PGG.Population: a database for understanding the genomic diversity and genetic ancestry of human populations

Nucleic Acids Res. 2018 Jan 4;46(D1):D984-D993. doi: 10.1093/nar/gkx1032.

Abstract

There are a growing number of studies focusing on delineating genetic variations that are associated with complex human traits and diseases due to recent advances in next-generation sequencing technologies. However, identifying and prioritizing disease-associated causal variants relies on understanding the distribution of genetic variations within and among populations. The PGG.Population database documents 7122 genomes representing 356 global populations from 107 countries and provides essential information for researchers to understand human genomic diversity and genetic ancestry. These data and information can facilitate the design of research studies and the interpretation of results of both evolutionary and medical studies involving human populations. The database is carefully maintained and constantly updated when new data are available. We included miscellaneous functions and a user-friendly graphical interface for visualization of genomic diversity, population relationships (genetic affinity), ancestral makeup, footprints of natural selection, and population history etc. Moreover, PGG.Population provides a useful feature for users to analyze data and visualize results in a dynamic style via online illustration. The long-term ambition of the PGG.Population, together with the joint efforts from other researchers who contribute their data to our database, is to create a comprehensive depository of geographic and ethnic variation of human genome, as well as a platform bringing influence on future practitioners of medicine and clinical investigators. PGG.Population is available at https://www.pggpopulation.org.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Databases, Genetic*
  • Ethnicity / genetics
  • Genetic Variation*
  • Genetics, Population*
  • Genome, Human*
  • Genomics
  • Genotype
  • High-Throughput Nucleotide Sequencing
  • Humans