disease-trajectories

What problem does it solve?

Mine disease trajectories (DT/DisTraj) outputs for comorbidity/trajectory candidates, including parsing DT JSON/TSV, extracting directed pairs, filtering by sex or significance, and mapping signals into dismech comorbidity YAML.

Core Features & Use Cases

• Parses DT artifacts (JSON/phase_dict or edge lists) and normalizes to disease_a_id, disease_b_id, directionality, and statistical fields.
• Supports sex-based and significance filtering to focus on relevant comorbidity signals.
• Maps signals into dismech comorbidity YAML for downstream validation and knowledge-base integration.
• Use cases include converting DisTraj outputs into YAML inputs for the dismech knowledge base and related pipelines.

Quick Start

Run dt_extract_edges.py on a DT JSON file to produce a normalized edge list, then map selected edges to dismech comorbidity YAML signals.