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Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation
The Annotation Query (AnnoQ) (http://annoq.org/) is designed to provide comprehensive and up-to-date functional annotations for human genetic variants. The system is supported by an annotation database with ∼39 million human variants from the Haplotype Reference Consortium (HRC) pre-annotated with s...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252745/ https://www.ncbi.nlm.nih.gov/pubmed/35640593 http://dx.doi.org/10.1093/nar/gkac418 |
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author | Liu, Zhu Mushayahama, Tremayne Queme, Bryan Ebert, Dustin Muruganujan, Anushya Mills, Caitlin Thomas, Paul D Mi, Huaiyu |
author_facet | Liu, Zhu Mushayahama, Tremayne Queme, Bryan Ebert, Dustin Muruganujan, Anushya Mills, Caitlin Thomas, Paul D Mi, Huaiyu |
author_sort | Liu, Zhu |
collection | PubMed |
description | The Annotation Query (AnnoQ) (http://annoq.org/) is designed to provide comprehensive and up-to-date functional annotations for human genetic variants. The system is supported by an annotation database with ∼39 million human variants from the Haplotype Reference Consortium (HRC) pre-annotated with sequence feature annotations by WGSA and functional annotations to Gene Ontology (GO) and pathways in PANTHER. The database operates on an optimized Elasticsearch framework to support real-time complex searches. This implementation enables users to annotate data with the most up-to-date functional annotations via simple queries instead of setting up individual tools. A web interface allows users to interactively browse the annotations, annotate variants and search variant data. Its easy-to-use interface and search capabilities are well-suited for scientists with fewer bioinformatics skills such as bench scientists and statisticians. AnnoQ also has an API for users to access and annotate the data programmatically. Packages for programming languages, such as the R package, are available for users to embed the annotation queries in their scripts. AnnoQ serves researchers with a wide range of backgrounds and research interests as an integrated annotation platform. |
format | Online Article Text |
id | pubmed-9252745 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-92527452022-07-05 Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation Liu, Zhu Mushayahama, Tremayne Queme, Bryan Ebert, Dustin Muruganujan, Anushya Mills, Caitlin Thomas, Paul D Mi, Huaiyu Nucleic Acids Res Web Server Issue The Annotation Query (AnnoQ) (http://annoq.org/) is designed to provide comprehensive and up-to-date functional annotations for human genetic variants. The system is supported by an annotation database with ∼39 million human variants from the Haplotype Reference Consortium (HRC) pre-annotated with sequence feature annotations by WGSA and functional annotations to Gene Ontology (GO) and pathways in PANTHER. The database operates on an optimized Elasticsearch framework to support real-time complex searches. This implementation enables users to annotate data with the most up-to-date functional annotations via simple queries instead of setting up individual tools. A web interface allows users to interactively browse the annotations, annotate variants and search variant data. Its easy-to-use interface and search capabilities are well-suited for scientists with fewer bioinformatics skills such as bench scientists and statisticians. AnnoQ also has an API for users to access and annotate the data programmatically. Packages for programming languages, such as the R package, are available for users to embed the annotation queries in their scripts. AnnoQ serves researchers with a wide range of backgrounds and research interests as an integrated annotation platform. Oxford University Press 2022-05-30 /pmc/articles/PMC9252745/ /pubmed/35640593 http://dx.doi.org/10.1093/nar/gkac418 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 Liu, Zhu Mushayahama, Tremayne Queme, Bryan Ebert, Dustin Muruganujan, Anushya Mills, Caitlin Thomas, Paul D Mi, Huaiyu Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation |
title | Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation |
title_full | Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation |
title_fullStr | Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation |
title_full_unstemmed | Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation |
title_short | Annotation Query (AnnoQ): an integrated and interactive platform for large-scale genetic variant annotation |
title_sort | annotation query (annoq): an integrated and interactive platform for large-scale genetic variant annotation |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252745/ https://www.ncbi.nlm.nih.gov/pubmed/35640593 http://dx.doi.org/10.1093/nar/gkac418 |
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