Mercurial > repos > greg > draw_amr_matrix
changeset 17:eb86b4bf140e draft default tip
Uploaded
author | greg |
---|---|
date | Wed, 03 May 2023 15:13:12 +0000 (20 months ago) |
parents | 7bd48449ee79 |
children | |
files | draw_amr_matrix.py |
diffstat | 1 files changed, 141 insertions(+), 146 deletions(-) [+] |
line wrap: on
line diff
--- a/draw_amr_matrix.py Mon May 01 18:52:58 2023 +0000 +++ b/draw_amr_matrix.py Wed May 03 15:13:12 2023 +0000 @@ -13,13 +13,6 @@ import matplotlib.pyplot as pyplot -def get_amr_in_feature_hits(amr_feature_hits): - for k in amr_feature_hits.keys(): - if k.lower().find('amr') >= 0: - return amr_feature_hits[k] - return None - - def load_fasta(fasta_file): sequence = pandas.Series(dtype=object) for contig in Bio.SeqIO.parse(fasta_file, 'fasta'): @@ -77,148 +70,150 @@ best_hits = None amr_feature_hits[feature_name] = best_hits - amr_hits = get_amr_in_feature_hits(amr_feature_hits) - ofh.write("\namr_hits:\n%s\n" % str(amr_hits)) - if amr_hits is not None: - amr_to_draw = pandas.DataFrame(columns=['gene', 'drug']) - ofh.write("\namr_to_draw:\n%s\n" % str(amr_to_draw)) - # Read amr_drug_gene_file. - amr_gene_drug = pandas.read_csv(amr_gene_drug_file, index_col=None, sep='\t', quoting=csv.QUOTE_NONE, header=None) - ofh.write("\namr_gene_drug:\n%s\n" % str(amr_gene_drug)) + # Process populated feature hits. + for k in amr_feature_hits.keys(): + if amr_feature_hits[k] is not None: + amr_hits = amr_feature_hits[k] + ofh.write("\namr_hits:\n%s\n" % str(amr_hits)) + amr_to_draw = pandas.DataFrame(columns=['gene', 'drug']) + ofh.write("\namr_to_draw:\n%s\n" % str(amr_to_draw)) + # Read amr_drug_gene_file. + amr_gene_drug = pandas.read_csv(amr_gene_drug_file, index_col=None, sep='\t', quoting=csv.QUOTE_NONE, header=None) + ofh.write("\namr_gene_drug:\n%s\n" % str(amr_gene_drug)) + + # Roll up AMR gene hits. + ofh.write("\namr_hits.shape[0]: %s\n" % str(amr_hits.shape[0])) + if amr_hits.shape[0] > 0: + for gene_idx, gene in amr_hits.iterrows(): + ofh.write("gene_idx: %s\n" % str(gene_idx)) + ofh.write("gene: %s\n" % str(gene)) + gene_name = gene[3] + ofh.write("gene_name: %s\n" % str(gene_name)) + ofh.write("amr_gene_drug[0]: %s\n" % str(amr_gene_drug[0])) + drugs = amr_gene_drug.loc[amr_gene_drug[0] == gene_name, :][1] + ofh.write("drugs: %s\n" % str(drugs)) + for drug in drugs: + amr_to_draw = amr_to_draw.append(pandas.Series([gene_name, drug], name=amr_to_draw.shape[0], index=amr_to_draw.columns)) + ofh.write("\amr_to_draw: %s\n" % str(amr_to_draw)) - # Roll up AMR gene hits. - ofh.write("\namr_hits.shape[0]: %s\n" % str(amr_hits.shape[0])) - if amr_hits.shape[0] > 0: - for gene_idx, gene in amr_hits.iterrows(): - ofh.write("gene_idx: %s\n" % str(gene_idx)) - ofh.write("gene: %s\n" % str(gene)) - gene_name = gene[3] - ofh.write("gene_name: %s\n" % str(gene_name)) - ofh.write("amr_gene_drug[0]: %s\n" % str(amr_gene_drug[0])) - drugs = amr_gene_drug.loc[amr_gene_drug[0] == gene_name, :][1] - ofh.write("drugs: %s\n" % str(drugs)) - for drug in drugs: - amr_to_draw = amr_to_draw.append(pandas.Series([gene_name, drug], name=amr_to_draw.shape[0], index=amr_to_draw.columns)) - ofh.write("\amr_to_draw: %s\n" % str(amr_to_draw)) - - ofh.write("\nvarscan_vcf_file is None: %s\n" % str(varscan_vcf_file == 'None')) - if varscan_vcf_file not in [None, 'None'] and os.path.getsize(varscan_vcf_file) > 0: - amr_mutations = pandas.Series(dtype=object) - if amr_mutation_regions_bed_file is not None: - mutation_regions = pandas.read_csv(amr_mutation_regions_bed_file, header=0, sep='\t', index_col=False) - # Validate mutation regions. - if mutation_regions.shape[1] != 7: - efh.write("The selected mutations regions BED file is invalid, it should be a six column file.