The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species

TLDR

In biology and biomedicine, linking phenotypic outcomes to genetic variation and environmental factors remains challenging due to mismatched phenotypes, uncharacterized genes, species differences, unknown environmental influences, and fragmented resources; since its 2015 launch, the Monarch Initiative has expanded data, ontologies, APIs, and a redesigned interface to address these gaps. The Monarch Initiative aims to integrate genetic and phenotypic data across species and enable ontology‑based search. It develops widely adopted ontologies such as Mondo, HPO, and uPheno, and algorithms that support computational analysis, mechanistic discovery, diagnostics, and identification of animal models through phenotypic similarity, and is integrated with GA4GH and NCATS Translator. The platform’s ontologies and tools are widely used to identify animal disease models, support differential diagnostics and translational research, and are incorporated into GA4GH and NCATS Translator for mechanistic discovery.

Abstract

Abstract In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.