Technologies standards: Phenopackets

# The following block describes Decreased fetal movement.

- type:
    id: "HP:0001558"
    label: "Decreased fetal movement"
  onset:
    ontologyClass:
      id: "HP:0011461"
      label: "Fetal onset"
  evidence:
  - evidenceCode:
      id: "ECO:0000033"
      label: "author statement supported by traceable reference"
    reference:
      id: "PMID:30808312"
      description: "COL6A1 mutation leading to Bethlem myopathy with recurrent hematuria:\
        \ a case report."

Documentation https://phenopacket-schema.readthedocs.io/en/latest/

GitHub https://github.com/phenopackets/phenopacket-schema

Description

Phenopackets are a standard data format designed for sharing structured information about phenotypic abnormalities and their associations with genetic or other data. Developed by the Global Alliance for Genomics and Health (GA4GH), phenopackets capture detailed information about a patient’s phenotype, medical history, and, optionally, genetic data such as variants or omics findings. This standard enables interoperability across research and clinical settings, allowing consistent representation and exchange of data in studies of rare diseases, cancer, and other areas where phenotype-genotype correlations are critical.

Phenopackets are designed to work closely with the HPO ontology for phenotype, and the VRS standard for genomic variant representation. Phenopackets have a native binary format defined using Protocol Buffers (protobuf), and may be encoded in JSON or YAML making them machine-readable while maintaining human interpretability. Phenopackets are registered as an ISO standard

What they are not

Phenopackets are not a comprehensive electronic health record (EHR) or a system for managing clinical workflows. Instead, they focus on phenotypic and genomic data and are intended to complement, not replace, existing clinical or research systems. The format is specific, structured, and optimized for cross-platform data sharing and integration into bioinformatics pipelines or research projects. The phenopacket schema is not designed as a primary data storage schema (cf. OMOP)

Phenopackets and FHIR differ significantly in their scope. Phenopackets focus on capturing detailed phenotypic and genomic data, particularly for research and precision medicine use cases like rare diseases and cancer. They are designed to facilitate data sharing between researchers and clinicians by providing a standardized, lightweight format for describing phenotypes, diagnoses, genetic findings, and medical histories.

In contrast, FHIR (Fast Healthcare Interoperability Resources) has a much broader scope, covering all aspects of healthcare data exchange. FHIR is designed for clinical and administrative use cases, including patient records, medication management, scheduling, billing, and much more. It provides a comprehensive framework for healthcare interoperability and supports a wide variety of data types and workflows.

Technical Implementation

The technical implementation of phenopackets is simple and focused. They use JSON or Protocol Buffers for encoding, which makes them lightweight, easy to parse, and well-suited for research pipelines. The schema is specific, concise, and tailored to phenotypic and genomic data, enabling rapid adoption for its niche use cases. Phenopackets rely heavily on controlled vocabularies, such as the Human Phenotype Ontology (HPO), to ensure consistency in describing phenotypic abnormalities.

(FHIR, in contrast, is a comprehensive and modular standard based on RESTful APIs and supports data representation in JSON, XML, or RDF. Its resources are highly extensible and interoperable, allowing for detailed customization to fit the needs of diverse healthcare systems. However, FHIR’s complexity can make implementation challenging, especially for organizations with limited technical resources.)