TY - JOUR
T1 - Population-specific genetic variation in large sequencing data sets
T2 - why more data is still better
AU - van Rooij, Jeroen G J
AU - Jhamai, Mila
AU - Arp, Pascal P
AU - Nouwens, Stephan C A
AU - Verkerk, Marijn
AU - Hofman, Albert
AU - Ikram, M Arfan
AU - Verkerk, Annemieke J
AU - van Meurs, Joyce B J
AU - Rivadeneira, Fernando
AU - Uitterlinden, André G
AU - Kraaij, Robert
PY - 2017/10
Y1 - 2017/10
N2 - 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.
AB - 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.
U2 - 10.1038/ejhg.2017.110
DO - 10.1038/ejhg.2017.110
M3 - Article
C2 - 28905877
SN - 1018-4813
VL - 25
SP - 1173
EP - 1175
JO - European Journal of Human Genetics
JF - European Journal of Human Genetics
IS - 10
ER -