phenosign ============ **phenosign** is a Python library for analyzing correlations and synergy in `GA4GH Phenopacket `_ cohorts. It provides tools to systematically process `Human Phenotype Ontology `_ (HPO) features, identify pairwise associations, and detect higher-order interactions relevant to diseases or variant conditions. Overview -------- Phenotypic features often co-occur or interact in complex ways across individuals. Understanding these relationships can provide insights into disease mechanisms, genotype-phenotype associations, and combinatorial biomarkers. **phenosign enables:** - Construction of structured datasets from phenopacket cohorts - Pairwise correlation analysis of HPO terms - Detection of higher-order feature interactions (synergy) - Interactive visualization of correlation and synergy heatmaps Quick Example ------------- .. code-block:: python from pathlib import Path import json from phenosign import ( PhenotypeDatasetBuilder, HPOCorrelationAnalyzer, ) # Load phenopackets phenopacket_dir = Path("path/to/your/fbn1_phenopackets/") phenopackets = [] for file_path in phenopacket_dir.glob("*.json"): with open(file_path, "r", encoding="utf-8") as f: data: str = f.read() phenopacket: Phenopacket = Parse(data, Phenopacket()) phenopackets.append(phenopacket) # Build dataset dataset = PhenotypeDatasetBuilder(phenopackets).build() # Run correlation analysis analyzer = HPOCorrelationAnalyzer(dataset) results = analyzer.compute_correlation_matrix() results.result_table.head() This minimal example demonstrates the workflow: **load phenopackets → build dataset → compute correlations** .. toctree:: :maxdepth: 1 :caption: Getting Started installation .. toctree:: :maxdepth: 1 :caption: Tutorial tutorial .. toctree:: :maxdepth: 1 :caption: Usage usage/dataset usage/correlation usage/synergy .. toctree:: :maxdepth: 1 :caption: API Reference api/phenosign