PGG SV

PGG SV catalogs structural variants from whole-genome next-generation sequencing (NGS) and third-generation long-read sequencing to characterize population-level SV diversity and support association analyses.


Key Features:

  • Extensive SV Archive: Contains 584,277 structural variants derived from whole-genome sequencing of 6,048 samples, including 1,030 long-read genomes representing 177 global populations.
  • High-Quality Data with Precision: Provides fine-scale SV coordinates mapped to both GRCh37 and GRCh38 reference assemblies.
  • Geographical Prevalence Estimation: Includes hierarchical estimation of SV prevalence across geographical populations.
  • Informative Annotations: Annotates SV-associated genes, potential functions, and clinical effects.
  • Research Facilitation Tools: Provides integrated analysis tools for SV-based case-control association studies.
  • Visualization Capabilities: Offers visualization tools for interpreting complex SV structures in the genome.

Scientific Applications:

  • Human Evolution: Enables analysis of structural variant patterns relevant to human evolutionary history.
  • Population Genetics: Supports characterization of SV diversity and population structure across global populations.
  • Disease Etiology: Facilitates investigation of structural variant contributions to disease susceptibility and clinical effects.
  • Association Studies: Enables SV-based case-control association studies to identify genotype–phenotype associations.

Methodology:

Integrates whole-genome NGS and third-generation long-read sequencing data for structural variant discovery and cataloging.

Topics

Details

License:
Not licensed
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Python, Shell, Perl
Added:
12/22/2022
Last Updated:
11/24/2024

Operations

Publications

Wang Y, Ling Y, Gong J, Zhao X, Zhou H, Xie B, Lou H, Zhuang X, Jin L, Fan S, Zhang G, Xu S. PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform. Nucleic Acids Research. 2022;51(D1):D1109-D1116. doi:10.1093/nar/gkac905. PMID:36243989. PMCID:PMC9825616.

PMID: 36243989
PMCID: PMC9825616
Funding: - Basic Science Center Program: 32288101 - National Natural Science Foundation of China: 31961130380, 32030020 - UK Royal Society-Newton Advanced Fellowship: NAF\R1\191094 - Shanghai Municipal Science and Technology: 2017SHZDZX01