A Walk Through GWAS
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Genome-wide association studies (GWAS) have been providing valuable insight to the genetics of common and complex diseases for many years. In this webcast we will walk through one possible workflow for completing GWAS in Golden Helix SNP & Variation Suite (SVS) with special attention paid to adjusting analysis for population stratification. The webcast will include: Visualizations including Manhattan Plots, linkage disequilibrium plots, and genomic annotation sources. Quality assurance including cryptic relatedness, population stratification, as well as sample and marker statistics. Genotype association tests and statistics including Corr/Trend tests, logistic and linear regression, Mixed Linear Models, and more.
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Performing a Trio Analysis in VSClinical
We recently have exposed the powerful application of our newly released product, VSClinical and the included ACMG Guidelines. Our previous webcasts covered some basics on new algorithms and annotations behind the variant scoring and classification. Taking a step back for a moment, there are many long-time VarSeq users are familiar with our Trio template that comes packaged with the software. But, how does the Trio analysis fit into VSClinical?
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Golden Helix is committed to providing next-gen sequencing solutions that are comprehensive and efficient. A significant portion of our user base processes pediatric cases or requires the ability to run family-based analyses that can be applied to all inheritance models in order to identify rare variants in Mendelian disorders and cancer. To increase diagnostic yield and reduce time to clinical results, these models and workflows must be easy to set up and used efficiently. Optimization can involve all the steps, including data import, workflow design (variant filtering), a detailed evaluation of variant impact and clinical relevance via ACMG guidelines and AMP guidelines, as well as providing a full clinical report.
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Things you will learn:
How to manage gene lists in a single location and use them for filtering, annotation, and reporting
How to use the recently released ACMG Secondary Findings v3.0 list for reporting incidental findings
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How to define gene lists based on the specific phenotypes and disorders you are targeting with your tests
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Exploring New Features and Clinical Reports in the ACMG Guideline Workflow
For the past year, Golden Helix has been preparing a VarSeq release that includes ACMG Guidelines scoring and classification for not only single nucleotide variants but also copy number variants. In the past few months, our webcasts have introduced these guidelines and explored example CNVs that demonstrated the automated scoring of CNVs according to the new ACMG CNV Guidelines. However, there are many other new features and upgrades that have been incorporated into this VarSeq release. These upgrades have largely been driven by input from VarSeq users! That’s why I am very excited to explore these features together in the upcoming webcast “Exploring New Features and Clinical Reports in the ACMG Guideline Workflow”. In this webcast, we will walk through a workflow with SNVs and CNVs highlighting many of the new features and upgrades that will improve and streamline your ACMG workflow. Notably, we will see how these new features can also be incorporated into clinical reports.
Specifically, we will cover the following features:
New and improved ACMG Classifier algorithms
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New Project Options interface for creating patient evaluations
Now offering three new word-based clinical report templates
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Enhanced report customization capability
Splice Site Algorithms for Clinical Genomics
To fully interpret variants in the context of clinical genomics, as outlined by the ACMG interpretation guidelines, variants near canonical splice boundaries must be evaluated for their potential to disrupt gene splicing and thus be classified as a gene-damaging mutation. Five splicing methods have been canonized for this purpose in the clinical testing market: GeneSplicer, MaxEntScan, NNSplice, and Position Weight Matrix (PWM). Although these algorithms vary wildly in their performance characteristics, such as sensitivity and specificity, they are treated as black-box oracles on equal footing when being used by variant curators to classify variants.
In this presentation, we will review these algorithms and their technical strengths and weakness from the perspective of clinical variant interpretation. Additionally, we will present our approach to splice site prediction within VarSeq, demonstrating how we improve on the status quo by employing these algorithms both in the batch annotation and genomic visualization contexts. Finally, we will demonstrate how these methods can be leveraged during the interpretation of variants following the ACMG guidelines within our upcoming product, VSClinical.
VSClinical: a complete clinical workflow solution
Clinical variant analysis involves many steps and potentially requires the expertise and input from multiple individuals. For many, this process can be rather complex as it entails moving the data from user to user and possibly multiple platforms or internal bioinformatic pipelines. In general, this workflow can be broken down into three stages:
- Quality control (QC) and processing of the data. This step involves importing the data into a tertiary analysis platform and validating that the variants and samples are high quality.
- Variant evaluation using different genomic databases and annotation sources, which is then incorporated into a draft report.
- Assessment and assurance that the previous steps were performed correctly and a sign-off on the report.
Golden Helix offers VSClinical, a complete clinical workflow solution that simplifies and streamlines the clinical analysis process outlined above. VSClinical is a single testing paradigm that consolidates and automates the tertiary analysis workflow. With this software, users can perform variant and sample QC, create a variant evaluation using a plethora of public and licensed annotation sources and evaluate variants with the automated ACMG and AMP guidelines for SNVs, Indels, and CNVs. All this information can then be used to create a clinical report with our new word-based report templates.
In this webcast, we plan to demonstrate the full clinical analysis workflow within VSClinical, focusing on the topics below:
- How easy it is to perform the different stages of a tertiary analysis in VarSeq and VSClinical
- The fluidity in transferring data between different users
- Evaluating germline and somatic variants according to the ACMG and AMP guidelines
- Creating and signing off on a clinical report with the new word-based templates
Automating NGS Gene Panel Analysis Workflows with Golden Helix
In a clinical setting, investing in automatable workflows provides two pay-backs: First, less time is spent by the constraint resource of laboratory staff and medical professionals. Second, and more importantly, the possibilities for errors is reduced. In this webcast, we will cover the full analysis workflow from sequencer to clinical report and how each component can be automated with the Golden Helix clinical stack. Producing high-quality genetic test reports requires the experience of an entire lab and a robust and repeatable process. Join us to see how automation can enable your laboratory to:
Automatically start secondary analysis pipelines when new sequence runs are complete
Go from FASTQ to BAM and high-quality variants in VCFs hands-off with Sentieon
Automatically start VSPipeline to go from raw VCFs to candidate variants
Compute coverage and call CNVs alongside small variants with VS-CNV
Generate short-list previously scored variants, annotated full candidate variant lists and draft reports with VarSeq and VSClinical
Join us for a tour de force of NGS analytics powered by the Golden Helix VarSeq clinical stack and learn about how each component of your laboratory NGS analysis process may benefit from automation capabilities.
Advanced VSClinical Reports with Scripting and Custom Integrations
Golden Helix VSClinical provides a guided workflow interface for following the ACMG and AMP guidelines for the evaluation of variants and CNVs for NGS tests. The output of this work is most often a lab-specific clinical report. Since VSClinical was introduced, we have provided a powerful Word-based templating system that allows labs to customize reports to include their specific content and branding.
Although powerful, this capability has been limited to customizing the contents of a Word file. Sometimes, the next logical step for the VSClinical analysis result is not a Word file, but some other file or target system: A database, LIMS, EMR, or even just a custom structured text file.
Join us in this webinar, as we discuss the next version of VarSeq, which will introduce a powerful scripting and custom integration engine built into VSClinical Reports. We will cover:
Capabilities and outputs of the workflows of VSClinical ACMG and Cancer
Content of VSClinical reports, including sample-QC, coverage statistics, custom gene panels, and data providence
The shipped report templates that range from gene panels to exome trios and comprehensive cancer testing
The new custom script-based reports and example workflows it enables
The tools enabling a powerful developer experience when building custom outputs and integrations
The VarSeq Suite holds customization and extendibility as core values, allowing the powerful capabilities of variant analysis to be truly customized to the needs of a specific laboratory and NGS test. The new scripting and integration capabilities build on this tradition for the VSClinical workflows. We hope you can join us as we explore this topic in-depth in this webinar.