\n") - elif mutation_regions.shape[0] == 0: - efh.write("There are no rows in the selected mutation regions file.\n") + ofh.write("\nvarscan_vcf_file is None: %s\n" % str(varscan_vcf_file == 'None')) + if varscan_vcf_file not in [None, 'None'] and os.path.getsize(varscan_vcf_file) > 0: + amr_mutations = pandas.Series(dtype=object) + if amr_mutation_regions_bed_file is not None: + mutation_regions = pandas.read_csv(amr_mutation_regions_bed_file, header=0, sep='\t', index_col=False) + # Validate mutation regions. + if mutation_regions.shape[1] != 7: + efh.write("The selected mutations regions BED file is invalid, it should be a six column file.\n") + elif mutation_regions.shape[0] == 0: + efh.write("There are no rows in the selected mutation regions file.\n") + else: + for region_i in range(mutation_regions.shape[0]): + region = mutation_regions.iloc[region_i, :] + if region[0] not in reference: + efh.write("Mutation region '%s' not found in reference genome.\n" % str(region)) + break + if not isinstance(region[1], numpy.int64): + efh.write("Non-integer found in mutation region start (column 2): %s.\n" % str(region[1])) + break + if not isinstance(region[2], numpy.int64): + efh.write("Non-integer found in mutation region start (column 3): %s.\n" % str(region[2])) + break + if region[1] <= 0 or region[2] <= 0: + efh.write("Mutation region '%s' starts before the reference sequence.\n" % str(region)) + if region[1] > len(reference[region[0]].seq) or region[2] > len(reference[region[0]].seq): + efh.write("Mutation region '%s' ends after the reference sequence.\n" % str(region)) + if not region.get('type', default='No Type') in ['snp', 'small-indel', 'any']: + ofh.write("\n\nSkipping mutation region '%s' with invalid type '%s', valid types are 'snp', 'small-indel', 'any'.\n\n" % (str(region), str(region.get('type', default='No Type')))) + continue + ofh.write("\nFinding AMR mutations for %s.\n" % str(region['name'])) + region_bed = 'region_%s.bed' % region_i + ofh.write("region_bed: %s\n" % str(region_bed)) + mutation_regions.loc[[region_i], ].to_csv(path_or_buf=region_bed, sep='\t', header=False, index=False) + ofh.write("mutation_regions.loc[[region_i], ]:\n%s\n" % str(mutation_regions.loc[[region_i], ])) + region_mutations_tsv = os.path.join(mutation_regions_dir, 'region_%s_mutations.tsv' % region_i) + ofh.write("region_mutations_tsv: %s\n" % str(region_mutations_tsv)) + cmd = ' '.join(['bedtools intersect', + '-nonamecheck', + '-wb', + '-a', region_bed, + '-b', varscan_vcf_file, + ' | awk \'BEGIN{getline < "' + amr_mutation_regions_bed_file + '";printf $0"\\t";', + 'getline < "' + varscan_vcf_file + '"; getline < "' + varscan_vcf_file + '";print $0}{print}\'', + '1>' + region_mutations_tsv]) + ofh.write("\ncmd:\n%s\n" % cmd) + run_command(cmd) + try: + ofh.write("After running command, os.path.getsize((region_mutations_tsv): %s\n" % str(os.path.getsize(region_mutations_tsv))) + region_mutations = pandas.read_csv(region_mutations_tsv, sep='\t', header=0, index_col=False) + ofh.write("\nregion_mutations: %s\n" % region_mutations) + except Exception: + continue + # Figure out what kind of mutations are in this region. + region_mutation_types = pandas.Series(['snp'] * region_mutations.shape[0], name='TYPE', index=region_mutations.index) + region_mutation_types[region_mutations['REF'].str.len() != region_mutations['ALT'].str.len()] = 'small-indel' + region_mutation_drugs = pandas.Series(region['drug'] * region_mutations.shape[0], name='DRUG', index=region_mutations.index) + region_notes = pandas.Series(region['note'] * region_mutations.shape[0], name='NOTE', index=region_mutations.index) + region_mutations = pandas.concat([region_mutations, region_mutation_types, region_mutation_drugs, region_notes], axis=1) + region_mutations = region_mutations[['#CHROM', 'POS', 'TYPE', 'REF', 'ALT', 'DRUG', 'NOTE']] + amr_mutations[region['name']] = region_mutations else: - for region_i in range(mutation_regions.shape[0]): - region = mutation_regions.iloc[region_i, :] - if region[0] not in reference: - efh.write("Mutation region '%s' not found in reference genome.\n" % str(region)) - break - if not isinstance(region[1], numpy.int64): - efh.write("Non-integer found in mutation region start (column 2): %s.\n" % str(region[1])) - break - if not isinstance(region[2], numpy.int64): - efh.write("Non-integer found in mutation region start (column 3): %s.\n" % str(region[2])) - break - if region[1] <= 0 or region[2] <= 0: - efh.write("Mutation region '%s' starts before the reference sequence.\n" % str(region)) - if region[1] > len(reference[region[0]].seq) or region[2] > len(reference[region[0]].seq): - efh.write("Mutation region '%s' ends after the reference sequence.\n" % str(region)) - if not region.get('type', default='No Type') in ['snp', 'small-indel', 'any']: - ofh.write("\n\nSkipping mutation region '%s' with invalid type '%s', valid types are 'snp', 'small-indel', 'any'.\n\n" % (str(region), str(region.get('type', default='No Type')))) - continue - ofh.write("\nFinding AMR mutations for %s.\n" % str(region['name'])) - region_bed = 'region_%s.bed' % region_i - ofh.write("region_bed: %s\n" % str(region_bed)) - mutation_regions.loc[[region_i], ].to_csv(path_or_buf=region_bed, sep='\t', header=False, index=False) - ofh.write("mutation_regions.loc[[region_i], ]:\n%s\n" % str(mutation_regions.loc[[region_i], ])) - region_mutations_tsv = os.path.join(mutation_regions_dir, 'region_%s_mutations.tsv' % region_i) - ofh.write("region_mutations_tsv: %s\n" % str(region_mutations_tsv)) - cmd = ' '.join(['bedtools intersect', - '-nonamecheck', - '-wb', - '-a', region_bed, - '-b', varscan_vcf_file, - ' | awk \'BEGIN{getline < "' + amr_mutation_regions_bed_file + '";printf $0"\\t";', - 'getline < "' + varscan_vcf_file + '"; getline < "' + varscan_vcf_file + '";print $0}{print}\'', - '1>' + region_mutations_tsv]) - ofh.write("\ncmd:\n%s\n" % cmd) - run_command(cmd) - try: - ofh.write("After running command, os.path.getsize((region_mutations_tsv): %s\n" % str(os.path.getsize(region_mutations_tsv))) - region_mutations = pandas.read_csv(region_mutations_tsv, sep='\t', header=0, index_col=False) - ofh.write("\nregion_mutations: %s\n" % region_mutations) - except Exception: - continue - # Figure out what kind of mutations are in this region. - region_mutation_types = pandas.Series(['snp'] * region_mutations.shape[0], name='TYPE', index=region_mutations.index) - region_mutation_types[region_mutations['REF'].str.len() != region_mutations['ALT'].str.len()] = 'small-indel' - region_mutation_drugs = pandas.Series(region['drug'] * region_mutations.shape[0], name='DRUG', index=region_mutations.index) - region_notes = pandas.Series(region['note'] * region_mutations.shape[0], name='NOTE', index=region_mutations.index) - region_mutations = pandas.concat([region_mutations, region_mutation_types, region_mutation_drugs, region_notes], axis=1) - region_mutations = region_mutations[['#CHROM', 'POS', 'TYPE', 'REF', 'ALT', 'DRUG', 'NOTE']] - amr_mutations[region['name']] = region_mutations + ofh.write("\nMutation region BED file not received.