TY - JOUR
T1 - A comparison of genotyping arrays
AU - Verlouw, Joost A.M.
AU - Clemens, Eva
AU - de Vries, Jard H.
AU - Zolk, Oliver
AU - Verkerk, Annemieke J.M.H.
AU - am Zehnhoff-Dinnesen, Antoinette
AU - Medina-Gomez, Carolina
AU - Lanvers-Kaminsky, Claudia
AU - Rivadeneira, Fernando
AU - Langer, Thorsten
AU - van Meurs, Joyce B.J.
AU - van den Heuvel-Eibrink, Marry M.
AU - Uitterlinden, André G.
AU - Broer, Linda
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/11
Y1 - 2021/11
N2 - Array technology to genotype single-nucleotide variants (SNVs) is widely used in genome-wide association studies (GWAS), clinical diagnostics, and linkage studies. Arrays have undergone a tremendous growth in both number and content over recent years making a comprehensive comparison all the more important. We have compared 28 genotyping arrays on their overall content, genome-wide coverage, imputation quality, presence of known GWAS loci, mtDNA variants and clinically relevant genes (i.e., American College of Medical Genetics (ACMG) actionable genes, pharmacogenetic genes, human leukocyte antigen (HLA) genes and SNV density). Our comparison shows that genome-wide coverage is highly correlated with the number of SNVs on the array but does not correlate with imputation quality, which is the main determinant of GWAS usability. Average imputation quality for all tested arrays was similar for European and African populations, indicating that this is not a good criterion for choosing a genotyping array. Rather, the additional content on the array, such as pharmacogenetics or HLA variants, should be the deciding factor. As the research question of a study will in large part determine which class of genes are of interest, there is not just one perfect array for all different research questions. This study can thus help as a guideline to determine which array best suits a study’s requirements.
AB - Array technology to genotype single-nucleotide variants (SNVs) is widely used in genome-wide association studies (GWAS), clinical diagnostics, and linkage studies. Arrays have undergone a tremendous growth in both number and content over recent years making a comprehensive comparison all the more important. We have compared 28 genotyping arrays on their overall content, genome-wide coverage, imputation quality, presence of known GWAS loci, mtDNA variants and clinically relevant genes (i.e., American College of Medical Genetics (ACMG) actionable genes, pharmacogenetic genes, human leukocyte antigen (HLA) genes and SNV density). Our comparison shows that genome-wide coverage is highly correlated with the number of SNVs on the array but does not correlate with imputation quality, which is the main determinant of GWAS usability. Average imputation quality for all tested arrays was similar for European and African populations, indicating that this is not a good criterion for choosing a genotyping array. Rather, the additional content on the array, such as pharmacogenetics or HLA variants, should be the deciding factor. As the research question of a study will in large part determine which class of genes are of interest, there is not just one perfect array for all different research questions. This study can thus help as a guideline to determine which array best suits a study’s requirements.
UR - http://www.scopus.com/inward/record.url?scp=85108060366&partnerID=8YFLogxK
U2 - 10.1038/s41431-021-00917-7
DO - 10.1038/s41431-021-00917-7
M3 - Article
C2 - 34140649
AN - SCOPUS:85108060366
SN - 1018-4813
VL - 29
SP - 1611
EP - 1624
JO - European Journal of Human Genetics
JF - European Journal of Human Genetics
IS - 11
ER -