VSWarehouse Upgrade: Somatic Variant Analysis via VSClinical AMP Guidelines
Golden Helix is announcing an upgrade to their VSWarehouse and VarSeq software. The upgrade includes new features that allow somatic variant analysis and interpretation using American College of Medical Genetics and Genomics and Association for Molecular Pathology guidelines. Variants can be stored and annotated in the centralized VSWarehouse database and shared across projects and collaborators. Clinical reports generated in VarSeq can also be stored in the VSWarehouse for integration with electronic medical records. The software aims to help researchers and clinicians efficiently analyze biomarkers and classify variants according to established clinical evidence tiers.
AMP-Based Variant Classification with VSClinical
The document discusses Golden Helix's VSClinical software and its capabilities for analyzing biomarkers and variants according to AMP and ACMG guidelines. VSClinical provides a four-phased workflow to 1) filter variants, 2) assess evidence, 3) develop classifications, and 4) include interpretations in clinical reports. It leverages Golden Helix's CancerKB knowledgebase to accelerate variant interpretation and standardized reporting. The document demonstrates VSClinical's analysis and reporting of variants from a myeloid gene panel according to AMP guidelines.
Introducing VSClinical AMP Guidelines: A Comprehensive Workflow for NGS Testi...
Golden Helix is introducing new guidelines for next-generation sequencing (NGS) testing of cancer samples using their VSClinical software. The AMP guidelines provide a comprehensive workflow for variant filtering, annotation, classification evidence levels, and integrated clinical reporting of somatic and germline variants. The software utilizes various data sources to aid in cancer interpretation and allows users to save and reuse interpretations. An upcoming webinar will demonstrate how to score somatic variants for oncogenicity using VSClinical.
Efficient Application of NGS Family-Based Analysis
Golden Helix is committed to providing next-gen sequencing solutions that are comprehensive and efficient. A significant portion of our user base processes pediatric cases or requires the ability to run family-based analyses that can be applied to all inheritance models in order to identify rare variants in Mendelian disorders and cancer. To increase diagnostic yield and reduce time to clinical results, these models and workflows must be easy to set up and used efficiently. Optimization can involve all the steps, including data import, workflow design (variant filtering), a detailed evaluation of variant impact and clinical relevance via ACMG guidelines and AMP guidelines, as well as providing a full clinical report.
VarSeq is the best tool to accomplish this task. VarSeq, our tertiary analytics platform, is designed to process all sizes of genomic data. It can filter through all variants in order to identify clinically relevant variants. The results are evaluated using automated and standardized guidelines. This webcast will demonstrate workflows tailored to different pedigree scenarios. It will also demonstrate VarSeq features designed to speed up analysis time while maintaining consistency with outcomes.
In this webcast, we will cover the following topics:
Explore various family-based project designs (includes trio and duo & extended families)
Discuss various inheritance models (compound het, de novo, dominant inherited, etc)
Briefly examine the ACMG guidelines relevant to inheritance and review an example trio clinical report
Demonstrate how VSPipeline can automate the creation of projects
Building Secure Analysis and Storage Systems with Golden Helix
Genetic testing labs deal with personal data in categories with the highest level of security requirements: personal identity and medical records. Given the liability and risk associated with a breach of this secure information, it is not surprising that many labs and institutes that aggregate genomic data prefer if not require on-premise analysis and storage solutions.
Golden Helix is in a unique position to provide completely on-premise analysis solutions with a history of building analysis software from the ground-up on first principles and a focus on providing integrated, turn-key solutions. This allows for a licensing model based on training and supporting users, not tracking per-sample usage of cloud resources. As the regulatory environment around the world strengthens the privacy rights of individuals and the outcry around data breaches raises the stakes for building a secure system, we have developed a number of best practices for building secure, offline genomic analysis pipelines. Watch as we cover:
- Building a FASTQ to clinical reports pipeline behind a firewall
- On-premise analysis, warehouse and data servers independent of the internet
- Single sign-on based on local credential systems and without internet access
- Storage and network considerations for the analysis of patient-linked data
- Choose when to update and validate new pipelines, data sources and software versions
We hope you enjoy as we review the capabilities and best practices in building the most secure environment for hosting the analytics behind your precision medicine tests.
Efficiently Following the AMP Guidelines with VSClinical and Golden Helix Can...
Interpreting somatic variants for the clinical genetic testing of tumors requires hands-on time of the most skilled clinical lab personnel. Various clinical and genomic sources must be queried, papers and guidelines referenced, and an evaluation of the clinical actionability of the mutation determined by the following the AMP guidelines. Yet, there is tremendous potential for reuse of this time consuming and valuable work!
Earlier this summer we launched our VSClinical AMP Guidelines workflow which integrates a lab-specific knowledgebase that saves every biomarkers interpretation in up to seven different snippets that ar reusable across various genomic and clinical contexts. Furthermore, our cancer workflow is bundled with the Golden Helix CancerKB, our expert-curated interpretations of the most common biomarkers for the most common cancer types, reducing the time to your first precision medicine report.
Follow along as we cover:
The interpretation of clinically actionable biomarkers for targeted molecular therapy and diagnostic/prognostic clinical reports for cancer
The different levels and scopes of re-use of the interpretation for each biomarker
Saving, re-using and updating these interpretations over time by multiple users within a clinical lab with an integrated lab-specific knowledgebase
The built in Golden Helix CancerKB that provides default interpretations for most cancer genes, biomarkers and many clinically actionable Tier I/II drug sensitivity and resistance interpretations.
In the world of genomics shaping precision medicine in oncology, the limiting factor is the time-to-sign-off on fully interpreted molecular profile reports.
Exome Analysis with VS-CNV and VSClinical: Updated Strategies and Expanded Ca...
This document summarizes a presentation given by Gabe Rudy, VP of Product & Engineering at Golden Helix, on updated strategies and expanded capabilities for exome analysis with VS-CNV and VSClinical. The presentation demonstrates new features for enhanced variant analysis, including analyzing splice site, non-coding RNA, and mitochondrial variants. It also reviews improvements to Golden Helix's exome CNV calling in VarSeq, including a new low-quality target filter strategy that reduces the number of CNVs called while maintaining sensitivity and precision. Additional capabilities discussed include generating synchronized clinical reports and incorporating virtual gene panels.
Updates to VSClinical ACMG Guidelines & a Tour of Cancer Annotation Sources
Earlier this year we launched our latest product VSClinical featuring workflow support for the ACMG guidelines with advanced automation capabilities and per-criteria recommendations. It has been amazing to watch the adoption of this product in labs doing both germline and in some cases cancer variant interpretation. Our latest VarSeq 2.1 release demonstrates our approach to iterative product improvements based on our committed relationship with our customers and includes numerous enhancements to VSClinical.
In this webcast, we cover the new and updated capabilities that can add value to your genetic testing workflows as well as review the VarSeq workflow support somatic variant interpretation in tumors by leveraging our cancer-specific annotations sources. In this webcast, we:
-Demonstrate the new “Consortium Classification” support in VSClinical to have an additional ClinVar-like annotation source added to the automated and interactive ACMG scoring process.
-See how previous interpretations are integrated into your VSClinical analysis, whether they are for the current variant or are just in the genomic neighborhood.
-Cover the additional “Lookup in PubMed” variant search feature for finding supporting studies that may provide functional or clinical evidence for a variant.
-See in action the new ACMG Auto Scoring based templates for trio analysis and gene panel tests.
-Review somatic variant filtering and prioritizing in VarSeq and the updates to relevant public annotation sources including CiVIC, ICGC and a new and available to license COSMIC v86!
Reduce Turn-Around with Enhanced Cancer Annotations and CancerKB Updates
Annotation sources are constantly evolving, sometimes quite literally overnight. This is especially true in the case of cancer databases. These ever-evolving annotation sources, coupled with increasing research publications, make it difficult to do variant analysis with up-to-date scientific knowledge. With the resources available to an individual clinician or single lab, this may even prove impossible. Fortunately, VSClinical provides access to the most current clinical annotation sources - automating scoring and interpreting variants according to the most recent ACMP and AMPO guidelines. This includes many fast-changing sources such as ClinVar and COSMIC, as well as expert-curated reviews of literature and the latest drug-labeling from regulatory bodies.
