In continuation of our blog posts focusing on new features of VarSeq v2.2.2, here we will discuss the Latest Sample Assessment algorithm for both single nucleotide variants (SNVs) and copy number variants (CNVS). This algorithm annotates the variants of the project with the latest assessment from your variant catalog, which will show the history of interpretations made for the variants… Read more »
Curious about how coverage statistics can be used in conjunction with VarSeq? Evaluating the coverage over target regions or whole genomes is essential whether you are working with variant or CNV analysis. VarSeq has had the capability to compute sample level coverage statistics for some time now, but in the 2.2.2 release of VarSeq, there are some new features that… Read more »
In this blog post, I will be analyzing a loss-of-function splice variant in MTHFR using VarSeq. In the search for clinically relevant variants contributing to rare disorders, efficient filtering strategies are an important step in eliminating disinteresting variants. However, any applied filters must also ensure no interesting variants inadvertently get filtered out. Golden Helix provides the tools to complete this… Read more »
The potential of genetic testing to impact a patient’s life has been greatly accelerated by the sharing of variant interpretations done by clinical labs in public repositories such as ClinVar. This is not an inevitable outcome, but the persistent work and advocacy of people like Dr. Heidi Rehm and organizations like ClinGen. We recently participated in a survey and vetting… Read more »
As clinical genetic tests have been adopted as a critical enabler of precision medicine, the number of tests offered by clinical labs and the volume of tested patients has grown by orders of magnitude in the past five years. The Gene Testing Registry, managed by the NIH, documented a rise from 13,000 to 60,000 tests offered in the US market… Read more »
Copy Number Variation (CNV) is a type of structural variation in which sections of the genome are duplicated or deleted. Although CNV events are rare in the human population, constituting approximately 10% of the human genome, they are also associated with being causal mutations for disease phenotypes. Because of this, it is important for clinical and research settings to identify… Read more »
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 »
Streamlining the ACMG Guidelines and Providing Scoring Recommendations As we discussed in our recent webcast on VSClinical, the process of scoring the ACMG guidelines requires evaluating evidence for the connection between a variant and the disorder or condition being evaluated by the genetic test for an individual. These lines of evidence cover clinical presentation, gene function, bioinformatic annotations and in-silico… Read more »
Revisiting the Five Splice Site Algorithms used in Clinical Genetics Interpretation of variants in accordance with the ACMG guidelines requires that variants near canonical splice boundaries be evaluated for their potential to disrupt gene splicing [1]. The five most common tools for splice site detection are NNSplice, MaxEntScan, GeneSplicer, HumanSplicingFinder, and SpliceSiteFinder-like. Because these algorithms have been made easily accessible… 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 »
Next-Gen Sequencing promised to be the ultimate paradigm when it comes to genetic research and clinical testing since it contains the complete genetic information. When it comes to the current reality in testing labs, there are still a number of additional testing paradigms used in an analysis, specifically, copy number variations. Among these, labs still widely use Chromosomal Microarrays and… 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 »
