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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...

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Autores principales: Liu, Zhu, Mushayahama, Tremayne, Queme, Bryan, Ebert, Dustin, Muruganujan, Anushya, Mills, Caitlin, Thomas, Paul D, Mi, Huaiyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
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.
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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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