In this webcast, we demonstrate the automation of a cancer workflow with enhanced cancer annotations for somatic and germline cancer variants:
- Golden Helix’s own CancerKB database has been updated to include new interpretations for genes and biomarkers with AMP Tier Level I evidence for drug sensitivity, resistance, diagnostic, and prognostic information.
- We feature a new Golden Helix curated annotation source that automates the scoring of TP53 variants with the special rule specifications by ClinGen’s TP53 Expert Panel.
- The ClinGen Expert Curated Interpretation of Variants has always been available as an annotation source for VarSeq projects, but now the expert comments and interpretations can automatically be pulled into VSClinical and used for clinical reports.
This webcast walks through a hematological-focused cancer workflow that shows off the enhanced cancer annotations and CancerKB updates!
Large Scale PCA Analysis in SVS
Golden Helix’s SNP & Variation Suite (SVS) has been used by researchers around the world to do association testing and trait analysis on large cohorts of samples in both humans and other species. As samples size increase to do population-scale genomics, the analysis methods need to adapt to remain computable on your analysis workstation.
One of the most popular methods for determining population structure in SVS is Principal Component Analysis. In this webcast, we review the fundamentals of this methodology, as well as how we have advanced the state of the art by implementing a new “Large Data PCA” capability in SVS, handling over 10 times as many samples as previously possible at a fraction of the time. Join us as we cover:
A review of SVS association testing and trait analysis capabilities
Usage of Principle Component Analysis to discern population structure
Scaling PCA beyond the limitations of computer hardware Other SVS improvements based on ongoing feedback from the user community
SVS continues to move forward as a flexible and powerful tool to perform genotype and Large-N variant analysis. We hope you enjoy this webcast highlighting the exciting new features and select enhancements we have made.
An Exploration of Clinical Workflows in VarSeq
In this webcast, we feature several example workflows and helpful features in the VarSeq that can be used in the clinic. We discuss options for conducting a comprehensive gene panel analysis for cancer or hereditary diseases. Then we introduce an example of a single exome workflow that goes from an unfiltered VCF created by a secondary analysis pipeline to a report containing information about interesting variants. Finally, we walk through an example of a trio analysis showcasing a variety of different filter options as well as inheritance patterns. All these workflows will result in a customizable clinical report.
PhoRank 2.0: Improved Phenotype-Based Gene Ranking in VarSeq
When performing variant analysis on whole exome or large gene panels, clinicians must sort through thousands of variants to determine which variants are most likely to be associated with the patient’s phenotypes. To assist with this process, we have implemented the PhoRank algorithm, which incorporates phenotypic associations to highlight the most relevant genes with potentially damaging variants. PhoRank 1.0 supports researchers leveraging all possible gene-disease associations by traversing multiple gene and pathway ontologies. Recent papers have demonstrated new techniques that have improved ranking performance in a clinical context. We have incorporated these new strategies into PhoRank 2.0: providing better ranking and improved computational performance for most clinically diagnostic and testing scenarios. Join us in this webinar as we cover:
Utility of gene ranking in genetic testing
Scenarios that warrant the use of PhoRank 2.0
New ranking strategies provided by recent papers
Benchmarks of PhoRank 2.0 on published datasets
Golden Helix provides a comprehensive solution for NGS testing labs to perform best practice guidelines such as ACMG and AMP. Our gene ranking methods provide a vital role in scaling tests to large gene panels and exomes. Please join us as we review the testing workflow and how this significant update to our gene ranking algorithm fits into the testing workflow.
Introducing VSClinical: Streamlining ACMG Variant Interpretation Guidelines
We have seen the widespread adoption of VarSeq in the clinic. It is chosen for its versatility and flexibility as well as the extensive catalog of annotations provided by Golden Helix. In a genetic testing scenario, VarSeq provides the annotated and filtered list of high-quality variants to that are ready for the user to classify and interpret.
In this webcast, we introduce a new product VSClinical that enables the interpretation of variants following the ACMG Guidelines. By incorporating new algorithms and annotation sources, detailed variant scoring and classification can occur right within VarSeq and without the need for additional external tools or resources.
Join us to see these upcoming capabilities:
Streamline the ACMG scoring guidelines with supportive recommendation and incorporated historical precedence
See the new algorithms behind the automated recommendation algorithm, and how they provide various levels of evidence
Drill down to an unprecedented level of supporting evidence for mutation hot spots, splice site predictions, and related clinical assertions
Build your own lab practices around new capabilities of blinded interpretations, collaborative interpretation review and detailed audit logs for CLIA compliance
Finalize your interpretation for a sample and compose the clinical report with the classified variants and their interpretation
In combination, this can be a game-changer for any clinical lab looking to improve their efficiency and reproducibility of the most complex step in the genetic testing workflow.
Creating & Managing Reusable Gene Lists with VSClinical
Golden Helix supports performing repeatable clinical workflows designed to meet the needs of your lab's clinical genetic tests. A critical component of any genetic test is the reporting of clinically significant genes and the ability to limit interpretations to a predefined set of test-specific genes. This webinar will cover the upcoming “Managed Gene List” feature of VarSeq and VSClinical which enables the defining and re-use of gene lists outside of individual product templates.
The community has stepped up to provide disease-specific gene lists that are validated and well-researched for specific genetic disorders. In this webinar, we will discuss how these gene lists can be incorporated into your VSClinical workflows and we will demonstrate how these gene lists can be modified to meet the specific needs of your lab.
Things you will learn:
How to manage gene lists in a single location and use them for filtering, annotation, and reporting
How to use the recently released ACMG Secondary Findings v3.0 list for reporting incidental findings
How to leverage the well-researched PanelApp knowledgebase to construct your gene lists based on different levels of evidence for a specific disease
How to define gene lists based on the specific phenotypes and disorders you are targeting with your tests
Golden Helix's End-to-End Solution for Clinical Labs
In this webcast, we provide an overview of our complete end-to-end clinical stack. Initially, we walk through our powerful secondary analysis pipeline which allows you to call SNVs and CNVs. We then demonstrate how various types of CNVs are called and discuss metrics that express the confidence associated with each call.
From there, we show you our powerful tertiary analysis capabilities for gene panels, exome, and whole genome data. We show how our users can move seamlessly from the variant interpretation stage to a clinical report. Lastly, we demonstrate how our genetic data warehouse, VSWarehouse, can be used in the clinic. We also demonstrate various use cases and show how a comprehensive assessment catalog can be utilized to ensure consistent analysis across multiple labs.
We hope you enjoy our first presentation on Golden Helix's entire end-to-end solution for clinical labs!
What's hot (20)
Exploring New Features and Clinical Reports in the ACMG Guideline Workflow
Exploring New Features and Clinical Reports in the ACMG Guideline Workflow
Automating NGS Gene Panel Analysis Workflows with Golden Helix
Automating NGS Gene Panel Analysis Workflows with Golden Helix
Advanced VSClinical Reports with Scripting and Custom Integrations
Advanced VSClinical Reports with Scripting and Custom Integrations
VSWarehouse Upgrade: Somatic Variant Analysis via VSClinical AMP Guidelines
VSWarehouse Upgrade: Somatic Variant Analysis via VSClinical AMP Guidelines
Introducing VSClinical AMP Guidelines: A Comprehensive Workflow for NGS Testi...
Introducing VSClinical AMP Guidelines: A Comprehensive Workflow for NGS Testi...
Efficient Application of NGS Family-Based Analysis
Efficient Application of NGS Family-Based Analysis
Building Secure Analysis and Storage Systems with Golden Helix
Building Secure Analysis and Storage Systems with Golden Helix
Efficiently Following the AMP Guidelines with VSClinical and Golden Helix Can...
