This year has been full of excitement for our team, and customers as well; we have a plethora of recently published articles citing Golden Helix! We would like to congratulate everyone on their success. Please enjoy these features articles, or see the full list here. SNP & Variation Suite Di Gerlando, R.; Mastrangelo, S.; Sardina, M.T.; Ragatzu, M.; Spaterna, A.;… 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 »
We would like to thank everyone who entered our 2019 Abstract Competition. This event is an excellent opportunity for our team to hear the unique ways Golden Helix software is being applied around the world. We had a number of remarkable entries this year which made our selection process a daunting one, indeed. It is my pleasure to announce this… 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 »
Clinical Variant Analysis – Applying ACMG Guidelines to Analyze Germline Diseases The clinical interpretation of genetic variants is time-consuming and requires strict attention to detail. Clinicians must thoroughly review any variants that could potentially cause disease using a complex set of guidelines. There are guidelines for the interpretation of variants relating to hereditary risk, germline diagnostics issued by the American… Read more »
I am excited to announce the release of my new eBook “Clinical Variant Analysis – Applying ACMG Guidelines to Analyze Germline Diseases“! You can download your complimentary by clicking on the button below. The clinical interpretation of variants in Next-Gen Sequencing is a quickly evolving field. While the body of knowledge is growing exponentially, experts have to derive sound, clinical decisions leveraging an… Read more »
The Beginning of Your Tertiary Analysis VarSeq is designed to be your NGS tertiary analysis solution providing users simple but in-depth means of exploring gene panel, exome, and whole genome variants. For those not accustomed to the VarSeq software, the main import file for variant analysis is the VCF. Those who are familiar with the VCF know that there can… Read more »
As our final part of the ‘Top-Quality GWAS Analysis’ blog series, we will be giving a summary of the values behind GWAS quality control and quality assessment. Performing GWAS can provide insight into the association of genetic variants with traits and complex disorders. Any novel insights into marker-phenotype associations need to be based on performing quality control steps. In this… Read more »
Population Stratification This article is going to cover how to factor for population stratification in your association test to continue our blog series on top quality GWAS analysis (additional articles for this series are located at the bottom of this blog). Quality control steps up to this point have included assessing sample and marker statistics, LD pruning on markers, and… Read more »
Sample Relatedness Pruning your data based on Linkage Disequilibrium (LD) values and filtering for sample “relatedness” are ideal quality assurance steps following the marker and sample quality filtering described in Part II of this blog series. The value of running an Identity by Decent estimation not only allows you to factor family relatedness in your samples but makes screening for… Read more »
Eliminate Low-Quality Samples and Markers In Part I of this GWAS Analysis series, Dr. Eli Sward provided us with a great overview on the value SVS provides in managing the quality of your SNP or NGS data to maintain the high power and accuracy of your GWAS. He also gave a snapshot of what a typical genotype spreadsheet may look… 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 »
We had a great time showing users the new COSMIC database for future NGS cancer analyses within VarSeq. If you didn’t get a chance to join us for this live webcast, you can watch the recording below. I have summarized our live Q&A session for anyone who is curious about what others were asking. The COSMIC track is free, what… Read more »
We have released a new version of my eBook, “Secondary Analysis 3.0”. To download a complimentary copy, I encourage you to do so here. Next-Generation Sequencing (NGS) promises 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… Read more »
Happy New Year. I trust you had a relaxing time over the holidays with family and friends as well as a great start into 2019. Golden Helix certainly had a landmark year. There were many highlights that actually shaped the direction for us in the years to come. Please let me mention a few: We launched VSClinical in May 2018:… Read more »
We are happy to announce that our latest version of SVS includes the ability to call CNVs on low read depth Whole Genome Sequencing (WGS) data. Designed for calling large cytogenetic events, this algorithm can detect chromosomal aneuploidy events and other large events spanning one or more bands of a chromosome from genomes with average coverage as low as 0.05x…. Read more »
The PhoRank tool in VarSeq is further explored in this post by looking at the sample-specific capability. VarSeq PhoRank Part: 1 Variant Phorank Gene Ranking showed how the PhoRank algorithm could be applied to all the variants in a VarSeq project, regardless of the number of (or difference in) samples. There is another PhoRank algorithm in VarSeq that allows the… Read more »
One of the main goals of clinical genomic labs is to identify problematic variants in affected individuals. One tool to assist in this search is the phenotype driven variant ontological re-ranking tool in VarSeq called PhoRank. A common situation facing clinicians is sorting through thousands of variants provided by an individual’s exome data (or possibly the individual’s nuclear family exome… Read more »
