Population-specific genetic variation in large sequencing data sets: why more data is still better

Jeroen G J van Rooij, Mila Jhamai, Pascal P Arp, Stephan C A Nouwens, Marijn Verkerk, Albert Hofman, M Arfan Ikram, Annemieke J Verkerk, Joyce B J van Meurs, Fernando Rivadeneira, André G Uitterlinden, Robert Kraaij*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Scopus)

Abstract

We have generated a next-generation whole-exome sequencing data set of 2628 participants of the population-based Rotterdam Study cohort, comprising 669 737 single-nucleotide variants and 24 019 short insertions and deletions. Because of broad and deep longitudinal phenotyping of the Rotterdam Study, this data set permits extensive interpretation of genetic variants on a range of clinically relevant outcomes, and is accessible as a control data set. We show that next-generation sequencing data sets yield a large degree of population-specific variants, which are not captured by other available large sequencing efforts, being ExAC, ESP, 1000G, UK10K, GoNL and DECODE.

Original languageEnglish
Pages (from-to)1173-1175
Number of pages3
JournalEuropean Journal of Human Genetics
Volume25
Issue number10
Early online date19 Jul 2017
DOIs
Publication statusPublished - Oct 2017

Research programs

  • EMC OR-01

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