Genomic

Dataset Information

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PAGE: Global Reference Panel


ABSTRACT:

Stanford contributed samples to the PAGE study that can act as a population reference dataset across the globe. Therefore this dataset includes reference individuals, without phenotypes, chosen to help infer ancestry that will help us understand the diverse samples available in PAGE. The complete dataset comprises individuals of European, African, Asian, Oceanian, and Native American descent, from a total of over 50 populations. A subset of these individuals from Puno, Peru and Easter Island (Rapa Nui), Chile, are included in the PAGE samples that were whole genome sequenced in 2015. Additional details are available in the Study Acknowledgments.

The Global Reference Panel comprises 6 sample sets:

  • A population sample of Andean individuals primarily of Quechuan/Aymaran ancestry from Puno, Peru
  • A population sample of Easter Island (Rapa Nui), Chile
  • Individuals of indigenous origin from Oaxaca, Mexico
  • Individuals of indigenous origin from Honduras
  • Individuals of indigenous origin from Colombia
  • Individuals of indigenous origin from the Nama and Khomani KhoeSan populations of the Northern Cape, South Africa

In addition, we genotyped publicly available samples that will be hosted on the Bustamante lab website (https://bustamantelab.stanford.edu/). These comprise large public datasets to provide an open reference dataset for the world:

  • The additional related individuals from the Americas in the Human Genome Diversity Panel (H952) plus all additional samples from the Americas
  • A subset of the unrelated individuals from the Maasai in Kinyawa, Kenya (MKK) dataset from the International Hapmap Project hosted at Coriell

Additional samples will be available for restricted use with a data access agreement with the Bustamante Lab.

This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356).

PROVIDER: phs001033 | dbGaP |

SECONDARY ACCESSION(S): PRJNA302342PRJNA302341

REPOSITORIES: dbGaP

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