Efficiently Following the AMP Guidelines with VSClinical and Golden Helix Can...
Exome Analysis with VS-CNV and VSClinical: Updated Strategies and Expanded Ca...
Exome Analysis with VS-CNV and VSClinical: Updated Strategies and Expanded Ca...
Updates to VSClinical ACMG Guidelines & a Tour of Cancer Annotation Sources
Updates to VSClinical ACMG Guidelines & a Tour of Cancer Annotation Sources
Reduce Turn-Around with Enhanced Cancer Annotations and CancerKB Updates
Reduce Turn-Around with Enhanced Cancer Annotations and CancerKB Updates
PhoRank 2.0: Improved Phenotype-Based Gene Ranking in VarSeq
PhoRank 2.0: Improved Phenotype-Based Gene Ranking in VarSeq
Introducing VSClinical: Streamlining ACMG Variant Interpretation Guidelines
Introducing VSClinical: Streamlining ACMG Variant Interpretation Guidelines
Creating & Managing Reusable Gene Lists with VSClinical
Creating & Managing Reusable Gene Lists with VSClinical
Golden Helix's End-to-End Solution for Clinical Labs
Golden Helix's End-to-End Solution for Clinical Labs
Similar to A Walk Through GWAS
Prediction and Meta-Analysis
We are excited to announce and demonstrate some new and highly requested features in this webcast, including predicting phenotypes by applying existing GBLUP or Bayesian models and meta-analysis for GWAS studies.
Recently in SVS we added additional genomic prediction tools such as Bayesian Genomic Prediction and K-Fold Cross Validation. We have continued to build out the prediction suite of tools by adding the ability to apply the results of a model to a new genomic dataset to predict the phenotype. This is designed to work hand-in-hand with the output of K-Fold cross-validation using either GBLUP or Bayes C/C-pi.
Next we will provide a sneak-peak at the upcoming meta-analysis feature. This was one of the most requested features in our latest customer survey. Including this feature in SVS will combine the power of the numerous file imports and data visualization with the standard meta-analysis methods in use today.
Join us as we explore how these new features can stream-line your analysis and provide additional insight into your results.
Prediction and Meta-Analysis
We are excited to announce and demonstrate some new and highly requested features in this webcast, including predicting phenotypes by applying existing GBLUP or Bayesian models and meta-analysis for GWAS studies.
Whole Genome Trait Association in SVS
Golden Helix’s SNP & Variation Suite (SVS) has been used by researchers around the world to do trait analysis and association testing on large cohorts of samples in both humans and other species. As Next-Generation Sequencing of whole genomes becomes more affordable, large cohorts of Whole Genome Sequencing (WGS) samples are available to search for additional trait association signals that were not found in array-based testing. In fact, recent papers have shown that WGS analysis using advanced GREML (Genomic Relatedness Restricted Maximum Likelihood) techniques is able to outperform micro-array based GWAS methods in the analysis of complex traits and proportion of the trait heritability explained.
Our latest update release of SVS has expanded the exiting maximum likelihood and GRM methods to support these new techniques. We have also enhanced various other association testing and prediction methodologies. This webcast showcases:
- Newly supported analysis workflow for whole genome variants using LD binning and enhanced GBLUP analysis
- Enhanced gender correction using REML
- Additional capabilities for genomic prediction and phenotype prediction
We are continually improving our products based on our customer’s feedback. We hope you enjoy this recording highlighting the exciting new features and select enhancements we have made.
Genomic Prediction Methods in SVS
Predicting phenotypic traits from genotypes is a key focus in agrigenomics, as researchers and commercial farming operations work to increase crop yields and meat production to satisfy the needs of a growing global population. Genomic prediction allows these scientists to identify the plants or animals with the best breeding potential for desirable traits without having to go through lengthy and expensive field trials.
The Golden Helix SNP and Variation Suite (SVS) offers three methods for genomic prediction: Bayes C, Bayes C-pi and Genomic Best Linear Unbiased Predictors (GBLUP). This webcast will discuss the principles of genomic prediction. It describes how these methods are applied within SVS predicting phenotypes for both plant and animal species. In addition, we show how k-fold cross-validation can be utilized optimizing predictive models.
NGS-Based Clinical Analysis
Next-generation sequencing has enabled clinicians and researchers alike to identify novel genetic variants associated with rare Mendelian Diseases across the human genome. To help enable researchers and clinicians understand the role of CNVs in human health and disease, Golden Helix has integrated a specialized NGS-based CNV caller capable of detecting deletion and duplication events as small as single-exons and as large as whole chromosome aneuploidy events. In this webcast, we will present our workflows that integrates the NGS-based CNV caller into SVS.
Big Data at Golden Helix: Scaling to Meet the Demand of Clinical and Research...
This document summarizes Golden Helix's capabilities for handling big data in genomics. It discusses how Golden Helix's software tools like VarSeq and the Variant Storage Warehouse can scale to handle large volumes of genomic and clinical data from whole genome sequencing, exome sequencing, and large population studies. It provides examples of how these tools have been used for clinical and research applications like variant filtering, annotation, and analysis of rare variants. The presentation concludes with a demonstration of the software.
Tools for Using NIST Reference Materials
This document discusses the Genome in a Bottle Consortium's efforts to develop reference materials and standards to validate next generation sequencing assays. It provides an overview of the consortium's goals to generate reference genomes with highly confident variant calls and accompanying data to allow labs to compare results and assess false positives and false negatives. The document describes some examples of how labs are using the consortium's data on the NA12878 genome to benchmark sequencing platforms and bioinformatics workflows.
New Enhancements: GWAS Workflows with SVS
This document describes new enhancements to GWAS workflows in Golden Helix's SNP & Variation Suite software. Key updates include improved tools for genotype imputation, quality control of samples and markers, association testing with multiple correction techniques, and review of test results including visualization, LD regression, and meta-analysis. The enhancements aim to provide a more robust and comprehensive solution for conducting genome-wide association studies.
Enhance Genomic Research with Polygenic Risk Score Calculations in SVS
Golden Helix’s SNP & Variation Suite (SVS) has been used by researchers around the world to do trait analysis and association testing on large cohorts of samples in both humans and other species. The latest SVS release introduces a significant leap in capabilities, with a focus on advanced Polygenic Risk Score (PRS) calculations. PRS has become a fundamental tool in genomic research, enabling the identification of correlations between genotypic variants and phenotypes across large populations.
This enhancement is particularly relevant for researchers working on large cohorts and meta-analysis. Please join us as we explore:
-SVS Workflow Review: A review of the extensive capabilities of SVS to meaningful insights from large cohorts and association test result datasets
-Computing Polygenic Risk Scores: An overview of the PRS capabilities in SVS, including Clumping and Thresholding and creation of multiple PRS models
-Evaluating and Applying PRS: Evaluating PRS models in-sample and out-of-sample and applying PRS models to perform trait prediction
-Future Implications: Brief exploration of how these advancements in SVS could influence future genomic research.
This webcast will explore how SVS facilitates the creation of multiple PRS models from large-scale genomic data, such as those obtained from extensive cohort studies or comprehensive meta-analyses. Join us to discover how these latest updates in SVS are supporting large-scale genomic research.
171017 giab for giab grc workshop
Presentation by Justin Zook at GRC/GIAB ASHG 2017 workshop "Getting the most from the reference assembly and reference materials" on benchmarks for indels and structural variants.
171017 giab for giab grc workshop
Genome in a Bottle is working to characterize difficult variants in human genomes to enable benchmarking of sequencing technologies and bioinformatics methods. They have extensively characterized five human genomes and are now focusing on large insertions, deletions, and structural variants over 20 base pairs. This work presents many challenges due to limitations in detection and representation of large variants. Genome in a Bottle is integrating calls from multiple technologies and approaches to refine sequence-resolved variants and provide benchmark variant call files.
