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

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

Getting Started

Tutorial

Usage