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SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population

SND-ID: EXT 0285

Creator/Principal investigator(s)

Adam Ameur - Uppsala University orcid

Ulf Gyllensten - Uppsala University, Department of Immunology, Genetics and Pathology

Description

The SweGen contains whole-genome variant frequencies for 1000 Swedish individuals generated within the SweGen project. The data is intended to be used as a resource for the research community and clinical genetics laboratories.

Language

English

Research principal, contributors, and funding

Research principal

Uppsala University

Responsible department/unit

Department of Immunology, Genetics and Pathology

Protection and ethical review
Method and time period

Population

1000 indviduals representing a cross section of the Swedish population

Study design

Observational study

Geographic coverage
Topic and keywords

Research area

Medical and Health Sciences (The Swedish standard of fields of research 2011)

Keywords

genetics, population

Publications

Ameur A, Dahlberg J, Olason P, Vezzi F, Karlsson R, Martin M, Viklund J, Kähäri AK, Lundin P, Che H, Thutkawkorapin J, Eisfeldt J, Lampa S, Dahlberg M, Hagberg J, Jareborg N, Liljedahl U, Jonasson I, Johansson Å, Feuk L, Lundeberg J, Syvänen AC, Lundin S, Nilsson D, Nystedt B, Magnusson PK, Gyllensten U. SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population. Eur J Hum Genet. 2017 Nov;25(11):1253-1260, doi:10.1038/ejhg.2017.130
DOI: https://doi.org/10.1038/ejhg.2017.130

If you have published anything based on these data, please notify us with a reference to your publication(s). If you are responsible for the catalogue entry, you can update the metadata/data description in DORIS.

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Dataset
SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population

Description

DNA from blood samples were whole genome sequenced using Illumina X technology at SciLifeLab Uppsala and SciLifeLab Stockholm. The sequencing data was analyzed with the GATK best practices pipeline to obtain a joint called variant frequency dataset. For more information, see: https://www.nature.com/articles/ejhg2017130

Data format / data structure

Numeric

Text

Interactive resource

Creator/Principal investigator(s)

Adam Ameur - Uppsala University orcid

Ulf Gyllensten - Uppsala University, Department of Immunology, Genetics and Pathology

Data collection

  • Mode of collection: Registry extract and/or access to biobank sample
  • Source of the data: Biological samples

Variables

1

Number of individuals/objects

1000

Published: 2019-06-25