############################################################################ # Copyright (c) 2015-2022 Saint Petersburg State University # Copyright (c) 2011-2015 Saint Petersburg Academic University # All Rights Reserved # See file LICENSE for details. ############################################################################ import os from quast_libs import qconfig, qutils from quast_libs.log import get_logger from quast_libs.qutils import val_to_str logger = get_logger(qconfig.LOGGER_DEFAULT_NAME) try: basestring except: basestring = (str, bytes) # Here you can modify content and order of metrics in QUAST reports and names of metrcis as well class Fields: #################################################################################### ########################### CONFIGURABLE PARAMETERS ############################## #################################################################################### ### for indent before submetrics TAB = ' ' HALF_TAB = ' ' ### List of available fields for reports. Values (strings) should be unique! ### # Header NAME = 'Assembly' # Basic statistics CONTIGS = '# contigs' CONTIGS__FOR_THRESHOLDS = ('# contigs (>= %d bp)', tuple(qconfig.contig_thresholds)) LARGCONTIG = 'Largest contig' TOTALLEN = 'Total length' TOTALLENS__FOR_THRESHOLDS = ('Total length (>= %d bp)', tuple(qconfig.contig_thresholds)) TOTALLENS__FOR_1000_THRESHOLD = 'Total length (>= 1000 bp)' TOTALLENS__FOR_10000_THRESHOLD = 'Total length (>= 10000 bp)' TOTALLENS__FOR_50000_THRESHOLD = 'Total length (>= 50000 bp)' N50 = 'N50' auN = 'auN' auNG = 'auNG' auNA = 'auNA' auNGA = 'auNGA' Nx = 'N%d' % qconfig.x_for_additional_Nx L50 = 'L50' Lx = 'L%d' % qconfig.x_for_additional_Nx GC = 'GC (%)' # Read statistics MAPPED_READS = '# mapped' MAPPED_READS_PCNT = 'Mapped (%)' PROPERLY_PAIRED_READS = '# properly paired' PROPERLY_PAIRED_READS_PCNT = 'Properly paired (%)' SINGLETONS = '# singletons' SINGLETONS_PCNT = 'Singletons (%)' MISJOINT_READS = '# misjoint mates' MISJOINT_READS_PCNT = 'Misjoint mates (%)' DEPTH = 'Avg. coverage depth' COVERAGE__FOR_THRESHOLDS = ('Coverage >= %dx (%%)', tuple(qconfig.coverage_thresholds)) COVERAGE_1X_THRESHOLD = 'Coverage >= 1x (%)' COVERAGE_5X_THRESHOLD = 'Coverage >= 5x (%)' COVERAGE_10X_THRESHOLD = 'Coverage >= 10x (%)' # Misassemblies MISASSEMBL = '# misassemblies' MISCONTIGS = '# misassembled contigs' MISCONTIGSBASES = 'Misassembled contigs length' MISINTERNALOVERLAP = 'Misassemblies inter-contig overlap' ### additional list of metrics for detailed misassemblies report LARGE_MIS_EXTENSIVE = '# large blocks misassemblies' LARGE_MIS_RELOCATION = TAB + '# large relocations' LARGE_MIS_TRANSLOCATION = TAB + '# large translocations' LARGE_MIS_INVERTION = TAB + '# large inversions' LARGE_MIS_ISTRANSLOCATIONS = TAB + '# large i/s translocations' ### additional list of metrics for detailed misassemblies report MIS_ALL_EXTENSIVE = '# misassemblies' MIS_RELOCATION = TAB + '# relocations' MIS_TRANSLOCATION = TAB + '# translocations' MIS_INVERTION = TAB + '# inversions' MIS_ISTRANSLOCATIONS = TAB + '# interspecies translocations' MIS_EXTENSIVE_CONTIGS = '# misassembled contigs' MIS_EXTENSIVE_BASES = 'Misassembled contigs length' MIS_LOCAL = '# local misassemblies' MIS_SCAFFOLDS_GAP = '# scaffold gap ext. mis.' MIS_LOCAL_SCAFFOLDS_GAP = '# scaffold gap loc. mis.' MIS_FRAGMENTED = '# misassemblies caused by fragmented reference' CONTIGS_WITH_ISTRANSLOCATIONS = '# possibly misassembled contigs' POSSIBLE_MISASSEMBLIES = TAB + '# possible misassemblies' POTENTIAL_MGE = '# possible TEs' # former MGEs -- mobile genetic elements ### structural variations STRUCT_VARIATIONS = '# structural variations' # Special case: metrics for separating Contig/Scaffold misassemblies in detailed misassemblies report CTG_MIS_ALL_EXTENSIVE = HALF_TAB + '# contig misassemblies' CTG_MIS_RELOCATION = TAB + '# c. relocations' CTG_MIS_TRANSLOCATION = TAB + '# c. translocations' CTG_MIS_INVERTION = TAB + '# c. inversions' CTG_MIS_ISTRANSLOCATIONS = TAB + '# c. interspecies translocations' SCF_MIS_ALL_EXTENSIVE = HALF_TAB + '# scaffold misassemblies' SCF_MIS_RELOCATION = TAB + '# s. relocations' SCF_MIS_TRANSLOCATION = TAB + '# s. translocations' SCF_MIS_INVERTION = TAB + '# s. inversions' SCF_MIS_ISTRANSLOCATIONS = TAB + '# s. interspecies translocations' # Unaligned UNALIGNED = '# unaligned contigs' UNALIGNEDBASES = 'Unaligned length' AMBIGUOUS = '# ambiguously mapped contigs' AMBIGUOUSEXTRABASES = 'Extra bases in ambiguously mapped contigs' MISLOCAL = '# local misassemblies' ### additional list of metrics for detailed unaligned report UNALIGNED_FULL_CNTGS = '# fully unaligned contigs' UNALIGNED_FULL_LENGTH = 'Fully unaligned length' UNALIGNED_PART_CNTGS = '# partially unaligned contigs' UNALIGNED_PART_LENGTH = 'Partially unaligned length' UNALIGNED_MISASSEMBLED_CTGS = '# unaligned mis. contigs' # Indels and mismatches MISMATCHES = '# mismatches' INDELS = '# indels' INDELSBASES = 'Indels length' SUBSERROR = '# mismatches per 100 kbp' INDELSERROR = '# indels per 100 kbp' MIS_SHORT_INDELS = TAB + '# indels (<= 5 bp)' MIS_LONG_INDELS = TAB + '# indels (> 5 bp)' UNCALLED = "# N's" UNCALLED_PERCENT = "# N's per 100 kbp" # Genome statistics MAPPEDGENOME = 'Genome fraction (%)' DUPLICATION_RATIO = 'Duplication ratio' AVE_READ_SUPPORT = 'Avg contig read support' GENES = '# genomic features' OPERONS = '# operons' LARGALIGN = 'Largest alignment' TOTAL_ALIGNED_LEN = 'Total aligned length' NG50 = 'NG50' NA50 = 'NA50' NGA50 = 'NGA50' LG50 = 'LG50' LA50 = 'LA50' LGA50 = 'LGA50' NGx = 'NG%d' % qconfig.x_for_additional_Nx NAx = 'NA%d' % qconfig.x_for_additional_Nx NGAx = 'NGA%d' % qconfig.x_for_additional_Nx LGx = 'LG%d' % qconfig.x_for_additional_Nx LAx = 'LA%d' % qconfig.x_for_additional_Nx LGAx = 'LGA%d' % qconfig.x_for_additional_Nx # Unique k-mer statistics KMER_COMPLETENESS = 'K-mer-based compl. (%)' KMER_CORR_LENGTH = 'K-mer-based cor. length (%)' KMER_MIS_LENGTH = 'K-mer-based mis. length (%)' KMER_UNDEF_LENGTH = 'K-mer-based undef. length (%)' KMER_MISASSEMBLIES = '# k-mer-based misjoins' KMER_TRANSLOCATIONS = TAB + '# k-mer-based translocations' KMER_RELOCATIONS = TAB + '# k-mer-based 100kbp relocations' # Predicted genes PREDICTED_GENES_UNIQUE = '# predicted genes (unique)' PREDICTED_GENES = ('# predicted genes (>= %d bp)', tuple(qconfig.genes_lengths)) RNA_GENES = '# predicted rRNA genes' BUSCO_COMPLETE = 'Complete BUSCO (%)' BUSCO_PART = 'Partial BUSCO (%)' # Reference statistics REFLEN = 'Reference length' ESTREFLEN = 'Estimated reference length' REF_FRAGMENTS = 'Reference fragments' REFGC = 'Reference GC (%)' REF_GENES = 'Reference genomic features' REF_OPERONS = 'Reference operons' # Reads statistics TOTAL_READS = '# total reads' LEFT_READS = '# left' RIGHT_READS = '# right' REF_MAPPED_READS = '# reference mapped' REF_MAPPED_READS_PCNT = 'Reference mapped (%)' REF_PROPERLY_PAIRED_READS = '# reference properly paired' REF_PROPERLY_PAIRED_READS_PCNT = 'Reference properly paired (%)' REF_SINGLETONS = '# reference singletons' REF_SINGLETONS_PCNT = 'Reference singletons (%)' REF_MISJOINT_READS = '# reference misjoint mates' REF_MISJOINT_READS_PCNT = 'Reference misjoint mates (%)' REF_DEPTH = 'Reference avg. coverage depth' REF_COVERAGE__FOR_THRESHOLDS = ('Reference coverage >= %dx (%%)', tuple(qconfig.coverage_thresholds)) REF_COVERAGE_1X_THRESHOLD = 'Reference coverage >= 1x (%)' REF_COVERAGE_5X_THRESHOLD = 'Reference coverage >= 5x (%)' REF_COVERAGE_10X_THRESHOLD = 'Reference coverage >= 10x (%)' # Icarus statistics SIMILAR_CONTIGS = '# similar correct contigs' SIMILAR_MIS_BLOCKS = '# similar misassembled blocks' ### content and order of metrics in MAIN REPORT (/report.txt, .tex, .tsv): order = [NAME, CONTIGS__FOR_THRESHOLDS, TOTALLENS__FOR_THRESHOLDS, CONTIGS, LARGCONTIG, TOTALLEN, REFLEN, ESTREFLEN, GC, REFGC, N50, NG50, Nx, NGx, auN, auNG, L50, LG50, Lx, LGx, TOTAL_READS, LEFT_READS, RIGHT_READS, MAPPED_READS_PCNT, REF_MAPPED_READS_PCNT, PROPERLY_PAIRED_READS_PCNT, REF_PROPERLY_PAIRED_READS_PCNT, DEPTH, REF_DEPTH, COVERAGE_1X_THRESHOLD, REF_COVERAGE_1X_THRESHOLD, LARGE_MIS_EXTENSIVE, MISASSEMBL, MISCONTIGS, MISCONTIGSBASES, MISLOCAL, MIS_SCAFFOLDS_GAP, MIS_LOCAL_SCAFFOLDS_GAP, STRUCT_VARIATIONS, POTENTIAL_MGE, UNALIGNED_MISASSEMBLED_CTGS, UNALIGNED, UNALIGNEDBASES, MAPPEDGENOME, DUPLICATION_RATIO, AVE_READ_SUPPORT, UNCALLED_PERCENT, SUBSERROR, INDELSERROR, GENES, OPERONS, BUSCO_COMPLETE, BUSCO_PART, PREDICTED_GENES_UNIQUE, PREDICTED_GENES, RNA_GENES, LARGALIGN, TOTAL_ALIGNED_LEN, NA50, NGA50, NAx, NGAx, auNA, auNGA, LA50, LGA50, LAx, LGAx, KMER_COMPLETENESS, KMER_CORR_LENGTH, KMER_MIS_LENGTH, KMER_MISASSEMBLIES] reads_order = [NAME, TOTAL_READS, LEFT_READS, RIGHT_READS, MAPPED_READS, MAPPED_READS_PCNT, PROPERLY_PAIRED_READS, PROPERLY_PAIRED_READS_PCNT, SINGLETONS, SINGLETONS_PCNT, MISJOINT_READS, MISJOINT_READS_PCNT, DEPTH, COVERAGE__FOR_THRESHOLDS, REF_MAPPED_READS, REF_MAPPED_READS_PCNT, REF_PROPERLY_PAIRED_READS, REF_PROPERLY_PAIRED_READS_PCNT, REF_SINGLETONS, REF_SINGLETONS_PCNT, REF_MISJOINT_READS, REF_MISJOINT_READS_PCNT, REF_DEPTH, REF_COVERAGE__FOR_THRESHOLDS] # content and order of metrics in DETAILED MISASSEMBLIES REPORT (/contigs_reports/misassemblies_report.txt, .tex, .tsv) classic_misassemblies_order = [MIS_RELOCATION, MIS_TRANSLOCATION, MIS_INVERTION, MIS_ISTRANSLOCATIONS] ctg_scf_misassemblies_order = [CTG_MIS_ALL_EXTENSIVE, CTG_MIS_RELOCATION, CTG_MIS_TRANSLOCATION, CTG_MIS_INVERTION, CTG_MIS_ISTRANSLOCATIONS, SCF_MIS_ALL_EXTENSIVE, SCF_MIS_RELOCATION, SCF_MIS_TRANSLOCATION, SCF_MIS_INVERTION, SCF_MIS_ISTRANSLOCATIONS] prefix_misassemblies_order = [NAME, MIS_ALL_EXTENSIVE] suffix_misassemblies_order = [MIS_EXTENSIVE_CONTIGS, MIS_EXTENSIVE_BASES, CONTIGS_WITH_ISTRANSLOCATIONS, POSSIBLE_MISASSEMBLIES, MIS_LOCAL, MIS_SCAFFOLDS_GAP, MIS_LOCAL_SCAFFOLDS_GAP, MIS_FRAGMENTED, STRUCT_VARIATIONS, POTENTIAL_MGE, UNALIGNED_MISASSEMBLED_CTGS, MISMATCHES, INDELS, MIS_SHORT_INDELS, MIS_LONG_INDELS, INDELSBASES] misassemblies_order = prefix_misassemblies_order + classic_misassemblies_order + suffix_misassemblies_order misassemblies_order_advanced = prefix_misassemblies_order + ctg_scf_misassemblies_order + suffix_misassemblies_order # content and order of metrics in DETAILED UNALIGNED REPORT (/contigs_reports/unaligned_report.txt, .tex, .tsv) unaligned_order = [NAME, UNALIGNED_FULL_CNTGS, UNALIGNED_FULL_LENGTH, UNALIGNED_PART_CNTGS, UNALIGNED_PART_LENGTH, UNCALLED] kmers_order = [NAME, KMER_COMPLETENESS, KMER_CORR_LENGTH, KMER_MIS_LENGTH, KMER_UNDEF_LENGTH, KMER_MISASSEMBLIES, KMER_TRANSLOCATIONS, KMER_RELOCATIONS] ### Grouping of metrics and