Introducing VSClinical: Streamlining ACMG Variant Interpretation Guidelines
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Golden Helix is a global bioinformatics company providing software solutions for genomic analysis, including the ACMG variant interpretation guidelines, aimed at standardizing genetic testing processes. The company's offerings, which include automated classification algorithms and support for evidence-based variant evaluation, are designed to enhance accuracy and reduce subjectivity in clinical settings. Golden Helix's upcoming release, VarSeq 2.0, will introduce additional features such as splice site predictions and functional predictions to improve variant analysis.
![[Demo in VarSeq]](https://image.slidesharecdn.com/introducing-vsclinical-191004160244/85/Introducing-VSClinical-Streamlining-ACMG-Variant-Interpretation-Guidelines-11-320.jpg)
Introducing VSClinical: Streamlining ACMG Variant Interpretation Guidelines
- 1. Gabe Rudy | VP of Product & Engineering Standardizing ACMG Variant Interpretation Guidelines
- 2. Golden Helix – Who We Are Golden Helix is a global bioinformatics company founded in 1998. CNV Analysis GWAS Genomic Prediction Large-N-Population Studies RNA-Seq Large-N CNV-Analysis Variant Warehouse Centralized Annotations Hosted Reports Sharing and Integration Variant Calling Filtering and Annotation Variant Interpretation Clinical Reports CNV Analysis Pipeline: Run Workflows
- 3. Cited in over 1,200 peer-reviewed publications
- 4. Over 350 customers globally
- 5. Golden Helix – Who We Are When you choose a Golden Helix solution, you get more than just software ▪ REPUTATION ▪ TRUST ▪ EXPERIENCE ▪ INDUSTRY FOCUS ▪ THOUGHT LEADERSHIP ▪ COMMUNITY ▪ TRAINING ▪ SUPPORT ▪ RESPONSIVENES S ▪ INNOVATION and SPEED ▪ CUSTOMIZATIONS
- 6. Genetic Testing Process Sample Prep Sequencing Align & Call Annotate & Filter Variant Interpretation Report Sentieon & VS-CNV VarSeq VSReportsVSClinical Golden Helix Clinical Suite
- 7. Variant Interpretation â–Ş Evaluation of Evidence: - Clinical presentation - Gene function - Bioinformatic evidence - Population frequencies Benign Pathogenic Uncertain Significance
- 8. ACMG Guidelines - A standardized process for scoring variant for genes that cause Mendelian disorders. - Widely adopted in US, and worldwide - 33 criteria for evaluating a variants evidence - Rules for combining criteria into a single Classification - Not static, follow up papers and expanded recommendations published
- 9. VSClinical â–Ş Complete Support for ACMG Guideline Workflow: - Implements a guided workflow for following the ACMG guideline scoring and classifying - Place criteria into conceptually related groups, paired with their opposites, and formatted as answerable question. â–Ş Aggregate and Automate: - Questions have supporting evidence presented with rich and interactive visuals - Automatically computed recommendations for questions that have explicit bioinformatic evidence, with supporting reasons for each answer. â–Ş Expert and Beginner Friendly: - Start with descriptive summaries and recommendations for a variant - Deep dive into Population Catalogs, Gene Impact, Published Studies and Clinical tabs - Integrated documentation, readings on scoring criteria and citations
- 10. Analysis Workflow with VSClinical 1. Follow your existing VarSeq annotation and filtering workflow 2. Add new ACMG Auto Classifier algorithm: - Looks up if variant annotated in previous sample - Scores 18 criteria based on available evidence from 7 sources 3. Select variants to evaluate using the ACMG Guidelines 4. Score and Finalize each variant, selecting which to report 5. Finalize the sample, review and report
- 11. [Demo in VarSeq]
- 12. How Does VSClinical Work? â–Ş 7 Algorithms and 5 Annotation Sources â–Ş On the fly computation, thinner projects â–Ş Exclusive to VSClinical - Splice Site Predictions - Multiple Sequence Alignment (MSA) - MSA derived GERP++ and phyloP - MSA derived SIFT and Polyphen2 - ACMG Auto Classifier â–Ş New Annotation Sources - ClinVar Assessments - Missense Badness
- 13. Golden Helix Pathogenicity Calculator â–Ş Probabilistic Model of Pathogenicity: - Provide instantons feedback - Per classification probabilities - Combined pathogenicity probability - Necessary to classify a variant with conflicting criteria
- 14. Transcript Aware Analysis â–Ş Updated selection of clinically relevant transcript based on ClinVar Assessments â–Ş Your transcript preferences saved and used in VarSeq + VSClinical â–Ş Warning if the the variant overlaps other transcripts that have a different effect â–Ş Can switch to view/interpret on any other transcript
- 15. Functional Predictions â–Ş Functional Predictions: - 100-way multiple-sequence alignment - Run on Primates, Mammals, Vertebrates - Algorithms run on-demand for any variant - Can be run as a bulk annotation algorithm - Upcoming webcast will cover more
- 16. Splice Site Predictions â–Ş Required for ACMG Classification: - Variants near splice site, synonymous - 4 algorithmic strategies - Detect deletion of canonical splice site - Run in VSClinical and as part of our gene annotation algorithm - Upcoming webcast to cover more
- 18. Standardize your Lab with VSClinical ▪ Reduce Subjectivity / Errors - Supports ”Blinded Analysis” of same sample by two lab personnel ▪ Self-learning System - Knowledge of assessments - Historical answers for same variant and similar variants in gene help inform decision ▪ Scale up Interpretations - Self guided exploration of details - Automate google searchers for variants in papers
- 19. Thanks to NIH & Stakeholders ▪ NIH Grant Supported - Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number R43GM128485. PI is Dr. Andreas Scherer, CEO Golden Helix. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. ▪ ACMG Guidelines Author Collaborator: - Dr. Elaine Spector (Childrens Colorado, USA) ▪ Stakeholders: - Dr. Abdallah Elias (Shodair Children’s Hospital, USA) - Dr. Ahmed Alfares, King Abdul Aziz Medical City, Saudi Arabia), - Dr. Bailey Glen (Medical University of South Carolina, USA) - Dr. Jim Weber (PreventionGenetics, USA) - Dr. Qin Hae and Dr. Line Larsen (Amplexa, Denmark) - Dr. Val Hyland (Pathology Queensland, Australia).
- 20. Summary & Next Steps â–Ş Contact us to evaluate! - New Product - Includes OMIM, CADD, VSReports - Splice site predictions - Functional predictions â–Ş Part of upcoming VarSeq 2.0 release â–Ş Shipping Q2, targeting end of May â–Ş Contact us if you are interested in other workflows or customizations