Category Archives: Best practices in genetic analysis

Clinical Variant Analysis: Part V

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 »

Clinical Variant Analysis: Part IV

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: Part III

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: Part II

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 »

Top-Quality GWAS Analysis: Part I

      Eli Sward    January 16, 2019    No Comments on Top-Quality GWAS Analysis: Part I

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 »