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VARAdb: a comprehensive variation annotation database for human

With the study of human diseases and biological processes increasing, a large number of non-coding variants have been identified and facilitated. The rapid accumulation of genetic and epigenomic information has resulted in an urgent need to collect and process data to explore the regulation of non-c...

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Detalles Bibliográficos
Autores principales: Pan, Qi, Liu, Yue-Juan, Bai, Xue-Feng, Han, Xiao-Le, Jiang, Yong, Ai, Bo, Shi, Shan-Shan, Wang, Fan, Xu, Ming-Cong, Wang, Yue-Zhu, Zhao, Jun, Chen, Jia-Xin, Zhang, Jian, Li, Xue-Cang, Zhu, Jiang, Zhang, Guo-Rui, Wang, Qiu-Yu, Li, Chun-Quan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779011/
https://www.ncbi.nlm.nih.gov/pubmed/33095866
http://dx.doi.org/10.1093/nar/gkaa922
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author Pan, Qi
Liu, Yue-Juan
Bai, Xue-Feng
Han, Xiao-Le
Jiang, Yong
Ai, Bo
Shi, Shan-Shan
Wang, Fan
Xu, Ming-Cong
Wang, Yue-Zhu
Zhao, Jun
Chen, Jia-Xin
Zhang, Jian
Li, Xue-Cang
Zhu, Jiang
Zhang, Guo-Rui
Wang, Qiu-Yu
Li, Chun-Quan
author_facet Pan, Qi
Liu, Yue-Juan
Bai, Xue-Feng
Han, Xiao-Le
Jiang, Yong
Ai, Bo
Shi, Shan-Shan
Wang, Fan
Xu, Ming-Cong
Wang, Yue-Zhu
Zhao, Jun
Chen, Jia-Xin
Zhang, Jian
Li, Xue-Cang
Zhu, Jiang
Zhang, Guo-Rui
Wang, Qiu-Yu
Li, Chun-Quan
author_sort Pan, Qi
collection PubMed
description With the study of human diseases and biological processes increasing, a large number of non-coding variants have been identified and facilitated. The rapid accumulation of genetic and epigenomic information has resulted in an urgent need to collect and process data to explore the regulation of non-coding variants. Here, we developed a comprehensive variation annotation database for human (VARAdb, http://www.licpathway.net/VARAdb/), which specifically considers non-coding variants. VARAdb provides annotation information for 577,283,813 variations and novel variants, prioritizes variations based on scores using nine annotation categories, and supports pathway downstream analysis. Importantly, VARAdb integrates a large amount of genetic and epigenomic data into five annotation sections, which include ‘Variation information’, ‘Regulatory information’, ‘Related genes’, ‘Chromatin accessibility’ and ‘Chromatin interaction’. The detailed annotation information consists of motif changes, risk SNPs, LD SNPs, eQTLs, clinical variant-drug-gene pairs, sequence conservation, somatic mutations, enhancers, super enhancers, promoters, transcription factors, chromatin states, histone modifications, chromatin accessibility regions and chromatin interactions. This database is a user-friendly interface to query, browse and visualize variations and related annotation information. VARAdb is a useful resource for selecting potential functional variations and interpreting their effects on human diseases and biological processes.
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spelling pubmed-77790112021-01-06 VARAdb: a comprehensive variation annotation database for human Pan, Qi Liu, Yue-Juan Bai, Xue-Feng Han, Xiao-Le Jiang, Yong Ai, Bo Shi, Shan-Shan Wang, Fan Xu, Ming-Cong Wang, Yue-Zhu Zhao, Jun Chen, Jia-Xin Zhang, Jian Li, Xue-Cang Zhu, Jiang Zhang, Guo-Rui Wang, Qiu-Yu Li, Chun-Quan Nucleic Acids Res Database Issue With the study of human diseases and biological processes increasing, a large number of non-coding variants have been identified and facilitated. The rapid accumulation of genetic and epigenomic information has resulted in an urgent need to collect and process data to explore the regulation of non-coding variants. Here, we developed a comprehensive variation annotation database for human (VARAdb, http://www.licpathway.net/VARAdb/), which specifically considers non-coding variants. VARAdb provides annotation information for 577,283,813 variations and novel variants, prioritizes variations based on scores using nine annotation categories, and supports pathway downstream analysis. Importantly, VARAdb integrates a large amount of genetic and epigenomic data into five annotation sections, which include ‘Variation information’, ‘Regulatory information’, ‘Related genes’, ‘Chromatin accessibility’ and ‘Chromatin interaction’. The detailed annotation information consists of motif changes, risk SNPs, LD SNPs, eQTLs, clinical variant-drug-gene pairs, sequence conservation, somatic mutations, enhancers, super enhancers, promoters, transcription factors, chromatin states, histone modifications, chromatin accessibility regions and chromatin interactions. This database is a user-friendly interface to query, browse and visualize variations and related annotation information. VARAdb is a useful resource for selecting potential functional variations and interpreting their effects on human diseases and biological processes. Oxford University Press 2020-10-23 /pmc/articles/PMC7779011/ /pubmed/33095866 http://dx.doi.org/10.1093/nar/gkaa922 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Issue
Pan, Qi
Liu, Yue-Juan
Bai, Xue-Feng
Han, Xiao-Le
Jiang, Yong
Ai, Bo
Shi, Shan-Shan
Wang, Fan
Xu, Ming-Cong
Wang, Yue-Zhu
Zhao, Jun
Chen, Jia-Xin
Zhang, Jian
Li, Xue-Cang
Zhu, Jiang
Zhang, Guo-Rui
Wang, Qiu-Yu
Li, Chun-Quan
VARAdb: a comprehensive variation annotation database for human
title VARAdb: a comprehensive variation annotation database for human
title_full VARAdb: a comprehensive variation annotation database for human
title_fullStr VARAdb: a comprehensive variation annotation database for human
title_full_unstemmed VARAdb: a comprehensive variation annotation database for human
title_short VARAdb: a comprehensive variation annotation database for human
title_sort varadb: a comprehensive variation annotation database for human
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779011/
https://www.ncbi.nlm.nih.gov/pubmed/33095866
http://dx.doi.org/10.1093/nar/gkaa922
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