ArticleJournal of biomedical semantics2014
Variation ontology: annotator guide.
Article in Journal of biomedical semantics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- BTKbase, Bruton Tyrosine Kinase Variant Database in X-Linked Agammaglobulinemia: Looking Back and Ahead.Human mutation · 2023Article
- Systematics for types and effects of RNA variations.RNA biology · 2021Article
- Systematics for types and effects of DNA variations.BMC genomics · 2018Review
- Human Variome Project Quality Assessment Criteria for Variation Databases.Human mutation · 2016Article
- Types and effects of protein variations.Human genetics · 2015Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSystematic representation of information related to genetic and non-genetic variations is required to allow large scale studies, data mining and data integration, and to make it possible to reveal novel relationships between genotype and phenotype. Although lots of variation data is available it is often difficult to use due to lack of systematics.
resultsA novel ontology, Variation Ontology (VariO http://variationontology.org), was developed for annotation of effects, consequences and mechanisms of variations. In this article instructions are provided on how VariO annotations are made. The major levels for description are the three molecules, namely DNA, RNA and protein. They are further divided to four major sublevels: variation type, function, structure, and property, and further up to eight sublevels. VariO annotation summarizes existing knowledge about a variation and its effects and formalizes it so that computational analyses are efficient. The annotations should be made on as many levels as possible. VariO annotations are made in reference to normal states, which vary for each data item including e.g. reference sequences, wild type properties, and activities.
conclusionsDetailed instructions together with examples are provided to indicate how VariO can be used for annotation of variations and their effects. A dedicated tool has been developed for annotation and will be further developed to cover also evidence for the annotations. VariO is suitable for annotation of data in many types of databases. As several different kinds of databases are in a process of adapting VariO annotations it is important to have guidelines to guarantee consistent annotation.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.