Explore the importance of negative findings in genomic medicine through the lens of VarSeq’s VSClinical AMP. When analyzing a somatic sample in VarSeq, users have the option to report on several types of biomarkers with VSClinical AMP. In addition to your usual mutational biomarkers such as small variants, your copy number variants, and structural variants, we support the analysis of… Read more »
Discover the power of VSClinical’s Interpretation Match Behavior options for managing the scope of somatic variants in cancer reporting, enabling clinical teams to make informed treatment decisions. Multiple interpretations can apply to a single biomarker or tumor type. In some circumstances, a clinical team may only want to report the most relevant and significant biomarker, treatment, diagnosis, or prognosis interpretations… Read more »
Revolutionize Your Somatic Variant Analysis with Our Cutting-Edge Template for Annotation and Filtering in VarSeq Golden Helix is excited to share our new Comprehensive Cancer Template for somatic variant annotation and filtering, along with the latest version of our software VarSeq 2.3.0! Our latest VarSeq update was specifically focused on getting up to speed with multiple aspects of somatic variant… Read more »
Our recent webcast, Maximizing the Benefits of Comprehensive Genomic Testing in Cancer Care with Golden Helix CancerKB 2.0, was an opportunity to unveil Golden Helix CancerKB v2.0. Our latest VarSeq release was designed to address the changing landscape of cancer genomics, and in this webcast, we discussed the application of our very own Golden Helix CancerKB in the context of… Read more »
Variant normalization is essentially reducing the representation of a variant to its canonical representation. Variant normalization ensures that the way a variant is represented is parsimonious and left-aligned and can also refer to splitting variants into their allelic primitives. VarSeq normalizes variants by default, but we offer users the option to forego one or more aspects of variant normalization. This… Read more »
The last blog in this series covered streamlining variant analysis for large genetic cohorts, namely case-control studies, on a single-project basis. The reality when dealing with big data is that you often do not handle a high volume project all at once. Therefore, we will follow up on the topic of cohort analysis by discussing Golden Helix’s solution for streamlining… Read more »
Large genetic cohorts require substantial effort to analyze. Genetic researchers are increasingly turning to whole exome and whole genome sequencing analyses for their clinical diagnostics and research. However, with that approach comes the challenge of making sense of these massive datasets. This is especially challenging when looking for tools that can streamline variant analysis for large genetic cohorts and include… Read more »
Large-scale next-generation sequencing studies are becoming increasingly popular clinical and research tools. One enduring challenge for interpretion of these large amounts of data has been predicting the functional impact of genetic variants. Access to efficient computational tools for predicting the functional impact of variants is crucial to prioritizing the most potentially relevant variants in a dataset in a time-efficient manner…. Read more »
Genomic data visualization is an extremely powerful means to help users comprehend massive amounts of sequencing data and is valuable for communicating genomic information and findings. Genome browser tools allow users to visualize aligned sequence data in BAM format, map the data to a reference assembly, view annotation tracks, genomic region tracks, export graphics for sharing, and much more. Genome… Read more »
Oftentimes, the endpoint of a clinical variant analysis is a standardized, clinical report. As such, we ship a number of default templates with VSClinical for users to report their findings. But these templates are just a starting point! Our platform allows users to fully customize their reports to adhere to lab-specific preferences. We have shared a plethora of how-to’s on… Read more »
Advances in high-throughput sequencing have allowed us to be able to detect structural variants such as copy number variants in addition to small variants such as SNVs and indels. We provide users with an industry-leading CNV calling algorithm to detect CNVs directly from their next-generation sequencing data including whole genome, whole exome, and gene panel datasets, and also import CNVs… Read more »
Curated databases are a real time saver when compiling published evidence to support your variant evaluations and classifications. Leveraging the curated databases at your fingertips in our VSClinical variant interpretation hub is even more efficient. Not only does VSClinical provides users with automated variant classification for germline variants according to the ACMG guidelines and somatic variants according to the AMP… Read more »
When doing next-generation sequencing (NGS) analysis in VarSeq, the fundamental goal is to develop efficient ways to filter through your NGS data. If you are just getting started with Varseq, a pre-designed project template can really come in handy for variant filtering! This blog series will cover a number of template design recommendations for variant filtering on data types ranging… Read more »
Tumor profiling via next generation sequencing (NGS) often reveals secondary germline variants that may constitute important incidental findings. In May 2021, the American College of Medical Genetics and Genomics (ACMG) released an updated policy statement for reporting incidental findings in exome and genome sequencing data along with a corresponding list of genes. These recommendations state that laboratories should report pathogenic… Read more »
Thanks to all those who attended the recent webcast by Dr. Rana Smalling, “Integrating Custom Gene Panels for Variant Annotations”. If you were unable to attend or would like to recap, here is a link to watch the broadcast. We covered a lot of content regarding virtual gene panels, and there were several questions submitted during our Q&A session that… Read more »
Global population frequency catalogs like 1kG Phase 3, gnomAD, DGV, and others are excellent resources for identifying rare variants in your copy number variant (CNV) analysis. However, they are not exhaustive, and the reality is a lot of variants that are missing from global population frequency catalogs are still common variants. At the same time, CNVs that are identified by… Read more »
In our previous blog, we covered the highlights of our Advanced Report Customization in VSClinical webcast in the context of germline clinical reports. Now, we bring you the next of the series: somatic clinical reports. In the recent webcast, Advanced Report Customization, we covered a range of somatic-focused clinical reports, demonstrating how easy it is to create AMP guideline-based clinical… Read more »
In February 2020, the American College of Medical Genetics (ACMG) and the Clinical Genome Resource (ClinGen) published a joint consensus on standards for the interpretation and reporting of copy number variants (CNVs) ranging from large CNVs spanning multiple genes to small intragenic events1. The guidelines consist of over 80 different criteria which are arranged into five distinct sections. These extensive… Read more »
