Mouse Phenome Database

Mouse Phenome Database provides a centralized repository of primary per-animal phenotype data from laboratory mice, including naïve and drug- or environment-exposed animals, with curated protocols, ontology-based annotations, and tools to support genome–phenome and trait association analyses.

Key Features:

• Primary per-animal phenotype data: Curated per-animal measurements accompanied by detailed experimental protocols to support reproducibility.
• APIs: Programmatic access to data and analytical functions via APIs.
• Analysis and visualization tools: Integrated computational tools for analysis and visualization of curated phenotype data.
• Ontology and controlled vocabulary annotations: Use of public ontologies and controlled vocabularies to standardize annotations and enable cross-study integration.
• Genetic analysis support: Tools to explore genome–phenome relationships and perform genetic analyses.
• Diverse strain and population coverage: Data from inbred strains, recombinant inbred lines, F1 hybrids, transgenic models, targeted mutants, chromosome substitution strains, Collaborative Crosses, Diversity Outbreds, and other mapping populations.
• Advanced analytical capabilities: Support for trait association analyses, reproducibility assessments, polygenic syndrome model selection, and multi-trait modeling.

Scientific Applications:

• Genome–phenome mapping: Association of phenotypic endpoints with genetic variation across diverse mouse populations.
• Trait association studies: Identification and analysis of trait associations and candidate loci.
• Reproducibility assessment: Cross-study comparisons using per-animal data and standardized protocols to evaluate reproducibility.
• Polygenic syndrome model selection: Selection and evaluation of mouse models representing complex, multigenic syndromes.
• Multi-trait modeling and integrative analyses: Joint analysis of multiple phenotypes to study pleiotropy and trait covariance.
• Treatment and exposure studies: Analysis of phenotype changes in mice subjected to drugs or environmental agents.
• Translational physiology and disease research: Integration of phenotypic and genetic data to support studies with translational relevance.

Methodology:

Data curation at the per-animal level with linked experimental protocols; annotations using public ontologies and controlled vocabularies; programmatic access via APIs; computational support including analysis and visualization tools, genetic analysis methods, trait association testing, reproducibility assessment, polygenic syndrome model selection, and multi-trait modeling.