Rare Variant Analysis Workflows: Analyzing NGS Data in Large Cohorts
Analysis of rare variants for population-level data is becoming a more common component of genomic research. Whether using exome chips, whole-exome sequencing, or even whole-genome sequencing, rare variation analysis requires a unique analytic perspective.
In this presentation, we will review some of the tools available in SVS for large sequenced cohorts including summarization, visualization, and statistical analysis of rare variants using KBAC, CMC, and other methods.
Special attention will be given to useful functions available for download from the SVS scripts repository.
VariantSpark: applying Spark-based machine learning methods to genomic inform...
Genomic information is increasingly used in medical practice giving rise to the need for efficient analysis methodology able to cope with thousands of individuals and millions of variants. Here we introduce VariantSpark, which utilizes Hadoop/Spark along with its machine learning library, MLlib, providing the means of parallelisation for population-scale bioinformatics tasks. VariantSpark is the interface to the standard variant format (VCF), offers seamless genome-wide sampling of variants and provides a pipeline for visualising results.
To demonstrate the capabilities of VariantSpark, we clustered more than 3,000 individuals with 80 Million variants each to determine the population structure in the dataset. VariantSpark is 80% faster than the Spark-based genome clustering approach, ADAM, the comparable implementation using Hadoop/Mahout, as well as Admixture, a commonly used tool for determining individual ancestries. It is over 90% faster than traditional implementations using R and Python. These benefits of speed, resource consumption and scalability enables VariantSpark to open up the usage of advanced, efficient machine learning algorithms to genomic data.
The package is written in Scala and available at https://github.com/BauerLab/VariantSpark.
Multivariate Analysis and Visualization of Proteomic Data
From the UC Davis Proteomics 2014 Summer Workshop
www.proteomics.ucdavis.edu
by Dmitry Grapov, Ph D
20170426 - Deep Learning Applications in Genomics - Vancouver - Simon Fraser ...
This document discusses Google's capabilities for handling large genomic and biomedical data sets. It describes how Google uses technologies like Google Cloud, BigQuery, Dataflow and TensorFlow to process, store and analyze massive volumes of genomic and medical data. Google's systems can handle hundreds of terabytes to petabytes of data and enable fast querying and machine learning on these data sets. The document also provides examples of how Google is applying these capabilities to challenges in genomics, healthcare and precision medicine.
Arraygen_Brochure
ArrayGen is a global bioinformatics company that provides one-stop solutions for NGS data analysis, microarray data analysis, and bioinformatics application development. It offers services such as custom array design, NGS data validation, gene expression analysis, and bioinformatics services. ArrayGen also develops products like Agilent catalog microarrays and the ANG genome browser to enable genomics research.
Arraygen brochure
ArrayGen is a global genomics service provider company which is a one stop solution for Genomics Bioinformatics algorithm development and data analysis. ArrayGen's focus on Genomics, NGS data analysis, custom array design, microarray data analysis thus cover a vast majority of Bioinformatics applications in the life sciences sector.
Genome voyager-beta-brochure
The Genome Voyager platform enables institutions to analyze and interpret sequencing data from targeted gene panels, exomes and whole genomes to streamline the interpretation and reporting process. It provides easy-to-use filtering and visualization capabilities, facilitates collaboration between users, and utilizes a knowledge base to consolidate information and rapidly expand understanding of variants and conditions. Interested institutions can join the beta program to evaluate this solution and provide feedback.
GIAB Integrating multiple technologies to form benchmark SVs 180517
Genome in a Bottle aims to provide well-characterized human genomes as benchmarks to validate genome sequencing and variant calling. The summary characterizes five genomes that have been analyzed to provide benchmark calls for simple and some complex variants, though many challenges remain, particularly for structural variants and difficult genomic regions. Integration of multiple data types and analyses from diverse technologies is key to improving benchmark calls over time in an open and transparent manner.
Production Bioinformatics, emphasis on Production
Production bioinformatics at Sema4 can be thought of as data ops - a peer to the lab ops organization. We operate 24/7 to deliver correct and timely results on NGS and other data for thousands of samples per week. This deck introduces the Prod BI organization and systems architecture with a focus on what it takes to run bioinformatics in production rather than for R&D or pure research.
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Big Data at Golden Helix: Scaling to Meet the Demand of Clinical and Research...
Big Data at Golden Helix: Scaling to Meet the Demand of Clinical and Research...
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Enhance Genomic Research with Polygenic Risk Score Calculations in SVS
Rare Variant Analysis Workflows: Analyzing NGS Data in Large Cohorts
Rare Variant Analysis Workflows: Analyzing NGS Data in Large Cohorts
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Introducing VarSeq Dx as a Medical Device in the European Union
A transition period regarding in vitro medical device (IVD) regulation in the European Union (EU) is upon us. The former IVDD regulations are phasing out and IVDR 2017/746 has already taken its place as the acting regulation for IVD manufacturers but also lab developed tests (LDTs) and health institutions. In our upcoming webcast we will talk about the roles and significance of IVDR and ISO 13485 certification for clinical labs and for Golden Helix as a medical device manufacturer.
Join us as we will introduce VarSeq 2.6.1 complete with Dx Mode, which offers the use of VarSeq as CE marked medical device. Even more we will also present strategies to facilitate the transition of Golden Helix customers to operate in accordance with IVDR.
VarSeq 2.6.0: Advancing Pharmacogenomics and Genomic Analysis
In the rapidly evolving field of genomic analysis, staying current with the latest research, data sources, and test advancements is crucial. In this webinar, we review how VarSeq addresses the needs to stay on top of the latest with the release of VarSeq 2.6.0.
This release features an exome-optimized workflow for LOH and CNV calling as well as the introduction of VSPGx to produce pharmacogenomic reports for gene panels as well as exomes and genomes. With the recent release of gnomAD v4, we have had many requests for the integration of this large update to the most population frequency source. With VarSeq 2.6.0, the latest version of gnomAD has been integrated into VSClinical and the updated tracks spans beyond variants to cover CNVs and gene scores to update all your workflows to the latest data.
In this webcast, we will cover.
Improved VS-CNV performance and updated exome analysis workflows.
Pharmacogenomics in action: Utilizing VSPGx for exome and genome assessments.
gnomAD v4 in practice: Updated automated and manual variant interpretation workflows.
Join us for an insightful session on the latest VarSeq 2.6.0 features, bringing you the most up-to-date data and workflows for your genomic analysis.
Introducing VSPGx: Pharmacogenomics Testing in VarSeq
Inter-individual variability in drug response poses a significant challenge for clinicians, with much of this variability resulting from inherited genetic differences. While the field of pharmacogenomics (PGx) can provide powerful insights into how genomic factors affect drug response, the implementation of PGx testing in the clinic is hampered by the difficulty of translating genetic test results into actionable recommendations. In this webcast, we will discuss VarSeq’s new PGx testing capabilities, including the ability to identify actionable pharmacogenomic diplotypes and generate clinical reports.
In this webcast you will learn:
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Analyzing Performance of the Twist Exome with CNV Backbone at Various Probe D...
Clinical Whole Exome Sequencing (WES) offers a high diagnostic yield test by detecting pathogenic variants in all coding genes of the human genome. WES is poised to consolidate multiple genetic tests by accurately identifying Copy Number Variation (CNV) events, typically necessitating microarray analyses. However, standard commercial exome kits are limited to targeting exon coding regions, leaving significant gaps in coverage between genes which could hinder comprehensive CNV detection.
Addressing the need for comprehensive coverage, Twist Bioscience has developed an enhanced Twist Exome 2.0 Plus Comprehensive Exome Spike-in capture panel with added "backbone" probes. These probes target common SNPs polymorphic in multiple populations and are evenly distributed in the intergenic and intronic regions, with three varying densities at 25kb, 50kb, and 100kb intervals. In this webcast, we discuss the combined efficacy of the backbone-probe enhanced exome capture kit and VS-CNV in identifying known CNVs using the Coriell CNVPANEL01 reference set.
