Human Copy Number Variation Microarrays

Laboratory products

Human Copy Number Variation Microarrays

10 Sep, 2009

Published over 17 years ago. See the latest and most current information on Laboratory products.

Agilent Technologies, Inc introduced the Human CNV Association 2x105K microarray for studying associations between genomic copy number variations (CNV) and disease. The array is based on a design by the

Wellcome Trust Case Control Consortium (WTCCC), which is conducting the world’s largest study of CNVs and their relationships to a number of widespread disorders. "This array design is enriched for approximately

11,000 previously identified CNV locations along the genome," said Chris Grimley, Agilent Senior Marketing Director, Genomics. "The result is a highly validated, cost-effective CNV association tool, and we’re very pleased to be making it commercially available to the wider research community."

In August 2008, the WTCCC selected Agilent to manufacture the microarrays for the landmark CNV study; this commercial product is a result of that relationship. This array is the latest extension of Agilent’s CNV and similar comparative genomic hybridisation (CGH) microarray portfolio, Agilent’s fastest-growing product area.

"We have used the Agilent 2x105K array for characterising common structural variants in several different disease cohorts over the last several months," said Matthew Hurles, PhD, of the Wellcome Trust Sanger Institute. "Our preliminary estimate is that approximately 20 - 30% of the loci on the array are both polymorphic in our British-population study and provide sufficient data quality to assign integer copy numbers to individuals."As the name indicates, the Agilent Human CNV Association 2x105K is configured with two microarrays per 1 in. x 3 in. slide, each array containing 105,000 probes. Agilent’s 60 mer, high-fidelity optimised probes deliver unsurpassed sensitivity and precise copy number detection. The comprehensive design of this array results in more calls with fewer data points because of targeted content in high-confidence CNV regions.

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