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Deep phenotyping: symptom annotation made simple with SAMS

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 (Sy...

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Autores principales: Steinhaus, Robin, Proft, Sebastian, Seelow, Evelyn, Schalau, Tobias, Robinson, Peter N, Seelow, Dominik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252818/
https://www.ncbi.nlm.nih.gov/pubmed/35524573
http://dx.doi.org/10.1093/nar/gkac329
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author Steinhaus, Robin
Proft, Sebastian
Seelow, Evelyn
Schalau, Tobias
Robinson, Peter N
Seelow, Dominik
author_facet Steinhaus, Robin
Proft, Sebastian
Seelow, Evelyn
Schalau, Tobias
Robinson, Peter N
Seelow, Dominik
author_sort Steinhaus, Robin
collection PubMed
description 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/.
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spelling pubmed-92528182022-07-05 Deep phenotyping: symptom annotation made simple with SAMS Steinhaus, Robin Proft, Sebastian Seelow, Evelyn Schalau, Tobias Robinson, Peter N Seelow, Dominik Nucleic Acids Res Web Server Issue 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/. Oxford University Press 2022-05-07 /pmc/articles/PMC9252818/ /pubmed/35524573 http://dx.doi.org/10.1093/nar/gkac329 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Web Server Issue
Steinhaus, Robin
Proft, Sebastian
Seelow, Evelyn
Schalau, Tobias
Robinson, Peter N
Seelow, Dominik
Deep phenotyping: symptom annotation made simple with SAMS
title Deep phenotyping: symptom annotation made simple with SAMS
title_full Deep phenotyping: symptom annotation made simple with SAMS
title_fullStr Deep phenotyping: symptom annotation made simple with SAMS
title_full_unstemmed Deep phenotyping: symptom annotation made simple with SAMS
title_short Deep phenotyping: symptom annotation made simple with SAMS
title_sort deep phenotyping: symptom annotation made simple with sams
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252818/
https://www.ncbi.nlm.nih.gov/pubmed/35524573
http://dx.doi.org/10.1093/nar/gkac329
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