SAMS
SAMS annotates patient phenotypes using Human Phenotype Ontology (HPO), OMIM, and Orphanet to enable standardized phenotypic characterization and data sharing for precision medicine.
Key Features:
- Integration with annotation resources: Provides access to Human Phenotype Ontology (HPO), OMIM, and Orphanet for comprehensive phenotype characterization using standardized clinical signs.
- Data storage and interoperability: Stores phenotype data in an internal database and supports import and export of phenotypes as Global Alliance for Genomics and Health (GA4GH) Phenopackets for compatibility with genomic data standards.
- Patient-reported phenotype capture: Supports recording of patient- or guardian-reported symptoms to include patient-reported data in phenotype records.
- Clinical-sign–based annotation: Leverages HPO's focus on clinical signs rather than diagnoses to produce precise, standardized phenotype descriptions applicable in genetic and non-genetic contexts.
Scientific Applications:
- Precision phenotyping: Enables detailed phenotypic characterization of patients to inform precision medicine approaches.
- Variant and disease mutation identification: Provides standardized phenotype data to support identification and interpretation of disease-causing mutations.
- Pathophysiology research: Facilitates studies of disease mechanisms by supplying harmonized clinical-sign phenotypic datasets.
- Clinical study recruitment and data sharing: Supports collection and sharing of phenotype data to aid patient recruitment for clinical studies and trials via GA4GH Phenopackets.
Methodology:
Annotates phenotypes using HPO clinical-sign terms, integrates phenotype information with OMIM and Orphanet, stores phenotypes in an internal database, and imports/exports phenotype data using GA4GH Phenopackets.
Topics
Details
- Cost:
- Free of charge
- Tool Type:
- web application
- Operating Systems:
- Mac, Linux, Windows
- Added:
- 8/17/2022
- Last Updated:
- 11/24/2024
Operations
Data Inputs & Outputs
Database search
Outputs
Publications
Steinhaus R, Proft S, Seelow E, Schalau T, Robinson PN, Seelow D. Deep phenotyping: symptom annotation made simple with SAMS. Nucleic Acids Research. 2022;50(W1):W677-W681. doi:10.1093/nar/gkac329. PMID:35524573. PMCID:PMC9252818.
DOI: 10.1093/nar/gkac329
PMID: 35524573
PMCID: PMC9252818
Funding: - NIH NHGRI: RM1HG010860
- Deutsche Forschungsgemeinschaft: FOR2841 TP05, TP09