Category Archives: Assessment of new methods

New Assessment Catalogs Improve Saving and Tracking Variant Interpretations

         March 23, 2021

In this blog, we will be covering new assessment catalogs and how they work to improve saving and tracking variant interpretations. VarSeq is a variant analysis tool that effectively analyzes single nucleotide (SNVs) and copy number variants (CNVs) in both cancer and germline workflows.  Because VarSeq enables such diverse variant analysis, there are many research labs and institutions that evaluate… Read more »

Updates on Splice Site Analysis

         February 2, 2021

Our latest VarSeq release is one of the largest we’ve ever had, boasting an extensive list of new features and improvements. As part of this release, we have dramatically expanded our support for splice site analysis. This includes improvements to our novel splice site algorithm and support for splice site effect prediction along with several other small improvements. Novel Splice… Read more »

Golden Helix Announces New Workflow for the Interpretation and Reporting of Copy Number Variants in Concordance with the Recently Updated ACMG Guidelines

         August 18, 2020

The detection and interpretation of Copy Number Variants (CNVs) is vital for the clinical evaluation of individuals with a wide range of disorders. Golden Helix has remained at the forefront of CNVs in Next-Gen Sequencing (NGS) data since 2016 with the release of VS-CNV, our solution that allows you to both detect and analyze CNVs directly from NGS data. Earlier… Read more »

Updates to Default Transcripts and Gene Preferences in VarSeq

         June 9, 2020

An under-appreciated area of complexity when looking into the field of genetics from the outside can be found in genes and transcripts. Alternative splicing allows eukaryotic species to have a wonderfully powerful genetic code, resulting in multiple protein isoforms being encoded in a single section of DNA. But when it comes to variant interpretation, different transcripts can result in widely different predicted… Read more »

Clinical Variant Interpretation: Part III

         April 19, 2018
VCF file format

Yesterday we launched VSClincial with our first webcast in what will be a series about this powerful new way to perform variant interpretation following the ACMG guidelines. In this post, I wanted to cover the motivation for VSClinical and how we curated and presented the 33 criteria from the ACMG Guidelines into an intuitive workflow with various bioinformatic evidence and… Read more »

New & Improved ClinVar Annotations

         March 13, 2018

ClinVar is the NCBI variant database that focuses on the categorizing of variant alleles and their interpretation from a clinical standpoint. This has made it a great resource, especially for those seeking variant allele disease correlations and pathogenicity. And this all worked fairly well, but it was changed… Previously, the ClinVar variant track annotation took some time to curate due… Read more »

The Clinical Utility of the 1000 Genomes Variant Frequencies

         December 19, 2017

We have a lot to thank the 1000 Genomes project for in the genomics community. By the collaborate efforts of many researchers and organizations, the project produced not only the first catalog of rare human variation but in the process standardized many things we take for granted, such as the VCF and BAM file formats. The variant frequencies of the… Read more »

VSWarehouse Updates with the Power of VarSeq 1.4.7

         November 30, 2017
VSWarehouse Updates

With the recent release of VarSeq 1.4.7, we have expanded the concepts of our popular assessment catalog to include CNV and other region-based records and not just variants. To match these capabilities, we have made a major update to VSWarehouse that supports these new record types in the centrally hosted and versioned Catalogs and Reports. Review of the VSWarehouse Genomic… Read more »

Upcoming Webcast: Comprehensive Clinical Workflows for Copy Number Variants in VarSeq

         September 14, 2017
Tumor Sequencing

September 27, 2017 12:00 PM, EDT While Copy Number Variants are important to detect and interpret in many clinical genetic tests, labs have been without a comprehensive solution that integrates the annotating and reporting of high-quality CNV alongside their existing NGS variants. Golden Helix has developed and validated with our clinical partners a specialized NGS-based CNV caller capable of detecting… Read more »

By Popular Request: Our BEAGLE Algorithm Gains Support for Family Structure

         April 13, 2017
family structure

Earlier this year we released our own optimized and integrated BEAGLE implementation for SVS based on the BEAGLE 4.1 and optionally 4.0 algorithms. One of the commonly requested features since that released was to expand the algorithm implementation to be considerate of the parent-offspring relationship between samples to inform and improve the accuracy of the haplotype phasing.  With this information,… Read more »

Bridging Two Worlds: Lifting Over Your Variants to GRCh38

         June 7, 2016

When the new human reference genome was released over two years ago, it was hailed as a significant step forward for next generation sequencing. Compared to GRCh37, the new GRCH38 reference assembly fixed gaps, repaired incorrect sequences and offered access to sections of the genome that had been previously unaccounted for. Despite these improvements, adoption of the new assembly has… Read more »

Cross-Validation for Genomic Prediction in SVS

         April 28, 2015

The SNP and Variation Suite (SVS) software currently supports three methods for genomic prediction: Genomic Best Linear Unbiased Predictors (GBLUP), Bayes C and Bayes C-pi. We have discussed these methods extensively in previous blogs and webcast events.  Although there are extensive applications for these methods, they are primarily used for trait selection in agricultural genetics. Each method can be used… Read more »

Introducing Phenotype Gene Ranking in VarSeq

         March 3, 2015

Personal genome sequencing is rapidly changing the landscape of clinical genetics. With this development also comes a new set of challenges. For example, every sequenced exome presents the clinical geneticist with thousands of variants. The job at hand is to find out which one might be responsible for the person’s illness. In order to reduce the search space, clinicians use various methods… Read more »

Tips and Tricks for Quality Control Metrics

         September 4, 2014

SVS offers options for performing many different QC functions on genomic data. This blog takes you through some of the most commonly applied filters for various analysis types. Filters for GWAS data vary depending on the type of association tests you are performing. A typical GWAS for a common variant usually requires filters to remove problematic or poorly called variants,… Read more »

New MM-KBAC Method Explained

         July 29, 2014

Last month, June 2014, we announced a new method that Golden Helix developed–the soon to be available MM-KBAC. MM-KBAC, or Mixed Model Kernel Based Adaptive Clustering combines the KBAC method developed by Lui and Leal (2010) with a random effects matrix to adjust for relationships between samples. The KBAC algorithm takes a binary dependent variable and transformations are used to convert… Read more »

The added value of GenomeBrowse

         July 17, 2014

We released GenomeBrowse 2.0 earlier this year, allowing users to review all types of genomic data. Since then, it has received rave reviews from thousands of users around the world. Essentially, it’s the Google Earth app for genomic data. GenomeBrowse allows a user to sift through vast amounts of genomic data, and make it easy to focus on a single part… Read more »

The State of NGS Variant Calling: DON’T PANIC!!

         March 25, 2013

I’m a believer in the signal. Whole genomes and exomes have lots of signal. Man, is it cool to look at a pile-up and see a mutation as clear as day that you arrived at after filtering through hundreds of thousands or even millions of candidates. When these signals sit right in the genomic “sweet spot” of mappable regions with… Read more »