Evolution of the Sequence Ontology terms and relationships

The Sequence Ontology is undergoing reform to meet the standards of the OBO Foundry. Here we report some of the incremental changes and improvements made to SO. We also propose new relationships to better define the mereological, spatial and temporal aspects of biological sequence

Evolution of the Sequence Ontology terms and relationships

AbstractThe Sequence Ontology is an established ontology, with a large user community, for the purpose of genomic annotation. We are reforming the ontology to provide better terms and relationships to describe the features of biological sequence, for both genomic and derived sequence. The SO is working within the guidelines of the OBO Foundry to provide interoperability between SO and the other related OBO ontologies. Here, we report changes and improvements made to SO including new relationships to better define the mereological, spatial and temporal aspects of biological sequence

Quantitative measures for the management and comparison of annotated genomes

<p>Abstract</p> <p>Background</p> <p>The ever-increasing number of sequenced and annotated genomes has made management of their annotations a significant undertaking, especially for large eukaryotic genomes containing many thousands of genes. Typically, changes in gene and transcript numbers are used to summarize changes from release to release, but these measures say nothing about changes to individual annotations, nor do they provide any means to identify annotations in need of manual review.</p> <p>Results</p> <p>In response, we have developed a suite of quantitative measures to better characterize changes to a genome's annotations between releases, and to prioritize problematic annotations for manual review. We have applied these measures to the annotations of five eukaryotic genomes over multiple releases – <it>H. sapiens</it>, <it>M. musculus</it>, <it>D. melanogaster</it>, <it>A. gambiae</it>, and <it>C. elegans</it>.</p> <p>Conclusion</p> <p>Our results provide the first detailed, historical overview of how these genomes' annotations have changed over the years, and demonstrate the usefulness of these measures for genome annotation management.</p

Sequence Ontology Annotation Guide

This Sequence Ontology (SO) [13] aims to unify the way in which we describe sequence annotations, by providing a controlled vocabulary of terms and the relationships between them. Using SO terms to label the parts of sequence annotations greatly facilitates downstream analyses of their contents, as it ensures that annotations produced by different groups conform to a single standard. This greatly facilitates analyses of annotation contents and characteristics, e.g. comparisons of UTRs, alternative splicing, etc. Because SO also specifies the relationships between features, e.g. part_of, kind_of, annotations described with SO terms are also better substrates for validation and visualization software

The RNA Ontology (RNAO): An ontology for integrating RNA sequence and structure data

Biomedical Ontologies are intended to integrate diverse biomedical data to enable intelligent data-mining and facilitate translation of basic research into useful clinical knowledge. We present the first version of RNAO, an ontology for integrating RNA 3D structural, biochemical and sequence data. While each 3D data file depicts the structure of a specific molecule, such data have broader significance as representatives of classes of homologous molecules, which, while differing in sequence, generally share core structural features of functional importance. Thus, 3D structure data gain value by being linked to homologous sequences in genomic data and databases of sequence alignments. Likewise genomic data can increase in value by annotation of shared structural features, especially when these can be linked to specific functions. The RNAO is being developed in line with the developing standards of the Open Biomedical Ontologies (OBO) Consortium

A domain ontology for the non-coding RNA field

Identification of non-coding RNAs (ncRNAs) has been significantly enhanced due to the rapid advancement in sequencing technologies. On the other hand, semantic annotation of ncRNA data lag behind their identification, and there is a great need to effectively integrate discovery from relevant communities. To this end, the Non-Coding RNA Ontology (NCRO) is being developed to provide a precisely defined ncRNA controlled vocabulary, which can fill a specific and highly needed niche in unification of ncRNA biology

The Non-Coding RNA Ontology : a comprehensive resource for the unification of non-coding RNA biology

In recent years, sequencing technologies have enabled the identification of a wide range of non-coding RNAs (ncRNAs). Unfortunately, annotation and integration of ncRNA data has lagged behind their identification. Given the large quantity of information being obtained in this area, there emerges an urgent need to integrate what is being discovered by a broad range of relevant communities. To this end, the Non-Coding RNA Ontology (NCRO) is being developed to provide a systematically structured and precisely defined controlled vocabulary for the domain of ncRNAs, thereby facilitating the discovery, curation, analysis, exchange, and reasoning of data about structures of ncRNAs, their molecular and cellular functions, and their impacts upon phenotypes. The goal of NCRO is to serve as a common resource for annotations of diverse research in a way that will significantly enhance integrative and comparative analysis of the myriad resources currently housed in disparate sources. It is our belief that the NCRO ontology can perform an important role in the comprehensive unification of ncRNA biology and, indeed, fill a critical gap in both the Open Biological and Biomedical Ontologies (OBO) Library and the National Center for Biomedical Ontology (NCBO) BioPortal. Our initial focus is on the ontological representation of small regulatory ncRNAs, which we see as the first step in providing a resource for the annotation of data about all forms of ncRNAs. The NCRO ontology is free and open to all users

The Sequence Ontology: a tool for the unification of genome annotations.

The Sequence Ontology (SO) is a structured controlled vocabulary for the parts of a genomic annotation. SO provides a common set of terms and definitions that will facilitate the exchange, analysis and management of genomic data. Because SO treats part-whole relationships rigorously, data described with it can become substrates for automated reasoning, and instances of sequence features described by the SO can be subjected to a group of logical operations termed extensional mereology operators.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

The development of non-coding RNA ontology

Identification of non-coding RNAs (ncRNAs) has been significantly improved over the past decade. On the other hand, semantic annotation of ncRNA data is facing critical challenges due to the lack of a comprehensive ontology to serve as common data elements and data exchange standards in the field. We developed the Non-Coding RNA Ontology (NCRO) to handle this situation. By providing a formally defined ncRNA controlled vocabulary, the NCRO aims to fill a specific and highly needed niche in semantic annotation of large amounts of ncRNA biological and clinical data

A standard variation file format for human genome sequences

Here we describe the Genome Variation Format (GVF) and the 10Gen dataset. GVF, an extension of Generic Feature Format version 3 (GFF3), is a simple tab-delimited format for DNA variant files, which uses Sequence Ontology to describe genome variation data. The 10Gen dataset, ten human genomes in GVF format, is freely available for community analysis from the Sequence Ontology website and from an Amazon elastic block storage (EBS) snapshot for use in Amazon's EC2 cloud computing environment