This webcast reviews:
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-The impact of best-practice quality metrics and filters on sensitivity.
-How VarSeq’s CNV annotation capabilities can be leveraged to identify likely pathogenic CNVs.
-The interpretation of clinically relevant CNVs using VSClinical.
From Panels to Genomes with VarSeq: The Complete Tertiary Platform for Short ...
From gene panels to whole genome, from short to long-read sequencing, the VarSeq suite is the solution for NGS analysis and reporting in a modern clinical lab. VarSeq handles the spectrum of variant types (SNV, Indel, CNV, Fusions) and provides automated classification and reporting capabilities following the ACMG and AMP guidelines. With our new PacBio partnership, we are more adaptable than ever with creating a spectrum of custom workflows to suit our unique user needs.
This webcast will review:
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Come join us for this showcase in modern VarSeq analysis capabilities.
VarSeq 2.5.0: VSClinical AMP Workflow from the User Perspective
With our recent launch of VarSeq 2.5.0, our ability to expedite somatic analysis for NGS labs is more accessible than ever before. Our recent webcasts have shown our range of updates, including our new oncogenicity classifier and carrier status workflows:
Identifying Oncogenic Variants in VarSeq
VarSeq 2.5.0: Empowering Family Planning through Carrier Screening Analysis
In this user perspective webcast, we will highlight how the combination of our new oncogenicity classifier and the updates to our CancerKB database streamline the interpretation of oncogenic variants. In addition, as NGS labs progress from gene panels to WES analysis for ideal genomic signature generation, we will demonstrate how a VarSeq somatic workflow can scale with these increased scopes of data analysis with ease.
Our user perspective webcast will cover:
Application of virtual panels to WES tumor/normal workflows.
Use of the oncogenicity classifier to streamline filter chains.
Updates to our CancerKB database to include the CancerKB gene track.
Including parallel germline secondary findings for the whole NGS workflow.
VarSeq 2.5.0: Empowering Family Planning through Carrier Screening Analysis
Golden Helix introduced new capabilities in VarSeq 2.5.0 to support carrier screening analysis through NGS data. Key features include the ability to import partnered samples, detect shared carrier variants between samples at the gene level using a couples carrier screening workflow, and generate clinical reports that calculate reproductive risks and include variant interpretations. The software is designed to scale from gene panels to whole exomes/genomes. A demo showed how these new features streamline the carrier screening analysis process from data import and filtering to clinical reporting.
Identifying Oncogenic Variants in VarSeq
The interpretation of somatic variants can be a challenging process. While AMP Guidelines provide detailed rules for accessing the clinical evidence associated with a specific variation, they do not specify criteria for determining if a variant is likely to be a driver mutation, which generates functional changes that enhance tumor cell proliferation. In this webcast, we will discuss a new VarSeq algorithm for estimating the oncogenicity of a variant. This will include a deep dive into our oncogenicity scoring system and a discussion of the various criteria used to distinguish driver mutations from benign variations and variants of uncertain significance.
What you will learn in this webcast:
-How to use the scoring algorithm to identify variants with evidence of oncogenicity
-Which criteria are used to assess a variant's oncogenicity
-How to evaluate the oncogenicity of a variant in VSClinical
Best Practices for Validating a Next-Gen Sequencing Workflow
Validating an NGS workflow is an iterative process that begins with collaboration with personnel and planning protocols for the entire workflow from sample preparation, sequencing and variant calling, all the way to data analysis and reporting. At Golden Helix, while we do not provide pre-validated black-box workflows, we provide our customers with support to validate workflows in a transparent manner, and assist them in reaching production deadlines. This webcast will be led by members of our Field Application Scientist team, and we will explore some of the best practices for NGS workflow validation that we have observed and helped to implement based on real-world examples from our customer base. Key topics for discussion will include:
Sample preparation and collection of adequate case/control data
Designing a robust workflow with special considerations for single versus family analyses and phenotypic considerations
Generating the desired output for clinical or other reports
Real world NGS workflow validation strategies
Tune in for tips and strategies that you can deploy when designing and validating your NGS workflow.
2023 Innovation Awards Winner, Dr. Muthukumaran
Expanded carrier screening in an infertile/affected Couple for determining carrier status for genetic mutations - VarSeq Couple Carrier Workflow
VarSeq 2.4.0: VSClinical ACMG Workflow from the User Perspective
The document provides information about Golden Helix's VarSeq 2.4.0 software and its VSClinical ACMG workflow module. It summarizes a presentation given on the topic, including details about Golden Helix as a company, the content covered in the presentation, and examples that will be demonstrated including analysis of variants, copy number variants, and structural variants from PacBio long read sequencing data using VSClinical.
VarSeq 2.4.0: Structural Variants and Advanced Automation in VSClinical ACMG
Mendelian disorders can be caused by various classes of genetic mutations, from small variants to CNVs and even Structural Variants. With the introduction of VarSeq 2.4.0, we are excited to unveil the latest advancements in VSClinical ACMG, focusing on the integration of Structural Variants and the enhanced automation capabilities that streamline your analysis process.
Join us in this webcast as we dive into the following topics:
Integration of Structural Variants: Learn how VarSeq 2.4.0 enables you to import and incorporate Structural Variants into your VSClinical ACMG evaluations and reports, providing a comprehensive understanding of the genetic landscape.
Advanced Automation in the ACMG Interface: Discover how evaluation scripts can be employed to automate the VSClinical ACMG interface, allowing you to perform custom actions or eliminate manual steps, thus increasing efficiency and reducing the risk of errors.
End-to-End Automation: Explore how VSPipeline can fully automate your analysis process, from raw VCF to report, ensuring a streamlined and consistent workflow that saves time and resources.
Harnessing the Power of VSClinical: Gain insights into how VarSeq 2.4.0 empowers you to tackle complex genomic data, enabling faster and more accurate identification of Mendelian disorders and facilitating personalized patient care.
With the advanced capabilities of VarSeq 2.4.0 and VSClinical, you can now unlock a new level of precision and efficiency in diagnosing Mendelian disorders. This webcast will showcase the latest innovations in variant interpretation and automation, exemplifying why the VarSeq Clinical Suite is the premier NGS analysis platform for germline and cancer testing.
The Wide Spectrum of Next-Generation Sequencing Assays with VarSeq
There is a strong motivation for labs to bring most, if not all, of their next-gen sequencing pipeline in-house. This is especially relevant for clinical applications where there is a need to validate any routine diagnostics when seeking to provide genetic results to patients. The entirety of the NGS pipeline is highly automatable and comprised of multiple stages but from the geneticist's point of view, the tertiary stage requires the lengthiest review. This stage is where the geneticist sifts through the massive collection of genetic variants to find and report on those most relevant to the patient or population. Unfortunately, the tertiary stage can be a fairly sophisticated process and there aren’t many tools on the market that handle it comprehensively and simply. Many of the tools that are available may have severe limitations on the scale of genomic data they can process or limitations on the types of NGS assays that can be designed. Moreover, their license model may be on an individual sample basis and present cost-benefit hurdles for the user, especially when sample load will inevitably increase. Fortunately, none of these assay or cost-based issues are relevant with Golden Helix products.
The goal of this webcast is to expose our viewers to the versatility that GHI VarSeq provides when constructing your dream NGS assay. This demonstration will provide examples of germline and somatic workflows for both single and multi-sample analysis for a variety of different disorders. Please join us and learn more about the analytical possibilities you can achieve when using the VarSeq software.