\n") + ofh.write("\nAfter processing mutations, amr_mutations: %s\n" % str(amr_mutations)) + # Roll up potentially resistance conferring mutations. + ofh.write("\n##### Rolling up potentially resistance conferring mutations..\n") + for mutation_region, mutation_hits in amr_mutations.iteritems(): + ofh.write("mutation_region: %s\n" % str(mutation_region)) + ofh.write("mutation_hits: %s\n" % str(mutation_hits)) + for mutation_idx, mutation_hit in mutation_hits.iterrows(): + ofh.write("mutation_idx: %s\n" % str(mutation_idx)) + ofh.write("mutation_hit: %s\n" % str(mutation_hit)) + mutation_name = mutation_region + ' ' + mutation_hit['REF'] + '->' + mutation_hit['ALT'] + ofh.write("mutation_name: %s\n" % str(mutation_name)) + amr_to_draw = amr_to_draw.append(pandas.Series([mutation_name, mutation_hit['DRUG']], name=amr_to_draw.shape[0], index=amr_to_draw.columns)) + ofh.write("\nAfter processing mutations, amr_to_draw: %s\n" % str(amr_to_draw)) + ofh.write("\nAfter processing mutations, amr_to_draw.shape[0]: %s\n" % str(amr_to_draw.shape[0])) + + if amr_deletions_file not in [None, 'None'] and os.path.getsize(amr_deletions_file) > 0: + # Roll up deletions that might confer resistance. + try: + amr_deletions = pandas.read_csv(filepath_or_buffer=amr_deletions_file, sep='\t', header=None) + except Exception: + amr_deletions = pandas.DataFrame() + if amr_deletions.shape[0] > 0: + amr_deletions.columns = ['contig', 'start', 'stop', 'name', 'type', 'drug', 'note'] + amr_deletions = amr_deletions.loc[amr_deletions['type'].isin(['large-deletion', 'any']), :] + for deletion_idx, deleted_gene in amr_deletions.iterrows(): + amr_to_draw = amr_to_draw.append(pandas.Series(['\u0394' + deleted_gene[3], deleted_gene[5]], name=amr_to_draw.shape[0], index=amr_to_draw.columns)) + ofh.write("\nAfter processing deletions, amr_to_draw: %s\n" % str(amr_to_draw)) + + ofh.write("\namr_to_draw.shape[0]: %s\n" % str(amr_to_draw.shape[0])) + # I have no idea why, but when running functional tests with planemo + # the value of amr_to_draw.shape[0] is 1 even though the tests use the + # exact inputs when running outside of planeo that result in the value + # being 2. So we cannot test with planemo unless we incorporate a hack + # like a hidden in_test_mode parameter. + if amr_to_draw.shape[0] > 1: + ofh.write("\nDrawing AMR matrix...\n") + present_genes = amr_to_draw['gene'].unique() + present_drugs = amr_to_draw['drug'].unique() + amr_matrix = pandas.DataFrame(0, index=present_genes, columns=present_drugs) + for hit_idx, hit in amr_to_draw.iterrows(): + amr_matrix.loc[hit[0], hit[1]] = 1 + amr_matrix_png = os.path.join(amr_matrix_png_dir, 'amr_matrix.png') + int_matrix = amr_matrix[amr_matrix.columns].astype(int) + figure, axis = pyplot.subplots() + heatmap = axis.pcolor(int_matrix, cmap=pyplot.cm.Blues, linewidth=0) + axis.invert_yaxis() + axis.set_yticks(numpy.arange(0.5, len(amr_matrix.index)), minor=False) + axis.set_yticklabels(int_matrix.index.values) + axis.set_xticks(numpy.arange(0.5, len(amr_matrix.columns)), minor=False) + axis.set_xticklabels(amr_matrix.columns.values, rotation=90) + axis.xaxis.tick_top() + axis.xaxis.set_label_position('top') + pyplot.tight_layout() + pyplot.savefig(amr_matrix_png, dpi=300) else: - ofh.write("\nMutation region BED file not received.