_sra = parser.add_mutually_exclusive_group()
+    parser_optional_sra.add_argument('--SRA', action='store_true',
+                                     help='Tells getSeqENA.py to download reads in fastq format only from NCBI SRA'
+                                          ' database (not recommended)')
+    parser_optional_sra.add_argument('--SRAopt', action='store_true',
+                                     help='Tells getSeqENA.py to download reads from NCBI SRA if the download from ENA'
+                                          ' fails')
+
+    parser_optional_soft_clip = parser.add_argument_group('Soft clip facultative options')
+    parser_optional_soft_clip.add_argument('--softClip_baseQuality', type=int, metavar='N',
+                                           help='Base quality phred score in reads soft clipped regions',
+                                           required=False,
+                                           default=7)
+    parser_optional_soft_clip.add_argument('--softClip_recodeRun', type=str, metavar='first',
+                                           help='ReMatCh run to recode soft clipped regions (available'
+                                                ' options: %(choices)s)', choices=['first', 'second', 'both', 'none'],
+                                           required=False, default='none')
+    parser_optional_soft_clip.add_argument('--softClip_cigarFlagRecode', type=str, metavar='M',
+                                           help='CIGAR flag to recode CIGAR soft clip (available options: %(choices)s)',
+                                           choices=['M', 'I', 'X'], required=False, default='X')
+
+    args = parser.parse_args()
+
+    msg = []
+    if args.reference is None and not args.mlstReference:
+        msg.append('At least --reference or --mlstReference should be provided')
+    elif args.reference is not None and args.mlstReference:
+        msg.append('Only --reference or --mlstReference should be provided')
+    else:
+        if args.mlstReference:
+            if args.mlst is None:
+                msg.append('Please provide species name using --mlst')
+    if args.minFrequencyDominantAllele < 0 or args.minFrequencyDominantAllele > 1:
+        msg.append('--minFrequencyDominantAllele should be a value between [0, 1]')
+    if args.minGeneCoverage < 0 or args.minGeneCoverage > 100:
+        msg.append('--minGeneCoverage should be a value between [0, 100]')
+    if args.minGeneIdentity < 0 or args.minGeneIdentity > 100:
+        msg.append('--minGeneIdentity should be a value between [0, 100]')
+    if args.notWriteConsensus and args.doubleRun:
+        msg.append('--notWriteConsensus and --doubleRun cannot be used together.'
+                   ' Maybe you only want to use --doubleRun')
+
+    if len(msg) > 0:
+        argparse.ArgumentParser.error('\n'.join(msg))
+
+    start_time = time.time()
+
+    number_samples_successfully, samples_total_number = run_rematch(args)
+
+    print('\n' + 'END ReMatCh')
+    print('\n' +
+          str(number_samples_successfully) + ' samples out of ' + str(samples_total_number) + ' run successfully')
+    time_taken = utils.run_time(start_time)
+    del time_taken
+
+    if number_samples_successfully == 0:
+        sys.exit('No samples run successfully!')
+
+
+if __name__ == "__main__":
+    main()