set of main metrics for HTML version of main report grouped_order = [ ('Genome statistics', [MAPPEDGENOME, DUPLICATION_RATIO, AVE_READ_SUPPORT, GENES, OPERONS, LARGALIGN, TOTAL_ALIGNED_LEN, NG50, NGx, auNG, NA50, NAx, auNA, NGA50, NGAx, auNGA, LG50, LGx, LA50, LAx, LGA50, LGAx, BUSCO_COMPLETE, BUSCO_PART]), ('Reads mapping', [MAPPED_READS, MAPPED_READS_PCNT, PROPERLY_PAIRED_READS, PROPERLY_PAIRED_READS_PCNT, SINGLETONS, SINGLETONS_PCNT, MISJOINT_READS, MISJOINT_READS_PCNT, DEPTH, COVERAGE__FOR_THRESHOLDS]), ('Misassemblies', [LARGE_MIS_EXTENSIVE, LARGE_MIS_RELOCATION, LARGE_MIS_TRANSLOCATION, LARGE_MIS_INVERTION, LARGE_MIS_ISTRANSLOCATIONS, MIS_ALL_EXTENSIVE, MIS_RELOCATION, MIS_TRANSLOCATION, MIS_INVERTION, MIS_ISTRANSLOCATIONS, MIS_EXTENSIVE_CONTIGS, MIS_EXTENSIVE_BASES, CONTIGS_WITH_ISTRANSLOCATIONS, POSSIBLE_MISASSEMBLIES, MIS_LOCAL, MIS_SCAFFOLDS_GAP, MIS_LOCAL_SCAFFOLDS_GAP, STRUCT_VARIATIONS, POTENTIAL_MGE, UNALIGNED_MISASSEMBLED_CTGS]), ('Unaligned', [UNALIGNED_FULL_CNTGS, UNALIGNED_FULL_LENGTH, UNALIGNED_PART_CNTGS, UNALIGNED_PART_LENGTH, ]), ('Mismatches', [SUBSERROR, MISMATCHES, INDELSERROR, INDELS, MIS_SHORT_INDELS, MIS_LONG_INDELS, INDELSBASES, UNCALLED_PERCENT, UNCALLED, ]), ('Statistics without reference', [CONTIGS, CONTIGS__FOR_THRESHOLDS, LARGCONTIG, TOTALLEN, TOTALLENS__FOR_THRESHOLDS, N50, Nx, auN, L50, Lx, GC,]), ('K-mer-based statistics', [KMER_COMPLETENESS, KMER_CORR_LENGTH, KMER_MIS_LENGTH, KMER_UNDEF_LENGTH, KMER_MISASSEMBLIES, KMER_TRANSLOCATIONS, KMER_RELOCATIONS]), ('Predicted genes', [PREDICTED_GENES_UNIQUE, PREDICTED_GENES, RNA_GENES]), ('Similarity statistics', [SIMILAR_CONTIGS, SIMILAR_MIS_BLOCKS]), ('Reference statistics', [REFLEN, ESTREFLEN, REF_FRAGMENTS, REFGC, REF_GENES, REF_OPERONS, TOTAL_READS, LEFT_READS, RIGHT_READS, REF_MAPPED_READS, REF_MAPPED_READS_PCNT, REF_PROPERLY_PAIRED_READS, REF_PROPERLY_PAIRED_READS_PCNT, REF_SINGLETONS, REF_SINGLETONS_PCNT, REF_MISJOINT_READS, REF_MISJOINT_READS_PCNT, REF_DEPTH, REF_COVERAGE__FOR_THRESHOLDS]) ] # for "short" version of HTML report main_metrics = [CONTIGS, LARGCONTIG, TOTALLEN, LARGALIGN, TOTAL_ALIGNED_LEN, TOTALLENS__FOR_1000_THRESHOLD, TOTALLENS__FOR_10000_THRESHOLD, TOTALLENS__FOR_50000_THRESHOLD, LARGE_MIS_EXTENSIVE, MIS_ALL_EXTENSIVE, MIS_EXTENSIVE_BASES, SUBSERROR, INDELSERROR, UNCALLED_PERCENT, MAPPEDGENOME, DUPLICATION_RATIO, AVE_READ_SUPPORT, MAPPED_READS_PCNT, PROPERLY_PAIRED_READS_PCNT, SINGLETONS_PCNT, MISJOINT_READS_PCNT, GENES, OPERONS, BUSCO_COMPLETE, BUSCO_PART, NGA50, LGA50, PREDICTED_GENES_UNIQUE, PREDICTED_GENES, RNA_GENES, DEPTH, COVERAGE_1X_THRESHOLD, KMER_COMPLETENESS, KMER_MISASSEMBLIES] #################################################################################### ######################## END OF CONFIGURABLE PARAMETERS ########################## #################################################################################### class Quality: MORE_IS_BETTER = 'More is better' LESS_IS_BETTER = 'Less is better' EQUAL = 'Equal' quality_dict = { Quality.MORE_IS_BETTER: [LARGCONTIG, TOTALLEN, TOTALLENS__FOR_THRESHOLDS, TOTALLENS__FOR_1000_THRESHOLD, TOTALLENS__FOR_10000_THRESHOLD, TOTALLENS__FOR_50000_THRESHOLD, LARGALIGN, TOTAL_ALIGNED_LEN, N50, NG50, Nx, NGx, auN, auNG, NA50, NGA50, NAx, NGAx, auNA, auNGA, MAPPEDGENOME, AVE_READ_SUPPORT, GENES, OPERONS, PREDICTED_GENES_UNIQUE, PREDICTED_GENES, RNA_GENES, BUSCO_COMPLETE, MAPPED_READS, MAPPED_READS_PCNT, PROPERLY_PAIRED_READS, PROPERLY_PAIRED_READS_PCNT, KMER_COMPLETENESS, KMER_CORR_LENGTH, DEPTH, COVERAGE__FOR_THRESHOLDS], Quality.LESS_IS_BETTER: [L50, LG50, Lx, LGx, MISLOCAL, MISASSEMBL, MISCONTIGS, MISCONTIGSBASES, MISINTERNALOVERLAP, LARGE_MIS_EXTENSIVE, MIS_ALL_EXTENSIVE, CONTIGS_WITH_ISTRANSLOCATIONS, POSSIBLE_MISASSEMBLIES, UNALIGNED, UNALIGNEDBASES, AMBIGUOUS, AMBIGUOUSEXTRABASES, UNCALLED, UNCALLED_PERCENT, BUSCO_PART, SINGLETONS, SINGLETONS_PCNT, MISJOINT_READS, MISJOINT_READS_PCNT, KMER_MIS_LENGTH, KMER_UNDEF_LENGTH, KMER_MISASSEMBLIES, LA50, LGA50, LAx, LGAx, DUPLICATION_RATIO, INDELS, INDELSERROR, MISMATCHES, SUBSERROR, MIS_SHORT_INDELS, MIS_LONG_INDELS, INDELSBASES], Quality.EQUAL: [REFLEN, ESTREFLEN, GC, CONTIGS, CONTIGS__FOR_THRESHOLDS, REFGC, STRUCT_VARIATIONS, POTENTIAL_MGE, SIMILAR_CONTIGS, SIMILAR_MIS_BLOCKS], } # Old Python2 only version #for name, metrics in filter(lambda (name, metrics): name in ['Misassemblies', 'Unaligned'], grouped_order): # quality_dict['Less is better'].extend(metrics) # Python3 version for metrics in [v for name,v in grouped_order if name in ["Misassemblies", "Unaligned"]]: quality_dict['Less is better'].extend(metrics) ################################################# from quast_libs.log import get_logger logger = get_logger(qconfig.LOGGER_DEFAULT_NAME) #################################################################################### # Reporting module (singleton) for QUAST # # See class Fields to available fields for report. # Usage from QUAST modules: # from libs import reporting # report = reporting.get(fasta_filename) # report.add_field(reporting.Field.N50, n50) # # Import this module only after final changes in qconfig! # #################################################################################### reports = {} # basefilename -> Report assembly_fpaths = [] # for printing in appropriate order ################################################# def _mapme(func, data): return [func(this) for this in data] def get_main_metrics(): lists = _mapme(take_tuple_metric_apart, Fields.main_metrics) m_metrics = [] for l in lists: for m in l: m_metrics.append(m) return m_metrics def take_tuple_metric_apart(field): metrics = [] if isinstance(field, tuple): # TODO: rewrite it nicer thresholds = _mapme(int, ''.join(field[1]).split(',')) for i, feature in enumerate(thresholds): metrics.append(field[0] % feature) else: metrics = [field] return metrics def get_quality(metric): for quality, metrics in Fields.quality_dict.items(): if metric in Fields.quality_dict[quality]: return quality return Fields.Quality.EQUAL # Report for one filename, dict: field -> value class Report(object): def __init__(self, name): self.d = {} self.add_field(Fields.NAME, name) # TODO: associate floating fields with the default number of decimal points and format them automatically here def add_field(self, field, value): try: assert field in Fields.__dict__.itervalues(), 'Unknown field: %s' % field except: assert field in Fields.__dict__.values(), 'Unknown field: %s' % field self.d[field] = value def append_field(self, field, value): try: assert field in Fields.__dict__.itervalues(), 'Unknown field: %s' % field except: assert field in Fields.__dict__.values(), 'Unknown field: %s' % field self.d.setdefault(field, []).append(value) def get_field(self, field): try: assert field in Fields.__dict__.itervalues(), 'Unknown field: %s' % field except: assert field in Fields.