The goal of this project is to develop a commercial analysis software platform that features the ability to detect and interpret copy number variants (CNVs) and other types of structural variations (SVs) from short-read NextGen Sequence (NGS) data to enable comprehensive, widely accessible, and economical genetic testing. This capability is key in clinical and research applications. For example, currently clinical laboratories determine the presence of CNVs and SV by utilizing a wide array of specialized tests such a micro arrays or multiplex ligation-dependent probe amplification (MLPA). This is required to completely understand the variation with a human genome possibly contributing to a disease. Similarly, researchers are trying to understand the underlying association between such variations and diseases. The difference being that clinicians are conducting analytics on a single sample or perhaps a small set of family samples, whereas researchers often study larger cohorts. In both application areas, it would be a significant simplification of clinical or research flows, if these types analysis could occur solely within the NGS paradigm. Such simplification would also provide for major cost savings. In addition to this, there is a clear trend in research and clinical application of NextGen sequencing moving towards whole genome sequencing (WGS). Conceptually, all genomic information is captured in a WGS sample. Currently, the adoption of this paradigm is hindered by the complexity of the analysis required to process and detect the full range of genomic variation from the raw sequence data, and the lack of an analysis platform tailored for small research and clinical labs that meets their needs for repeatable workflows, intuitive interfaces and long-term archiving and data mining of their patient genomic and phenotypic data. We are set out to provide a comprehensive solution to this problem. In Phase 1 SBIR, we have developed and successfully brought to market VS-CNV: a product for detecting CNVs in targeted gene panels and exomes based on CNV data based on coverage data. We succeeded in all our aims and milestones. At Golden Helix, we have a strong track record to create bioinformatics products that provide high end analytics capabilities that don?t require specialized bioinformatics training to execute. We are uniquely positioned to build and commercialize a solution that removes the barrier to adoption of WGS as a single, comprehensive test of all genomic variation and meets the needs of both clinical and research environments. We propose to build this solution by leveraging the Golden Helix VarSeq Product Suite. This product line is a globally adopted filtering and annotation engine for genomic variation, with add-ons for clinical reporting, automation of workflows, and data warehousing.
The goal of this project is to develop a commercial analysis software platform that features the ability to detect and interpret copy number variants (CNVs) and other types of structural variations (SVs) from short-read NextGen Sequence (NGS) data, to enable comprehensive, widely accessible, and economical genetic testing.
