This initial implementation has now been archived - please refer to the phenopacket-schema repository for the current implementation.
PhenoPackets is an open standard for representing and sharing detailed descriptions of phenotypic abnormalities and characteristics of individual patients, organisms, diseases, and publications. This repository serves as the primary documentation about the PhenoPacket Exchange Format (PXF), including the JSON and YAML representations. Other repositories (see Implementations below) contain Java, JavaScript, Python and other language-specific tools and implementations.
The health of an individual organism results from a complex interplay between its genes and environment. Although great strides have been made in standardizing the representation of genetic information for exchange, there are no comparable standards to represent phenotypes (e.g. patient symptoms and disease features) and environmental factors. Phenotypic abnormalities of individual organisms are currently described in diverse places and in diverse formats: publications, databases, health records, registries, clinical trials, and even social media. However, the lack of standardization, accessibility, and computability among these contexts makes it extremely difficult to effectively extract and utilize these data, hindering the understanding of genetic and environmental contributions to disease.
See the Phenopackets.org site for the public-facing project documentation.
Or, see the detailed Markdown-based documentation via GitHub.
The Wiki has additional documentation, although it may be out-of-date.
- phenopacket-reference-implementation: Java Reference Implementation.
- phenopackets-js: JavaScript Implementation.
- phenopacket-python: Python Implementation.
- pxftools: Command-line Utility for manipulating PhenoPackets.
The PhenoPackets standard is still evolving, and there are many opportunities to help, including improving the expressivity of the format and providing implementations that enable.
The Issue Tracker is a good start.