To realize the potential of precision medicine, genetic information must be amassed on a large scale. High-throughput genotyping studies are crucial for generating this volume of data and identifying disease associations. Currently, microarrays are the platform of choice for genotyping, as they allow investigators to survey millions of markers across disease cohorts or populations.
High-throughput genotyping data hold immense value for pharmacogenomics, consumer genomics, population studies, and clinical practice. These studies can identify not only genetic risk factors for disease, but also the genotypes associated with drug response. Eventually, this information can lead to better health management and more successful treatment strategies.
Microarrays are ideal for large-scale genotyping studies to identify disease associations or characterize populations. Illumina arrays offer several advantages.
The Infinium XT microarray workflow is ideal for production-scale genotyping, supporting biobanks and precision medicine initiatives. Each step of the Infinium workflow is optimized in the Infinium XT workflow, reducing the turnaround time from three days to two days.
MyDNA partnered with Illumina, providing customers with access to its MyDNA software platform to make the most of the data produced and to enhance their reports.Read Interview
This collaborative genotyping effort identified disease-associated genetic markers prevalent in the Hispanic population.Read Interview
High-throughput Infinium arrays help WeGene provide personal genetic testing services and support human genome research studies.Read Interview
Complex diseases result from a combination of genetic and environmental factors. Array and sequencing technologies can help reveal the underpinnings of these diseases.
From discovery applications to routine screening, microarrays are a powerful tool for analyzing genetic variation.
National population genomics programs seek to integrate large, diverse data sets, combining clinical information with genomic data at scale in a learning health system.