Prenatal Genetic Screening with VarSeq
Our past webcast explored the current approaches for screening and diagnosis of genetic disorders in prenatal testing. While the methods available at the time were robust, they were severely limited, creating a need for a higher diagnostic yield and more efficient analysis for a wider range of genetic tests. The solution proposed was to improve and simplify prenatal screening and diagnosis with whole exome sequencing (WES).
During that webcast, we highlighted the advantages of WES over traditional methods such as karyotyping and chromosomal microarray, including improved accuracy, granularity, and cost-effectiveness. We also emphasized the potential of WES to expand diagnosis for many other adverse maternal-fetal complications beyond the large aneuploidy events previously covered. However, there was still an intimidation factor when it came to the massive data output from the exome. Fortunately, Golden Helix provided the necessary tools to build and standardize these genetic assays, simplifying the analytical process while leveraging increased diagnostic output. We explored our VarSeq software to demonstrate some example workflows of cases positive for Trisomy 21, an exon loss in DMD related to Duchenne Muscular Dystrophy, and detection of a single base change resulting in a LOF variant in RUNX1 relevant to hereditary leukemia.
Our goal was to expose our viewers to the methods of conquering this vast NGS-based data and play a role in dissolving any feeling of intimidation. Overall, exome sequencing has the potential to vastly improve diagnostic outcomes and widen discoveries in the research related to prenatal testing, and Golden Helix products are designed to facilitate this process.
Automated FASTQ to Reports with VarSeq Suite: A fast, flexible solution
NGS tests in the clinic cover more use cases than ever and are increasingly complex to implement. This leads to an increase in time to validate and bring tests to production, impacting a lab’s ability to be economically viable and serve the needs of patients. Core to the complexity is the expansion of tests to include multiple types of biomarkers and variants, including CNVs, gene fusions, and genomic signatures. The bioinformatics demands of these pipelines require powerful tools with built-in capabilities to handle the diverse needs of modern NGS tests and to integrate and automate the disparate steps leading to clinical insight.
Join us in this webinar as we explore the VarSeq suites’ capabilities as a fast, modular, and highly configurable solution for variant analysis and interpretation. We will cover:
The bioinformatic diversity of comprehensive genetic tests with NGS
Automation of FASTQ to clinical reports without losing control over the results of a test
Leverage built-in and custom automation capabilities in the VSClinical cancer guideline workflow to reduce work and improve accuracy
Reporting the relevant diagnostic and therapeutic findings for a patient based on the raw genomic data of modern NGS tests requires both human experience and advanced analysis software. We hope you can join us as we unpack how automation is a critical part of implementing NGS tests and furthering the application of precision medicine.
Maximizing the Benefits of Comprehensive Genomic Testing in Cancer Care with ...
Comprehensive genomic testing via next generation sequencing (NGS) is being increasingly adapted as part of cancer care in conjunction with molecular and immunohistochemical tests. Comprehensive genomic profiling potentially expands the number of targeted therapies that are available to patients, improves patient diagnosis and prognosis, and increases the number of clinical trials that are relevant to patients. However, with these advancements come challenges such as gaps in expertise resulting in inadequate efforts to interpret genomic data accurately and efficiently, poorly coordinated efforts to implement precision care, patients being diagnosed and treated despite inadequate access to relevant information and subsequent lack of patient exposure to all available treatment options.
Golden Helix CancerKB v2.0 provides a means of closing the gap, whether you're a beginner who is trying to capture the vast amount of knowledge in the cancer field or an expert who has high sample volume AND needs to keep up with the ever-evolving knowledge of Tier II and III variants. In this webcast, we will discuss and apply Golden Helix CancerKB in the context of cancer precision medicine. Golden Helix CancerKB is systematically curated and reviewed by experts in the field and contains information about cancer genes, biomarkers, and treatments generated from several trusted cancer resources. With VarSeq 2.3.0’s added support for comprehensive cancer genomic profiling tests, Golden Helix CancerKB has expanded to include interpretations for genomic signatures, combination biomarkers, and more investigational (tier II) biomarkers, among several other additions that will be discussed. With the Golden Helix CancerKB database, users will experience a streamlined automatic matching of biomarkers to available drugs and trials which ultimately saves users massive amounts of time and effort while reducing the possibility for errors.
A User’s Perspective: Somatic Variant Analysis in VarSeq 2.3.0
VarSeq 2.3.0 facilitates the evaluation of a multitude of somatic genomic variations with a more refined user interface to streamline variant evaluation. Our recent webcasts have shown the full range of these newly developed upgrades:
VarSeq 2.3.0: Supporting the Full Spectrum of Genomic Variation
VarSeq 2.3.0: New TSO-500 and Genomic Signature Support in VSClinical AMP
Now, we are showing it all in action from the user’s perspective. This webcast will provide a comprehensive demonstration of performing somatic variation analysis and reporting. We will review how to use workflow automation to expedite the NGS project creation process and report rendering. We will also demonstrate the streamlined capture of knowledge during variant evaluation by leveraging our clinical expert-curated interpretations with the Golden Helix Cancer Knowledge Base (CancerKB).
We hope you will join us to see VarSeq 2.3.0 from a user’s perspective, covering:
-Somatic variant workflows: necessary algorithms and filtering strategies
-Import of all relevant biomarker and genomic signatures data from TSO-500
-Review content and value of clinically curated interpretations and treatments with CancerKB
-Interpretation of structural variants in the VSClinical AMP Guidelines workflow
-Workflow automation with VSPipeline
VarSeq 2.3.0: Supporting the Full Spectrum of Genomic Variation
Next Generation Sequencing allows for the detection of a wide variety of genomic alterations. This includes small mutations, copy number variants and complex rearrangements. However, it can be difficult to annotate, filter, and interpret these alterations.
As part of our VarSeq 2.3.0 release, we have greatly simplified this process by allowing you to import, annotate, and filter mutations across all spectrums of genomic variation. This supports concurrent importation of small variants and CNVs as well as complex rearrangements. This release also includes strong support for structural variant annotation, filtering, and interpretation, including structural variant effect prediction. After filtering is complete, any clinically relevant structural variants can be interpreted with the VSClinical AMP Guidelines workflow and included in the final clinical report.
Come join us for this webcast to discuss VarSeq’s enhanced import and annotation capabilities, including:
Concurrent importation of variants CNVs and complex rearrangements
Improved multi-threaded import which dramatically speeds up the importation of large VCFs
Annotation of structural variants and prediction of effect
Interpretation of structural variants in the VSClinical AMP Guidelines workflow
Support for visualization and use of CRAM files as input for computing coverage statistics
VarSeq 2.3.0: New TSO-500 and Genomic Signature Support in VSClinical AMP
Precision medicine for cancer is rapidly accelerating because of the development and approval of targeted molecular therapies. These therapies require new genomic biomarkers as an indication for use, and require evaluating additional mutation types that are available in comprehensive genomic profiling assays as well as the small variants detected by Next-Generation Sequencing gene panels.
We are excited to announce VarSeq 2.3.0 which will update the VSClinical AMP workflow to meet the growing needs of labs conducting comprehensive genomic profiling (CGP) of tumors. This includes built-in support for the Illumina TruSight Oncology 500 (TSO-500) kit as well as similar kits from other vendors. The VSClinical AMP workflow has also gained native support for the bioinformatic outputs of CGP kits. Join us to learn about comprehensive genomic profiling in cancer, specifically:
Evaluation and clinical reporting of genomic signatures such as Microsatellite (MSI), Tumor mutation burden (TMB), PD-L1, Homologous recombination deficiency (HRD) statuses, and more.
Built-in TSO-500 import and expandable import capabilities for new genomic data types through the new advanced workflow scripting system.
Golden Helix CancerKB updates with report-ready genomic-signature interpretations written for approved therapies as well as gene interpretations for all 500 genes of the TSO-500 panel. In addition, CancerKB scopes have been extended to reference multiple relevant biomarkers in a single interpretation, capture approved therapies at the tumor type level, and include interpretations for clinically relevant negative findings.
