For almost two decades the Database of Genomic Variants (DGV) has provided researchers and clinicians open access to common copy number variations, from diverse genomic populations for the purpose of identifying common polymorphisms in these populations...
For 25 years, BioDiscovery, Inc. has been dedicated to developing state-of-the-art software products for life science research and clinical applications. In this interview, BioDiscovery Founder, President & CSO Soheil Shams portrays the success story of a company that is deeply entrenched in the history and rapid acceleration of genomics.
The American College of Medical Genetics and Genomics Secondary Findings Working Group has recently updated its recommendations.
With a continued focus on customers, BioDiscovery moves from a sales and support departmental structure to a holistic team filled with Customer Success Managers.
The long-awaited NxClinical update is here! NxClinical 6.0 is packed with over 500 features and improvements - too many to talk about here but this blog features some of the highlights.
Low Pass Genome Sequencing (LP-GS) for detection of CNVs as a replacement to constitutional microarray analysis. The team evaluated a number of different tools and found NxClinical to have superiority in CNV detection and classification.
A recent study from Arthur Beaudet’s lab at Baylor College of Medicine published in the American Journal of Human Genetics (AJHG) looks at the ability to detect fetal aneuploidies and copy number variants (CNVs) at 1Mb resolution from single circulating trophoblast (SCT) cells in maternal blood.
NxClinical has very strong visualization tools which is important for cytogeneticists - a reviewer can easily view the allele patterns and estimate % aberrant cells. But NxClinical 5.0 makes this even easier by automatically performing this calculation on a per event basis. The software also uses a user-defined threshold to mark events as mosaic or not. The software looks at event-specific aberrant cell fraction using both the Log R value as well as BAF (where available). This approach uses platform-dependent scaling so that the correct calculation can be applied to samples from multiple platforms (e.g. ThermoFisher, Illumina, CNV from NGS).
The BAM MSR algorithm uses a set of “normal” samples to create a pooled reference to be used against the samples under analysis. Here are a few recent publications showing the algorithm’s versatility in handling different types of NGS data from panels to low-pass whole genome.
The 2019 Tumor Profiling: Methods and Protocols book is out and we are particularly excited about the Whole-Genome Single Nucleotide Polymorphism Microarray for Copy Number and Loss of Heterozygosity Analysis chapter! Read more.