Huntington’s Disease (HD) Background Huntington’s Disease (HD) is an autosomal dominant neurodegenerative disease that is caused by a mutation in the huntingtin (HTT) gene resulting in 36 or more CAG trinucleotide repeats in exon 1. Individuals affected by HD experience motor disorders including involuntary movements and poor coordination, cognitive impairments showing a decline in thinking and reasoning and psychiatric disorders… Read more »
Congenital Myasthenic Syndromes (CMS) History: Congenital Myasthenic Syndromes (CMS) are a group of rare hereditary conditions that can cause seizures, severe muscle weakness, respiratory problems, and potentially disabling weaknesses shortly after birth or early childhood (1). CMS is the result of abnormalities in acetylcholine proteins residing in the motor endplate of the neuromuscular junction (1). These abnormalities can be diagnosed… Read more »
Hypertrophic Cardiomyopathy History It was December 9th, 1989, when one of Loyola Marymount’s strongest inside players, Hank Gathers, collapsed during the middle of a collegiate level basketball game against UC Santa Barbara. Measuring in at 6’7” and weighing 210 pounds, Gathers was diagnosed with exercise-induced ventricular tachycardia, or in layman’s terms, an abnormal heartbeat. Even with the concerning nature of… Read more »
Clinical Variant Analysis for Cancer – Applying AMP Guidelines to Analyze Somatic Variants Detecting cancer at an early stage can make it much more treatable. Developing tests and making them clinically actionable is crucial to beat this disease. This eBook covers the state-of-the-art gene panel tests for cancer. Of course, there is more that can be done. The field is… Read more »
We are upgrading all VSClinical +Cancer Add-On purchases to a 15-months license! One license of VSClinical +AMP Guidelines – $17,995* Additional Users: $8,995* The individualized nature of tumors requires genomic testing for providing the best outcomes for patients. Next-Gen Sequencing enables the detection of small mutations, copy number changes, and common fusions affordably and with high precision. However, the interpretation… Read more »
Clinical Variant Analysis for Cancer – Applying AMP Guidelines to Analyze Somatic Variants Somatic variants can manifest in different ways: Single Nucleotide Variants Indels Fusions and Copy Number Variations There is a difference between the interpretation of germline and somatic variants. The former is exclusively focused on establishing the level of pathogenicity vis a vis a particular disease. In contrast… Read more »
Clinical Variant Analysis for Cancer – Applying AMP Guidelines to Analyze Somatic Variants As described in my eBook “Genetic Testing for Cancer,” any bioinformatic pipeline for cancer ultimately calls variants based on the aligned reads that the sequencer generated. Variant calling is the process of reviewing a sequence alignment, typically in the form of a BAM file, to identify loci… Read more »
Clinical Variant Analysis for Cancer – Applying AMP Guidelines to Analyze Somatic Variants Analogous to the ACMG guidelines for germline mutations, the Association for Molecular Pathologists (AMP) has issued guidelines to assess and report on somatic variants. The key paper in this area was published by Li et. al (2017) with the title “Standards and Guidelines for the Interpretation and… Read more »
Clinical Variant Analysis for Cancer – Applying AMP Guidelines to Analyze Somatic Variants Precision Medicine uses genetic information from individual patients. This may include the following areas: Diagnosis Treatment Prevention Specifically, in the cancer space, data derived from Next-Gen Sequencing (NGS) is used to diagnose and prognose diseases, select a targeted therapy and potentially evaluate the suitability of a patient… Read more »
Applying AMP Guidelines to Analyze Somatic Variants Today, I am thrilled to share with you the launch of a brand new eBook titled “Clinical Variant Analysis for Cancer – Applying AMP Guidelines to Analyze Somatic Variants”. We would happy to send you a complimentary copy which can be requested on our website here. The clinical utilization of Next-Gen Sequencing data… Read more »
Overview VSClinical enables users to evaluate variants according to the ACMG guidelines in a high-throughput fashion and obtain consistent results and accurate variant interpretations. This feature is tightly integrated into our VarSeq platform as well, and when paired together, users can evaluate NGS data and obtain clinical reports all in one suite. Coupled with the ability to find novel or… Read more »
This blog will conclude our VSClinical Best Practice Workflow series and focuses on one of our new reports: VSClinical ACMG Gene Panel Template. This template is valuable because it automatically enters your variant interpretation from the ACMG Guidelines into the report and eliminates the need for manual submission. I would like to explain how to properly implement this report into… Read more »
In part one of this series, we discussed how the ACMG Classifier can be implemented in your filter chain to support a best practice workflow. To continue our discussion on best practices of VSClinical, this blog will shed light on other attributes of VSClinical that can add support to your evaluation. Specifically, we will explore how VSClinical can help users… 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 »
This webcast generated a lot of great questions about the content covered in the video above. I have summarized our Q&A session below and included some questions I didn’t have time to answer during the live event. If you have any further questions, reach out to us at info@goldenhelix.com! Q: Can I upload my existing classifications into a consortium source?… Read more »
Part 1 of this blog series was focused on new capabilities in Warehouse to store your CNV results. We explored some approaches of how to utilize assessment catalogs of cohort and known pathogenic events. What makes Warehouse so useful in this application is that the catalog is accessed from one central location and ensures every user is leveraging the same… Read more »
The recent release of VSClinical gives users the ability to evaluate variants based on the 33 criteria according to the American College of Medical Genetic and Genomics (ACMG) guidelines. This feature leverages a variety of variant sequencing evidence including population data, functional data, and computational predictions while providing rich visualizations and auto recommendations to help answer challenging criteria. This highly… Read more »
In our previous webcast, we discussed the splice site algorithms for clinical genomics within VSClinical. We took it a step further in yesterday’s webcast and looked at the functional predictions and conservation scores. We had a great turnout for this event with lots of great questions from the attendees. I’d like to recap our Q&A for anyone else who might… 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 »
Functional Predictions and Conservation Scores in VSClinical Several algorithms have been developed to predict the impact of amino acid substitutions on protein function and quantify conservation of nucleotide positions. These methods provide vital supporting evidence to clinicians when interpreting variants in accordance with the ACMG guidelines. The two most popular functional prediction algorithms are SIFT and PolyPhen2, while the most… Read more »
