Your browser doesn't support javascript.
loading
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.
Afiliación
  • Wang Y; Key Laboratory of Computational Biology, National Genomics Data Center & Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • Ling Y; Key Laboratory of Computational Biology, National Genomics Data Center & Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • Gong J; State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China.
  • Zhao X; Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China.
  • Zhou H; State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China.
  • Xie B; Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China.
  • Lou H; Key Laboratory of Computational Biology, National Genomics Data Center & Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • Zhuang X; Key Laboratory of Computational Biology, National Genomics Data Center & Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • Jin L; State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China.
  • Fan S; State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China.
  • Zhang G; Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China.
Nucleic Acids Res ; 51(D1): D1109-D1116, 2023 01 06.
Article en En | MEDLINE | ID: mdl-36243989
ABSTRACT
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Genómica / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Risk_factors_studies Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Genómica / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Risk_factors_studies Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2023 Tipo del documento: Article País de afiliación: China
...