ArticleDatabase : the journal of biological databases and curation2015
SORTA: a system for ontology-based re-coding and technical annotation of biomedical phenotype data.
Article in Database : the journal of biological databases and curation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Article
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- Residual allelic activity likely underlies the low rates of disease expression for predicted loss-of-function variants in population-scale biobanks.American journal of human genetics · 2025Article
- Pretrained language models for semantics-aware data harmonisation of observational clinical studies in the era of big data.BMC medical informatics and decision making · 2025Article
- The text2term tool to map free-text descriptions of biomedical terms to ontologies.Database : the journal of biological databases and curation · 2024Article
- FastHPOCR: pragmatic, fast, and accurate concept recognition using the human phenotype ontology.Bioinformatics (Oxford, England) · 2024Article
- Disentangling the heterogeneity of multiple sclerosis through identification of independent neuropathological dimensions.Acta neuropathologica · 2024Article
- Term-BLAST-like alignment tool for concept recognition in noisy clinical texts.Bioinformatics (Oxford, England) · 2023Article
- Semi-automatic translation of medicine usage data (in Dutch, free-text) from Lifelines COVID-19 questionnaires to ATC codes.Database : the journal of biological databases and curation · 2023Article
- Linking rare and common disease vocabularies by mapping between the human phenotype ontology and phecodes.JAMIA open · 2023Article
- Addressing the clinical unmet needs in primary Sjögren's Syndrome through the sharing, harmonization and federated analysis of 21 European cohorts.Computational and structural biotechnology journal · 2022Article
- The de novo FAIRification process of a registry for vascular anomalies.Orphanet journal of rare diseases · 2021Article
- Developing the building blocks to elucidate the impact of the urban exposome on cardiometabolic-pulmonary disease: The EU EXPANSE project.Environmental epidemiology (Philadelphia, Pa.) · 2021Article
- PhenoTagger: a hybrid method for phenotype concept recognition using human phenotype ontology.Bioinformatics (Oxford, England) · 2021Article
- A phenome-wide association study of 26 mendelian genes reveals phenotypic expressivity of common and rare variants within the general population.PLoS genetics · 2020Article
- Overcoming the Barriers That Obscure the Interlinking and Analysis of Clinical Data Through Harmonization and Incremental Learning.IEEE open journal of engineering in medicine and biology · 2020Article
- MOLGENIS research: advanced bioinformatics data software for non-bioinformaticians.Bioinformatics (Oxford, England) · 2019Article
- MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive.Bioinformatics (Oxford, England) · 2017Article
- SCALEUS: Semantic Web Services Integration for Biomedical Applications.Journal of medical systems · 2017Article
- Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer.BioMed research international · 2017Article
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Authors and funding
14 authors.
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Abstract
There is an urgent need to standardize the semantics of biomedical data values, such as phenotypes, to enable comparative and integrative analyses. However, it is unlikely that all studies will use the same data collection protocols. As a result, retrospective standardization is often required, which involves matching of original (unstructured or locally coded) data to widely used coding or ontology systems such as SNOMED CT (clinical terms), ICD-10 (International Classification of Disease) and HPO (Human Phenotype Ontology). This data curation process is usually a time-consuming process performed by a human expert. To help mechanize this process, we have developed SORTA, a computer-aided system for rapidly encoding free text or locally coded values to a formal coding system or ontology. SORTA matches original data values (uploaded in semicolon delimited format) to a target coding system (uploaded in Excel spreadsheet, OWL ontology web language or OBO open biomedical ontologies format). It then semi- automatically shortlists candidate codes for each data value using Lucene and n-gram based matching algorithms, and can also learn from matches chosen by human experts. We evaluated SORTA's applicability in two use cases. For the LifeLines biobank, we used SORTA to recode 90 000 free text values (including 5211 unique values) about physical exercise to MET (Metabolic Equivalent of Task) codes. For the CINEAS clinical symptom coding system, we used SORTA to map to HPO, enriching HPO when necessary (315 terms matched so far). Out of the shortlists at rank 1, we found a precision/recall of 0.97/0.98 in LifeLines and of 0.58/0.45 in CINEAS. More importantly, users found the tool both a major time saver and a quality improvement because SORTA reduced the chances of human mistakes. Thus, SORTA can dramatically ease data (re)coding tasks and we believe it will prove useful for many more projects. Database URL: http://molgenis.org/sorta or as an open source download from http://www.molgenis.org/wiki/SORTA.
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