DanMAC5: a browser of aggregated sequence variants from 8,671 whole genome sequenced Danish individuals

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  • Peter L. Møller
  • Tanya R. Techlo
  • G. Bragi Walters
  • Andrés Ingason
  • Anders Rosengren
  • Palle D. Rohde
  • Lisette J.A. Kogelman
  • David Westergaard
  • Troels Siggaard
  • Mona A. Chalmer
  • Ólafur Magnússon
  • Guðmundur Þórisson
  • Hreinn Stefánsson
  • Daníel F. Guðbjartsson
  • Kári Stefánsson
  • Simon Winther
  • Morten Bøttcher
  • Mette Nyegaard
Objectives Allele counts of sequence variants obtained by whole genome sequencing (WGS) often play a central role in interpreting the results of genetic and genomic research. However, such variant counts are not readily available
for individuals in the Danish population. Here, we present a dataset with allele counts for sequence variants (single nucleotide variants (SNVs) and indels) identified from WGS of 8,671 (5,418 females) individuals from the Danish population. The data resource is based on WGS data from three independent research projects aimed at assessing genetic risk factors for cardiovascular, psychiatric, and headache disorders. To enable the sharing of information on sequence variation in Danish individuals, we created summarized statistics on allele counts from anonymized data and made them available through the European Genome-phenome Archive (EGA, https:// ident ifiers. org/ ega. datas et: EGAD0 00010 09756) and in a dedicated browser, DanMAC5 (available at www. danma c5. dk). The summary level data and the DanMAC5 browser provide insight into the allelic spectrum of sequence variants segregating in the Danish population, which is important in variant interpretation.
Data description Three WGS datasets with an average coverage of 30x were processed independently using the same quality control pipeline. Subsequently, we summarized, filtered, and merged allele counts to create a high-quality
summary level dataset of sequence variants.
TidsskriftBMC Genomic Data
Udgave nummer1
Antal sider4
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
Open access funding provided by Royal Danish Library. Cost of sequencing was provided through scientific collaboration with deCODE genetics. Karina Banasik, Thomas F. Hansen, and Søren Brunak acknowledge the Novo Nordisk Foundation (NNF17OC0027594 and NNF14CC0001). Simon Winther acknowledges the Novo Nordisk Foundation (NNF21OC0066981). Mette Nyegaard acknowledges the Novo Nordisk Foundation (grant NNF21OC0071050). Thomas F. Hansen and Jes Olesen have received funding from Candy’s foundation (CEHEAD).

Publisher Copyright:
© 2023, The Author(s).

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