__dict__.values(), 'Unknown field: %s' % field return self.d.get(field, None) def get(assembly_fpath, ref_name=None): if not ref_name and qconfig.reference: ref_name = qutils.name_from_fpath(qconfig.reference) if assembly_fpath not in assembly_fpaths: assembly_fpaths.append(assembly_fpath) return reports.setdefault((os.path.abspath(assembly_fpath), ref_name), Report(qutils.label_from_fpath(assembly_fpath))) def delete(assembly_fpath): if assembly_fpath in assembly_fpaths: assembly_fpaths.remove(assembly_fpath) if assembly_fpath in reports.keys(): reports.pop(assembly_fpath) # ATTENTION! Contents numeric values, needed to be converted into strings def table(order=Fields.order, ref_name=None): if not isinstance(order[0], tuple): # is not a groupped metrics order order = [('', order)] table = [] required_fields = [] def define_required_fields(): if qconfig.report_all_metrics: required_fields.extend(Fields.order) return # if a reference is specified, keep the same number of Nx/Lx-like genome-based metrics in different reports # (no matter what percent of the genome was assembled) report = get(assembly_fpaths[0], ref_name=ref_name) if report.get_field(Fields.REFLEN): anyone_aligned = False for assembly_fpath in assembly_fpaths: report = get(assembly_fpath, ref_name=ref_name) if report.get_field(Fields.MAPPEDGENOME): anyone_aligned = True break if anyone_aligned: required_fields.extend([Fields.NA50, Fields.LA50, Fields.NAx, Fields.LAx]) if not qconfig.is_combined_ref: required_fields.extend([Fields.NG50, Fields.LG50, Fields.NGx, Fields.LGx]) if anyone_aligned: required_fields.extend([Fields.NGA50, Fields.LGA50, Fields.NGAx, Fields.LGAx]) def append_line(rows, field, are_multiple_thresholds=False, pattern=None, feature=None, i=None, ref_name=None): quality = get_quality(field) values = [] for assembly_fpath in assembly_fpaths: report = get(assembly_fpath, ref_name=ref_name) value = report.get_field(field) if are_multiple_thresholds: values.append(value[i] if (value and i < len(value)) else None) else: values.append(value) if list(filter(lambda v: v is not None, values)) or field in required_fields: metric_name = field if (feature is None) else pattern % int(feature) # ATTENTION! Contents numeric values, needed to be converted to strings. rows.append({ 'metricName': metric_name, 'quality': quality, 'values': values, 'isMain': metric_name in Fields.main_metrics, }) define_required_fields() for group_name, metrics in order: rows = [] table.append((group_name, rows)) for field in metrics: if isinstance(field, tuple): # TODO: rewrite it nicer for i, feature in enumerate(field[1]): append_line(rows, field, are_multiple_thresholds=True, pattern=field[0], feature=feature, i=i, ref_name=ref_name) else: append_line(rows, field, ref_name=ref_name) if not isinstance(order[0], tuple): # is not a groupped metrics order group_name, rows = table[0] return rows else: return table def is_groupped_table(table): return isinstance(table[0], tuple) def get_all_rows_out_of_table(table): all_rows = [] if is_groupped_table(table): for group_name, rows in table: all_rows += rows else: all_rows = table return all_rows def save_txt(fpath, all_rows): # determine width of columns for nice spaces colwidths = [0] * (len(all_rows[0]['values']) + 1) for row in all_rows: for i, cell in enumerate([row['metricName']] + [val_to_str(this) for this in row['values']]): colwidths[i] = max(colwidths[i], len(cell)) # output it txt_file = open(fpath, 'w') if qconfig.min_contig: txt_file.write('All statistics are based on contigs of size >= %d bp, unless otherwise noted ' % qconfig.min_contig + \ '(e.g., "# contigs (>= 0 bp)" and "Total length (>= 0 bp)" include all contigs).