Expanded clinical trial support to include international trials and the ability to search within proximity of European postal codes. VSClinical is accessing all active studies in AACT/ClinicalTrials.gov wherein users can search and select trials based on relevant drugs, biomarkers, and the geographic distance to the patient or testing site.
VarSeq 2.3.0 will deliver powerful capabilities for genomic profiling in cancer, enabling a new level of personalized and effective care for your patients. We look forward to demonstrating these updates and Golden Helix’s continued innovation making the VarSeq Clinical Suite the NGS analysis platform of choice for germline and cancer testing.
Single Sample and Family Based Genome Analysis With VarSeq
One major hurdle facing medicine is the need to quickly identify and assess the genetic components contributing to rare diseases. It has been estimated that nearly 350 million people suffer from rare diseases, 140 million of which are children, of whom ~30% do not live past their fifth birthday1,2. The specific issue to overcome is reducing morbidity by facilitating rapid diagnosis and treatment. Fortunately, the cost of whole genome sequencing has dropped below the $1000 mark, which not only makes the NGS approach more affordable but has become the status quo method of comprehensive diagnosis for these rare disorders. Currently, there are limited options in the market when it comes to quality software that can scale to this size of data and handle variant processing and evaluation in a timely fashion. Fortunately, Golden Helix has sought to set the market standard for top-quality NGS analysis with our bioinformatic software VarSeq. The focus of this webcast will be to explore example workflows tailored for rare disorders and elaborate on how best to expedite the NGS pipeline process with our command-line tool VSPipeline.
During the webcast, we will address the following:
Customizing clinically validated NGS workflows with VarSeq for both single sample and trios
Demonstrating the automation of ACMG-based guideline review in the VSClinical variant interpretation hub and rendering of customized clinical reports
Expediting the NGS workflow via Golden Helix command-line tool VSPipeline
We look forward to you joining us for our presentation, where we can demonstrate the value of our products when building your next-gen workflows. Ultimately, we wish to diminish the intimidation of genome workflow design and leave our future customers feeling confident that there is capable software to suit their needs.
Bick D, Jones M, Taylor SL, et al. Case for genome sequencing in infants and children with rare, undiagnosed or genetic disease. J Med Genet 2019; 56:783-791.
Owen M, Lefebvre S, Hansen C, et al. An automated 13.5 hour system for scalable diagnosis and acute management guidance for genetic diseases. Nat Commun 2022; 13: 4057. https://doi.org/10.1038/s41467-022-31446-6
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Introducing VarSeq Dx as a Medical Device in the European Union
VarSeq 2.6.0: Advancing Pharmacogenomics and Genomic Analysis
VarSeq 2.6.0: Advancing Pharmacogenomics and Genomic Analysis
Introducing VSPGx: Pharmacogenomics Testing in VarSeq
Introducing VSPGx: Pharmacogenomics Testing in VarSeq
Analyzing Performance of the Twist Exome with CNV Backbone at Various Probe D...
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From Panels to Genomes with VarSeq: The Complete Tertiary Platform for Short ...
From Panels to Genomes with VarSeq: The Complete Tertiary Platform for Short ...
VarSeq 2.5.0: VSClinical AMP Workflow from the User Perspective
VarSeq 2.5.0: VSClinical AMP Workflow from the User Perspective
VarSeq 2.5.0: Empowering Family Planning through Carrier Screening Analysis
VarSeq 2.5.0: Empowering Family Planning through Carrier Screening Analysis
Best Practices for Validating a Next-Gen Sequencing Workflow
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VarSeq 2.4.0: VSClinical ACMG Workflow from the User Perspective
VarSeq 2.4.0: VSClinical ACMG Workflow from the User Perspective
VarSeq 2.4.0: Structural Variants and Advanced Automation in VSClinical ACMG
VarSeq 2.4.0: Structural Variants and Advanced Automation in VSClinical ACMG
The Wide Spectrum of Next-Generation Sequencing Assays with VarSeq
The Wide Spectrum of Next-Generation Sequencing Assays with VarSeq
Automated FASTQ to Reports with VarSeq Suite: A fast, flexible solution
Automated FASTQ to Reports with VarSeq Suite: A fast, flexible solution
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A User’s Perspective: Somatic Variant Analysis in VarSeq 2.3.0
A User’s Perspective: Somatic Variant Analysis in VarSeq 2.3.0
VarSeq 2.3.0: Supporting the Full Spectrum of Genomic Variation
VarSeq 2.3.0: Supporting the Full Spectrum of Genomic Variation
VarSeq 2.3.0: New TSO-500 and Genomic Signature Support in VSClinical AMP
VarSeq 2.3.0: New TSO-500 and Genomic Signature Support in VSClinical AMP
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A Walk Through GWAS
- 1. A Walk Through GWAS January 20th, 2016 Jami Bartole Senior Field Application Scientist
- 2. Use the Questions pane in your GoToWebinar window Questions during the presentation
- 3. Golden Helix – Who We Are Golden Helix is a global bioinformatics company founded in 1998. We are cited in over 900 peer-reviewed publications
- 4. Our Customers Over 200 organizations world wide, and thousands of users, trust our software.
- 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 RESPONSIVENESS TRANSPARENCY INNOVATION and SPEED CUSTOMIZATIONS
- 6. Core Features Packages Core Features Powerful Data Management Rich Visualizations Robust Statistics Flexible Applications Genotype Analysis DNA sequence analysis CNV Analysis RNA-seq differential expression SNP & Variation Suite (SVS)
- 7. GenomeBrowse Powerful visualization software for DNA and RNA sequencing data Supports most standard bioinformatics file formats Fast and responsive for interactive analysis Intuitive controls Stream data from the cloud and from your own remote data servers
- 8. Approximate Agenda Explore Results from a GWAS Project Q&A 2 3 4 Population Stratification in Analysis 1 Background of GWAS
- 9. A brief background of GWAS First the naïve approaches: Trend Tests, Contingency Tables, Linear/Logistic Regression Batch Effects, Population Structure and sharing of controls may violate assumptions of the naïve approaches and result in confounding of results. Stratification effects are more pronounced with larger sample sizes. Non-independence of samples is especially problematic in agrigenomic applications.
- 10. Summary of GWAS Dataset 513 individuals 29 populations from the Human Genome Diversity Project (HGDP) Illumina Infinium HumanHap550 Genotyping BeadChip Simulated Case/Control Phenotype
- 11. Demonstration
- 12. Q-Q Plots λ = 2.549 λ = 0.979 λ = 1.049
- 13. Demonstration
- 14. Overview of Methods Corr/Trend Test • Quality Control of Samples and Markers PCA Correction (Eigenstrat Price 2006) • Direct correction of genotype and phenotype data • Adding PCs as covariates to regression model EMMAX (Kang 2010) • Using the Genomic Relationship Matrix (IBD) to account for stratification Naïve GWAS GWAS + Correcting for Population Stratification Mixed Model Approach
- 15. Demonstration
- 16. Summary • Performed Basic Association Test • Verified contingency table counts http://goldenhelix.com/SNP_Variation/scripts/pages/FrequencyTable.html • Q-Q Plot to look for inflation of p-values http://goldenhelix.com/SNP_Variation/scripts/pages/CalculatePseudoLambda.html • Examined workflow to determine reasons for inflation of p-values • Sample/Marker Statistics • Call Rate Histograms • Cryptic Relatedness through IBD • IBD Heat Maps • Population Stratification with PCA • PCA Plots (2D & 3D) • Adjusted Analysis for Population Stratification • Using PCA from within Association Testing dialog • Using PCs as Covariates in Numeric Regression • Using Mixed Linear Model Analysis
- 17. Questions or more info: Email info@goldenhelix.com Request an evaluation of the software at www.goldenhelix.com Check out our abstract competition!