Mercurial > repos > greg > draw_amr_matrix
diff draw_amr_matrix.py @ 0:6044ca44e9f6 draft
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author | greg |
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date | Tue, 07 Feb 2023 22:13:57 +0000 |
parents | |
children | 5c923c77cf5f |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/draw_amr_matrix.py Tue Feb 07 22:13:57 2023 +0000 @@ -0,0 +1,117 @@ +#!/usr/bin/env python + +import argparse +import csv +import os + +import numpy +import pandas +import matplotlib.pyplot as pyplot + + +def get_amr_in_feature_hits(feature_hits): + for k in feature_hits.keys(): + if k.lower().find('amr') >= 0: + return feature_hits[k] + return None + + +def draw_amr_matrix(feature_hits_files, amr_gene_drug_file, output_dir): + ofh = open('process_log', 'w') + + # Read feature_hits_files. + feature_hits = pandas.Series(dtype=object) + for feature_hits_file in feature_hits_files: + feature_name = os.path.basename(feature_hits_file) + # Make sure the file is not empty. + if os.path.isfile(feature_hits_file) and os.path.getsize(feature_hits_file) > 0: + best_hits = pandas.read_csv(filepath_or_buffer=feature_hits_file, sep='\t', header=None) + ofh.write("\nFeature file %s will be processed\n" % os.path.basename(feature_hits_file)) + else: + ofh.write("\nEmpty feature file %s will NOT be processed\n" % os.path.basename(feature_hits_file)) + best_hits = None + feature_hits[feature_name] = best_hits + + amr_hits = get_amr_in_feature_hits(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)) + + # 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)) + + amr_mutations = pandas.Series(dtype=object) + if amr_mutations.shape[0] > 0: + # Roll up potentially resistance conferring mutations. + # TODO: may need to populate this if we need to use call_amr_mutations. + for mutation_region, mutation_hits in amr_mutations.iteritems(): + for mutation_idx, mutation_hit in mutation_hits.iterrows(): + mutation_name = mutation_region + ' ' + mutation_hit['REF'] + '->' + mutation_hit['ALT'] + 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)) + + amr_deletions = pandas.DataFrame() + if amr_deletions.shape[0] > 0: + # Roll up deletions that might confer resistance. + # TODO: may need to populate this if we need to use call_insertions. + 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)) + + 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(output_dir, 'amr_matrix.png') + int_matrix = amr_matrix[amr_matrix.columns].astype(int) + figure, axis = pyplot.subplots() + 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.close() + + +if __name__ == '__main__': + parser = argparse.ArgumentParser() + + parser.add_argument('--amr_gene_drug_file', action='store', dest='amr_gene_drug_file', help='AMR_gene_drugs tsv file') + parser.add_argument('--feature_hits_dir', action='store', dest='feature_hits_dir', help='Directory of tabular files containing feature hits') + parser.add_argument('--output_dir', action='store', dest='output_dir', help='Output directory') + + args = parser.parse_args() + + # Get thge collection of feature hits files. The collection + # will be sorted alphabetically and will contain 2 files + # named something like AMR_CDS_311_2022_12_20.fasta and + # Incompatibility_Groups_2023_01_01.fasta. + feature_hits_files = [] + for file_name in sorted(os.listdir(args.feature_hits_dir)): + file_path = os.path.abspath(os.path.join(args.feature_hits_dir, file_name)) + feature_hits_files.append(file_path) + + draw_amr_matrix(feature_hits_files, args.amr_gene_drug_file, args.output_dir)