Whole-genome genotyping, also known as genome-wide genotyping, provides an overview of the entire genome, enabling genome-wide discoveries and associations. Using high-throughput next-generation sequencing (NGS) and microarray technologies, researchers can obtain a deeper understanding of the genome, providing insight into the functional consequences of genetic variation.
Microarray-based genome-wide association studies (GWAS) have been the most common approach for identifying disease associations across the whole genome. While whole-genome microarrays can interrogate over 4 million markers per sample, NGS-based whole-genome sequencing provides a comprehensive base-by-base method for interrogating the 3.2 billion bases of the human genome. Each technology offers unique advantages in price, data analysis, and throughput depending on particular study goals.
Whole-genome genotyping microarrays have been used to successfully identify regions of the human genome that contribute to disease susceptibility and phenotypes. Illumina human whole-genome arrays offer informative content for a variety of human genotyping applications, from GWAS to copy number variation analysis and more.
Find and compare human whole-genome genotyping arrays with this easy-to-use tool.
Find the Right ArrayView a full list of arrays, including kits designed for human genome-wide genotyping studies.
See All Array KitsDesign a genotyping array that focuses on your specific targets of interest.
Learn MoreIllumina is providing sequencing for a UK-wide study led by Genomics England, designed to compare the genomes of severely and mildly ill COVID-19 patients.
Read ArticleResearchers use an Illumina array to identify responder genotypes in a cholesterol drug trial.
Read InterviewA collaborative genotyping effort identifies disease-associated SNP markers prevalent in the Hispanic population.
Read InterviewThese studies use high-throughput approaches to quickly scan entire genomes of large groups to find genetic variants correlated with a trait or disease. Variants for diseases like Type 2 diabetes and Parkinson's Disease were discovered using GWAS, but many opportunities remain.
Learn More about GWASIllumina offers a comprehensive suite of genome-wide genotyping array products for non-human organisms. Find ready-to-use solutions for crops, livestock, and model organisms, or genotype any species with our custom array options.
Find and compare non-human whole-genome genotyping arrays with this easy-to-use tool.
Find Non-Human ArraysAccess a wide variety of kits, including arrays, for genotyping non-human species such as crops, livestock, and model organisms.
See All Agrigenomics KitsDesign custom arrays for any species or population, including those not supported by standard products.
Learn MoreWhile arrays are effective for assaying known variants, they are limited in detecting novel variants. NGS is an unbiased approach to variant detection that evaluates all loci and alleles regardless of prior expectations. Whole-genome and whole-exome sequencing are common approaches for finding causal variants for rare or complex disease studies.
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Novel variants discovered using NGS can be used to generate a completely custom array, or added as additional content to an existing whole-genome genotyping array for large sample screening studies. Design custom panels targeting specific traits and/or genes of interest or for species and populations not available as standard panels.
Explore Custom GenotypingHigh throughput microarrays help labs identify common genetic variations among large cohorts for population-scale genotyping studies. Learn more about high-throughput genotyping.
Screen large sample numbers quickly to find causal variants associated with complex diseases. Learn more about causal variant discovery.
Enhance the value of crops and herds with screening and discovery tools that aid in breeding decisions. Learn more about plant and animal genotyping.
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기사 보기Researchers at Okayama University in Japan use Illumina Connected Analytics with DRAGEN pipelines for analyzing whole-genome, exome, transcriptome, and metagenome data
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