\n") - ofh.write("\nAfter processing mutations, amr_mutations: %s\n" % str(amr_mutations)) - # Roll up potentially resistance conferring mutations. - ofh.write("\n##### Rolling up potentially resistance conferring mutations..\n") - for mutation_region, mutation_hits in amr_mutations.iteritems(): - ofh.write("mutation_region: %s\n" % str(mutation_region)) - ofh.write("mutation_hits: %s\n" % str(mutation_hits)) - for mutation_idx, mutation_hit in mutation_hits.iterrows(): - ofh.write("mutation_idx: %s\n" % str(mutation_idx)) - ofh.write("mutation_hit: %s\n" % str(mutation_hit)) - mutation_name = mutation_region + ' ' + mutation_hit['REF'] + '->' + mutation_hit['ALT'] - ofh.write("mutation_name: %s\n" % str(mutation_name)) - amr_to_draw = amr_to_draw.append(pandas.Series([mutation_name, mutation_hit['DRUG']], name=amr_to_draw.shape[0], index=amr_to_draw.columns)) - ofh.write("\nAfter processing mutations, amr_to_draw: %s\n" % str(amr_to_draw)) - ofh.write("\nAfter processing mutations, amr_to_draw.shape[0]: %s\n" % str(amr_to_draw.shape[0])) - - if amr_deletions_file not in [None, 'None'] and os.path.getsize(amr_deletions_file) > 0: - # Roll up deletions that might confer resistance. - try: - amr_deletions = pandas.read_csv(filepath_or_buffer=amr_deletions_file, sep='\t', header=None) - except Exception: - amr_deletions = pandas.DataFrame() - if amr_deletions.shape[0] > 0: - amr_deletions.columns = ['contig', 'start', 'stop', 'name', 'type', 'drug', 'note'] - amr_deletions = amr_deletions.loc[amr_deletions['type'].isin(['large-deletion', 'any']), :] - for deletion_idx, deleted_gene in amr_deletions.iterrows(): - amr_to_draw = amr_to_draw.append(pandas.Series(['\u0394' + deleted_gene[3], deleted_gene[5]], name=amr_to_draw.shape[0], index=amr_to_draw.columns)) - ofh.write("\nAfter processing deletions, amr_to_draw: %s\n" % str(amr_to_draw)) - - ofh.write("\namr_to_draw.shape[0]: %s\n" % str(amr_to_draw.shape[0])) - # I have no idea why, but when running functional tests with planemo - # the value of amr_to_draw.shape[0] is 1 even though the tests use the - # exact inputs when running outside of planeo that result in the value - # being 2. So we cannot test with planemo unless we incorporate a hack - # like a hidden in_test_mode parameter. - if amr_to_draw.shape[0] > 1: - ofh.write("\nDrawing AMR matrix...\n") - present_genes = amr_to_draw['gene'].unique() - present_drugs = amr_to_draw['drug'].unique() - amr_matrix = pandas.DataFrame(0, index=present_genes, columns=present_drugs) - for hit_idx, hit in amr_to_draw.iterrows(): - amr_matrix.loc[hit[0], hit[1]] = 1 - amr_matrix_png = os.path.join(amr_matrix_png_dir, 'amr_matrix.png') - int_matrix = amr_matrix[amr_matrix.columns].astype(int) - figure, axis = pyplot.subplots() - heatmap = axis.pcolor(int_matrix, cmap=pyplot.cm.Blues, linewidth=0) - axis.invert_yaxis() - axis.set_yticks(numpy.arange(0.5, len(amr_matrix.index)), minor=False) - axis.set_yticklabels(int_matrix.index.values) - axis.set_xticks(numpy.arange(0.5, len(amr_matrix.columns)), minor=False) - axis.set_xticklabels(amr_matrix.columns.values, rotation=90) - axis.xaxis.tick_top() - axis.xaxis.set_label_position('top') - pyplot.tight_layout() - pyplot.savefig(amr_matrix_png, dpi=300) - else: - ofh.write("\nEmpty AMR matrix, nothing to draw...\n") + ofh.write("\nEmpty AMR matrix, nothing to draw...\n") efh.close() ofh.close()