main.py

"""File containing the main function to run the program.

@author: Nina Singlan."""
from utils.utils import parse_args, create_graph, check_arguments
from utils.save import save_results, save_clusters_edge_list

# 1 - Parse command line arguments
args = parse_args()
check_arguments(args)

print(f"[Arguments parsed]", flush=True)

# 2 - Create the needed graph according to parameters
graph = create_graph(values=args.values, column_values_name=args.column_values_name,
                     column_genes_name=args.column_genes_name, datadir=args.datadir,
                     edge_list=args.file, separator=args.separator, database=args.original_graph,
                     specie=args.species, min_neighborhood=args.min_neighborhood, min_fusion=args.min_fusion,
                     min_cooccurence=args.min_cooccurrence, min_coexpression=args.min_coexpression,
                     min_experimental=args.min_experimental, min_database=args.min_database,
                     min_textmining=args.min_textmining, min_combined_score=args.min_combined_score,
                     inter_type=args.inter_type, min_confidence=args.min_confidence)

print(f"[Graph created]", flush=True)

# 3 - Run SIMBA
graph.compute_communities(minimum_nodes=args.min_nodes)

print(f"[Communities computed]", flush=True)

# 4 - Save the CSV results
save_results(path_to_file=args.output, graph=graph)

print(f"[Results saved]", flush=True)

if args.datadir is not None:
    # 5 - Save the clusters in the directory as edge list files
    save_clusters_edge_list(directory=args.datadir, graph=graph)

print(f"[Clusters saved]", flush=True)