\n') txt_file.write('\n') for row in all_rows: txt_file.write(' '.join('%-*s' % (colwidth, cell) for colwidth, cell in zip(colwidths, [row['metricName']] + [val_to_str(this) for this in row['values']])) + "\n") txt_file.close() def save_tsv(fpath, all_rows): tsv_file = open(fpath, 'w') for row in all_rows: tsv_file.write('\t'.join([row['metricName']] + [val_to_str(this) for this in row['values']]) + "\n") tsv_file.close() def parse_number(val): # Float? try: num = int(val) except ValueError: # Int? try: num = float(val) except ValueError: num = None return num def get_num_from_table_value(val): if isinstance(val, int) or isinstance(val, float): num = val elif isinstance(val, basestring) and len(val.split()) > 0: # 'x + y part' format? tokens = val.split() # tokens = [x, +, y, part] if len(tokens) >= 3: # Yes, 'y + x part' format x, y = parse_number(tokens[0]), parse_number(tokens[2]) if x is None or y is None: num = None else: num = (x, y) # Tuple value. Can be compared lexicographically. else: num = parse_number(tokens[0]) else: num = val return num def save_tex(fpath, all_rows, is_transposed=False): tex_file = open(fpath, 'w') # Header tex_file.write('\\documentclass[12pt,a4paper]{article}\n') tex_file.write('\\begin{document}\n') tex_file.write('\\begin{table}[ht]\n') tex_file.write('\\begin{center}\n') tex_file.write('\\caption{All statistics are based on contigs of size $\geq$ %d bp, unless otherwise noted ' % qconfig.min_contig + \ '(e.g., "\# contigs ($\geq$ 0 bp)" and "Total length ($\geq$ 0 bp)" include all contigs).}\n') rows_n = len(all_rows[0]['values']) tex_file.write('\\begin{tabular}{|l*{' + val_to_str(rows_n) + '}{|r}|}\n') tex_file.write('\\hline\n') # Body for row in all_rows: values = row['values'] quality = row['quality'] if ('quality' in row) else Fields.Quality.EQUAL if is_transposed or quality not in [Fields.Quality.MORE_IS_BETTER, Fields.Quality.LESS_IS_BETTER]: cells = _mapme(val_to_str, values) else: # Checking the first value, assuming the others are the same type and format num = get_num_from_table_value(values[0]) if num is None: # Not a number cells = _mapme(val_to_str, values) else: nums = _mapme(get_num_from_table_value, values) best = None if quality == Fields.Quality.MORE_IS_BETTER: best = max(n for n in nums if n is not None) if quality == Fields.Quality.LESS_IS_BETTER: best = min(n for n in nums if n is not None) if len([num for num in nums if num != best]) == 0: cells = _mapme(val_to_str, values) else: cells = ['HIGHLIGHTEDSTART' + val_to_str(v) + 'HIGHLIGHTEDEND' if get_num_from_table_value(v) == best else val_to_str(v) for v in values] row = ' & '.join([row['metricName']] + cells) # escape characters for esc_char in "\\ % $ # _ { } ~ ^".split(): row = row.replace(esc_char, '\\' + esc_char) # more pretty '>=' and '<=', '>' row = row.replace('>=', '$\\geq$') row = row.replace('<=', '$\\leq$') row = row.replace('>', '$>$') # pretty indent if row.startswith(Fields.TAB): row = "\hspace{5mm}" + row.lstrip() if row.startswith(Fields.HALF_TAB): row = "\hspace{2mm}" + row.lstrip() # pretty highlight row = row.replace('HIGHLIGHTEDSTART', '{\\bf ') row = row.replace('HIGHLIGHTEDEND', '}') row += ' \\\\ \\hline' tex_file.write(row +"\n") # Footer tex_file.write('\\end{tabular}\n') tex_file.write('\\end{center}\n') tex_file.write('\\end{table}\n') tex_file.write('\\end{document}\n') tex_file.close() if os.path.basename(fpath) == 'report.tex': pass def save_pdf(report_name, table): if not qconfig.draw_plots: return all_rows = get_all_rows_out_of_table(table) column_widths = [0] * (len(all_rows[0]['values']) + 1) for row in all_rows: