Abstract
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.
Highlights
Massive parallelization of solid support-based oligonucleotide hybridization approaches has led to the development of the most widely used platform for genetic analyses, i.e., genotyping arrays based on single-nucleotide variants (SNVs)
The 660w-Quad array had ~65K copy-number variant (CNV) markers included in its design
While the comparison of arrays we performed here does not cover the complete scope of all applications of genomic microarray technology, this study considers the most commonly used applications in-depth
Summary
Massive parallelization of solid support-based oligonucleotide hybridization approaches has led to the development of the most widely used platform for genetic analyses, i.e., genotyping arrays based on single-nucleotide variants (SNVs). Of all the possible applications of genotyping arrays, traditionally its primary use has been GWAS, which has proven to be a successful research approach to discover genetic factors for complex diseases, toxicities, and traits [1,2,3]. Genome-wide coverage is a function of the number of genotyped SNVs and the capacity of these SNVs to tag adjacent (untyped) SNVs through patterns of linkage disequilibrium, which can be population-specific. There are many other considerations for choosing a genotyping array such as the possibility to customize the content, the demands and wishes of a consortium or investigators (i.e., an interest in specific gene categories), and the imputation quality, all of which may influence the final decision
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