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PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform
Structural variations (SVs) play important roles in human evolution and diseases, but there is a lack of data resources concerning representative samples, especially for East Asians. Taking advantage of both next-generation sequencing and third-generation sequencing data at the whole-genome level, w...
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/PMC9825616/ https://www.ncbi.nlm.nih.gov/pubmed/36243989 http://dx.doi.org/10.1093/nar/gkac905 |
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author | Wang, Yimin Ling, Yunchao Gong, Jiao Zhao, Xiaohan Zhou, Hanwen Xie, Bo Lou, Haiyi Zhuang, Xinhao Jin, Li Fan, Shaohua Zhang, Guoqing Xu, Shuhua |
author_facet | Wang, Yimin Ling, Yunchao Gong, Jiao Zhao, Xiaohan Zhou, Hanwen Xie, Bo Lou, Haiyi Zhuang, Xinhao Jin, Li Fan, Shaohua Zhang, Guoqing Xu, Shuhua |
author_sort | Wang, Yimin |
collection | PubMed |
description | Structural variations (SVs) play important roles in human evolution and diseases, but there is a lack of data resources concerning representative samples, especially for East Asians. Taking advantage of both next-generation sequencing and third-generation sequencing data at the whole-genome level, we developed the database PGG.SV to provide a practical platform for both regionally and globally representative structural variants. In its current version, PGG.SV archives 584 277 SVs obtained from whole-genome sequencing data of 6048 samples, including 1030 long-read sequencing genomes representing 177 global populations. PGG.SV provides (i) high-quality SVs with fine-scale and precise genomic locations in both GRCh37 and GRCh38, covering underrepresented SVs in existing sequencing and microarray data; (ii) hierarchical estimation of SV prevalence in geographical populations; (iii) informative annotations of SV-related genes, potential functions and clinical effects; (iv) an analysis platform to facilitate SV-based case-control association studies and (v) various visualization tools for understanding the SV structures in the human genome. Taken together, PGG.SV provides a user-friendly online interface, easy-to-use analysis tools and a detailed presentation of results. PGG.SV is freely accessible via https://www.biosino.org/pggsv. |
format | Online Article Text |
id | pubmed-9825616 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98256162023-01-10 PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform Wang, Yimin Ling, Yunchao Gong, Jiao Zhao, Xiaohan Zhou, Hanwen Xie, Bo Lou, Haiyi Zhuang, Xinhao Jin, Li Fan, Shaohua Zhang, Guoqing Xu, Shuhua Nucleic Acids Res Database Issue Structural variations (SVs) play important roles in human evolution and diseases, but there is a lack of data resources concerning representative samples, especially for East Asians. Taking advantage of both next-generation sequencing and third-generation sequencing data at the whole-genome level, we developed the database PGG.SV to provide a practical platform for both regionally and globally representative structural variants. In its current version, PGG.SV archives 584 277 SVs obtained from whole-genome sequencing data of 6048 samples, including 1030 long-read sequencing genomes representing 177 global populations. PGG.SV provides (i) high-quality SVs with fine-scale and precise genomic locations in both GRCh37 and GRCh38, covering underrepresented SVs in existing sequencing and microarray data; (ii) hierarchical estimation of SV prevalence in geographical populations; (iii) informative annotations of SV-related genes, potential functions and clinical effects; (iv) an analysis platform to facilitate SV-based case-control association studies and (v) various visualization tools for understanding the SV structures in the human genome. Taken together, PGG.SV provides a user-friendly online interface, easy-to-use analysis tools and a detailed presentation of results. PGG.SV is freely accessible via https://www.biosino.org/pggsv. Oxford University Press 2022-10-16 /pmc/articles/PMC9825616/ /pubmed/36243989 http://dx.doi.org/10.1093/nar/gkac905 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Wang, Yimin Ling, Yunchao Gong, Jiao Zhao, Xiaohan Zhou, Hanwen Xie, Bo Lou, Haiyi Zhuang, Xinhao Jin, Li Fan, Shaohua Zhang, Guoqing Xu, Shuhua PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform |
title | PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform |
title_full | PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform |
title_fullStr | PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform |
title_full_unstemmed | PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform |
title_short | PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform |
title_sort | pgg.sv: a whole-genome-sequencing-based structural variant resource and data analysis platform |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825616/ https://www.ncbi.nlm.nih.gov/pubmed/36243989 http://dx.doi.org/10.1093/nar/gkac905 |
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