for i, cell in enumerate([row['metricName']] + _mapme(val_to_str, row['values'])): column_widths[i] = max(column_widths[i], len(cell)) if qconfig.min_contig: extra_info = 'All statistics are based on contigs of size >= %d bp, unless otherwise noted ' % qconfig.min_contig +\ '\n(e.g., "# contigs (>= 0 bp)" and "Total length (>= 0 bp)" include all contigs).' else: extra_info = '' table_to_draw = [] for row in all_rows: table_to_draw.append(['%s' % cell for cell in [row['metricName']] + _mapme(val_to_str, row['values'])]) from quast_libs import plotter plotter.draw_report_table(report_name, extra_info, table_to_draw, column_widths) def save(output_dirpath, report_name, transposed_report_name, order, silent=False): # Where total report will be saved tab = table(order) if not silent: logger.info(' Creating total report...') report_txt_fpath = os.path.join(output_dirpath, report_name) + '.txt' report_tsv_fpath = os.path.join(output_dirpath, report_name) + '.tsv' report_tex_fpath = os.path.join(output_dirpath, report_name) + '.tex' all_rows = get_all_rows_out_of_table(tab) save_txt(report_txt_fpath, all_rows) save_tsv(report_tsv_fpath, all_rows) save_tex(report_tex_fpath, all_rows) save_pdf(report_name, tab) reports_fpaths = report_txt_fpath + ', ' + os.path.basename(report_tsv_fpath) + ', and ' + \ os.path.basename(report_tex_fpath) transposed_reports_fpaths = None if not silent: logger.info(' saved to ' + reports_fpaths) if transposed_report_name: if not silent: logger.info(' Transposed version of total report...') all_rows = get_all_rows_out_of_table(tab) if all_rows[0]['metricName'] != Fields.NAME: logger.warning('transposed version can\'t be created! First column have to be assemblies names') else: # Transposing table transposed_table = [{'metricName': all_rows[0]['metricName'], 'values': [all_rows[i]['metricName'] for i in range(1, len(all_rows))],}] for i in range(len(all_rows[0]['values'])): values = [] for j in range(1, len(all_rows)): values.append(all_rows[j]['values'][i]) transposed_table.append({'metricName': all_rows[0]['values'][i], # name of assembly, assuming the first line is assemblies names 'values': values,}) report_txt_fpath = os.path.join(output_dirpath, transposed_report_name) + '.txt' report_tsv_fpath = os.path.join(output_dirpath, transposed_report_name) + '.tsv' report_tex_fpath = os.path.join(output_dirpath, transposed_report_name) + '.tex' all_rows = get_all_rows_out_of_table(transposed_table) save_txt(report_txt_fpath, all_rows) save_tsv(report_tsv_fpath, all_rows) save_tex(report_tex_fpath, all_rows, is_transposed=True) transposed_reports_fpaths = report_txt_fpath + ', ' + os.path.basename(report_tsv_fpath) + \ ', and ' + os.path.basename(report_tex_fpath) if not silent: logger.info(' saved to ' + transposed_reports_fpaths) return reports_fpaths, transposed_reports_fpaths def save_total(output_dirpath, silent=True): if not silent: logger.print_timestamp() logger.info('Summarizing...') return save(output_dirpath, qconfig.report_prefix, qconfig.transposed_report_prefix, Fields.order, silent=silent) def save_misassemblies(output_dirpath): save(output_dirpath, "misassemblies_report", qconfig.transposed_report_prefix + "_misassemblies", Fields.misassemblies_order_advanced) def save_unaligned(output_dirpath): save(output_dirpath, "unaligned_report", "", Fields.unaligned_order) def save_reads(output_dirpath): save(output_dirpath, "reads_report", "", Fields.reads_order) def save_kmers(output_dirpath): save(output_dirpath, "kmers_report", "", Fields.kmers_order)