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

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.

PMID: 35524573
PMCID: PMC9252818
Funding: - NIH NHGRI: RM1HG010860 - Deutsche Forschungsgemeinschaft: FOR2841 TP05, TP09

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