Deep phenotyping: symptom annotation made simple with SAMS. Issue Volume 50:Issue W1(2022) (7th May 2022)

• Record Type: Journal Article
• Authors: Steinhaus, Robin; Proft, Sebastian; Seelow, Evelyn; Schalau, Tobias; Robinson, Peter N; Seelow, Dominik
• Is Part Of: Nucleic acids research. Volume 50:Issue W1(2022)
• Page Start: W677
• Page End: W681
• Publication Date: 2022-05-07
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkac329
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Precision medicine needs precise phenotypes. The Human Phenotype Ontology (HPO) uses clinical signs instead of diagnoses and has become the standard annotation for patients' phenotypes when describing single gene disorders. Use of the HPO beyond human genetics is however still limited. With SAMS (Symptom Annotation Made Simple), we want to bring sign-based phenotyping to routine clinical care, to hospital patients as well as to outpatients. Our web-based application provides access to three widely used annotation systems: HPO, OMIM, Orphanet. Whilst data can be stored in our database, phenotypes can also be imported and exported as Global Alliance for Genomics and Health (GA4GH) Phenopackets without using the database. The web interface can easily be integrated into local databases, e.g. clinical information systems. SAMS offers users to share their data with others, empowering patients to record their own signs and symptoms (or those of their children) and thus provide their doctors with additional information. We think that our approach will lead to better characterised patients which is not only helpful for finding disease mutations but also to better understand the pathophysiology of diseases and to recruit patients for studies and clinical trials. SAMS is freely available at https://www.genecascade.org/SAMS/ . Graphical Abstract: