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Golden Helix Releases Product for Whole Genome Copy Number Association Studies
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Golden Helix, Inc. has announced the release of the first ever software tool enabling whole genome copy number variation association studies, offering new opportunities for uncovering the genetic foundations of disease.
While there has been tremendous excitement in the genetic research community over the possibilities of whole genome copy number association, there simply have not been tools capable of delivering on the promise.
Most copy number programs available today have had to rely on Hidden Markov Models or other methods proven to be problematic due to high false discovery rates and low sensitivity. Though research has shown that a process called “segmentation” is the best way to reveal regions of variance, existing segmentation technologies are too computationally inefficient, making whole genome copy number analysis impractical.
In its initial research for the project, Golden Helix found the same powerful technology used for segmentation in its predictive analytics tools could be applied to this problem.
“For years we’ve used a proprietary lightning fast, optimal segmentation algorithm in several of our products,” said Dr. Christophe Lambert, CEO of Golden Helix. “When we realized that it could be used to solve the copy number problem, we knew we were on the verge of a discovery that could revolutionize the copy number analysis landscape.”
According to Company, leaping this technological hurdle in segmentation allowed scientists at Golden Helix to develop a new Copy Number Analysis Module (CNAM) for its SNP & Variation Suite. CNAM is capable of scanning through high-resolution microarray intensity data to identify copy number deletions and amplifications, which can then be used to perform whole genome association analysis.
“The tremendous attention recently devoted to copy number variation has been matched by the technical challenges in developing robust statistical approaches,” stated Dr. Todd Lencz of The Zucker Hillside Hospital campus of The Feinstein Institute for Medical Research. “Golden Helix has developed a novel tool for principled statistical analysis of microarray intensity data that represents an important step forward for the field.”
CNAM has been validated on several simulated datasets with known properties as well as whole genome Illumina and Affymetrix HapMap data with known regions of copy number variation. Papers detailing the methods behind CNAM are expected to be submitted for publication within the coming year.
