Examples of Clinical Variant Interpretation with VSClinical In this chapter, I’d like to go through a few examples for variants that have been classified with the help of VSClinical. This will give you a better understanding of how data sources are actually being represented in the software and how those are used to make decisions on applicable criteria. It goes… Read more »
Rules for Combining Various Classification Criteria Now that we have a solid understanding of how the various criteria are meant to be applied, it’s time to look at how the evidence collectively leads to the clinical categorization of a variant. Let’s go through the rule framework for combining the various criteria. Pathogenic In order for a variant to be classified… Read more »
Clinical Variant Analysis – Classification Criteria of Benign Variants The classification of benign variants is overall simpler and more straightforward, with the majority of benign variants being eliminated through allele frequency in various population catalogs. BA1 If a variant is common in one or more population catalog, as indicated by the allele frequency associated by the appropriate sub-population, it can… Read more »
Clinical Variant Analysis – Classification Criteria of Pathogenic Variants The ACMG Guidelines are utilized for the interpretation of variants. They are primarily applied to diagnose suspected inherited (primarily Mendelian) disorders in a clinical diagnostic laboratory setting. While evaluating variants no matter what the origin, it is important to distinguish between variants that are pathogenic (i.e., causative) for a disease and a… Read more »
Importance of Quality in Association Tests SVS is a research application platform provided by Golden Helix that enables an array of computational analyses including genome-wide association studies (GWAS). GWAS is an observational study that can provide insight into the association of genetic variants with traits and complex disorders. The foundation of GWAS utilizes large cohorts sequenced with single nucleotide polymorphisms… Read more »
What is Genomic Prediction? Genomic prediction is an algorithm widely used to improve desirable phenotypic traits in agriculture. For example, the cattle industry uses genomic prediction to improve beef quality and palatability as well as improve dairy production (1,2). By using genomic prediction, researchers can minimize multiple expenses in breeding industries as well as diminish the need for performing cumbersome… Read more »
In a recent webcast, our VP of Product and Engineering Gabe Rudy gave us insight into the current capability and benefits to lifting over to the GRCh38 assembly. Golden Helix fully supports this transition into the most recent reference assembly and have developed our tools on both the 38 and 37 fronts. The purpose of this blog is to not… Read more »
VSClinical is our most recent product that allows users to evaluate variants according to the ACMG guidelines. As with any tertiary analysis, there is a need to implement best practices into your workflow and using VSClinical for the ACMG guidelines is no exception. That said, we have put together a Best Practices Blog Series, with the purpose of discussing some… Read more »
2017 was an incredibly prosperous year for Golden Helix; we released a handful of new features, announced new partnerships and completed our end-to-end architecture for clinical testing labs. Our webcast series has become a very popular way for our community to stay up-to-date with our new capabilities and best practices in genetic analysis using our software. We had three webcast… Read more »
Clinical Assessment Tracks Golden Helix provides a large catalog of annotation sources for our research and clinical clientele. Making these public data repositories available to all our users is no easy task. As Cody Sarrazin mentioned in his blog post, annotation curation is a complex data science pipeline. This process aggregates data from many disparate sources and normalizes it into… Read more »
An Example of an Integrated Clinical Workflow for CNVs and SNVs In this blog series, I discuss the architecture of a state of the art secondary pipeline that is able to detect single nucleotide variations (SNVs) and copy number variations (CNVs) in one test leveraging next-gen sequencing. In Part I, we reviewed genetic variation in humans and looked at the key… Read more »
Examples of CNV Calling What do CNV calls actually look like? What are some of the key metrics to determine an event? Part IV of the Secondary Analysis 2.0 blog series will answer these questions by walking through some examples of how our CNV caller, VS-CNV, identifies CNVs. Golden Helix integrates multiple metrics to determine if a CNV event is… Read more »
Detection of CNVs in NGS Data Our Secondary Analysis 2.0 blog series continues with Part III: Detection of CNVs in NGS Data. We will give you an overview of some design principles of a CNV analytics framework for next-gen sequencing data. There are a number of different approaches to CNV detection. The published algorithms share common strategies to solve the… Read more »
In this blog series, I will discuss the architecture of a state of the art secondary pipeline that is able to detect single nucleotide variations (SNV) and copy number variations (CNV) in one test leveraging next-gen sequencing. In Part I, we reviewed genetic variation in humans in general and looked at the key components of a systems architecture supporting this… Read more »
Human genetic variation makes us unique. On average, humans are to 99.9% similar to each other. Understanding in detail what the nature of the difference in our genetic make-up is all about allows us to assess health risks, and eventually enables Precision Medicine as we determine treatment choices. Furthermore, it enables scientists to better understand ancient human migrations. It gives… Read more »
In the past couple of weeks, the topic of the Filter and Quality fields in the popular ExAC population catalog has come up a number of times. It turns out that unlike the 1000 Genomes project, which decided to very heavily filter their variant list to only contain variants they consider high quality, ExAC chose to include more dubious variants… Read more »
Since we released our Phenotype Gene Ranking algorithm in VarSeq, it has become a staple of the way people conduct their analysis. It allows for a combination of filtering with ranking to prioritize follow-up interpretations of analysis results. Our PhoRank algorithm will be available in our upcoming SVS release to also aid in the numerous research workflows performed on SNPs… Read more »
Genome-wide association study (GWAS) technology has been a primary method for identifying the genes responsible for diseases and other traits for the past ten years. GWAS continues to be highly relevant as a scientific method. Over 2000 human GWAS reports now appear in scientific journals. In fact, we see its adoption increasing beyond the human-centric research into the world of… Read more »
ExAC CNVs were released publicly with a recent publication, providing the full set of rare CNVs called on ~60K human exomes. While there are many public CNV databases out there, this is the first one that was derived from exome data, and thus includes both extremely rare and very small CNV events. With the recent release of Golden Helix’s CNV calling… Read more »
December’s webcast will provide the Golden Helix community with a more in-depth look at CNV analysis in VarSeq. On December 7th, Dr. Nathan Fortier will discuss the challenges and metrics surrounding CNV detection and then demonstrate VarSeq’s new capability from VCF to clinical report. Wednesday, December 7th @ 12:00 PM, EST Numerous studies have documented the role of Copy Number Variations (CNVs)… Read more »
