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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Genome-wide association studies (GWAS) have been providing valuable insight to the genetics of common and complex diseases for nearly 10 years. Despite some assertions to the contrary, GWAS is not dead. GWAS is alive and well, and remains a viable technology for genetic discovery.
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Genotype association testing and statistics: Contingency tables, linear and logistic regression, Mixed Linear Models, and more.
Visualizations including Manhattan Plots, linkage disequilibrium plots, and genomic annotation sources.
Exploring public databases to investigate your results.
Tips for using exome chips and other targeted genotyping platforms.
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Potential for Genomic Selection in indigenous breeds and results of GWAS in G...Superior Animal Genetics (SAG)
Potential for genomic selection in indigenous cattle breeds and results of GWAS in Gir dairy cattle of Gujrat by Dr.Pravin Kandhani and Dr. Vijay Trivedi KAMDHENU UNIVERSITY GANDHINAGAR 2015 bio it visualizing genomic variants and annotations is vital for accur...
This document summarizes a presentation about visualizing genomic variants and annotations for accurate interpretation. It discusses the speaker's background working on genetic association software and tools for analyzing single nucleotide polymorphisms, copy number variants, and next-generation sequencing data. It emphasizes the importance of visualizing variants in genomic context, alignment evidence from BAM files, representing variants and annotations consistently, and left-aligning data to facilitate comparison. Examples are provided of visualizing the speaker's own variants and those of family members identified through consumer genomics testing.
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.
Ngs webinar 2013
The document discusses GeneRead DNAseq Targeted Exon Enrichment and GeneRead Library Quantification System for Next Generation Sequencing. It provides an overview of the targeted enrichment workflow and principles, pathway-focused analysis tools, library quantification workflow, and performance data. The targeted enrichment panels allow users to focus sequencing on genes of interest, improve detection of low prevalence mutations from poor quality samples. The library quantification system uses qPCR to accurately quantify sequencing libraries and assess sample quality before NGS runs.
Research Program Genetic Gains (RPGG) Review Meeting 2021: From Discovery to ...
A number of advances in genetics and genomics research of pigeonpea. These advances have enhanced our understanding of structural and functional aspects of genome and also provided us opportunities to deal with constraints impeding production of pigeonpea in precise and faster manner. Availability of the draft genome sequence and large-scale molecular markers has made it possible to map traits of interest in speedy manner. Although germplasm re-sequencing has already been started in pigeonpea, large-scale germplasm including elite breeding line, landraces and wild species is expected to be fully sequenced very soon.
2013 02-14 - ngs webinar - sellappan
The document describes QIAGEN's GeneRead DNAseq Targeted Exon Enrichment and GeneRead Library Quantification System for next generation sequencing. It discusses targeted enrichment workflow and principles, data analysis, pathway content of panels, performance data and application examples. It also covers the library quantification workflow, using qPCR to quantify sequencing libraries, and a DNAseq library quantification array to assess sample quality. The document is aimed at promoting these NGS sample preparation and analysis solutions to potential customers.
Genotype imputation study in Gir dairy cattle of Gujarat
The present study was conducted with the aim of reducing the cost of implementing Genomic Selection(GS) by using Genotype imputation methodology in Gir cattle. Application of GS mainly depends upon the cost of genotyping and reduce its cost, imputation approaches have been used. Imputation strategies and GS have been comprehensively studied in several taurine dairy cattle populations but very limited information is available on indigenous populations. Factors that affect the efficiency of imputation and GS are population structure, linkage disequilibrium between markers and differing marker density between indigenous and taurine breeds. The objective of the study was to evaluate the performance of INDUSCHIP-1, a customized Illumina bovine microarray chip for indigenous cattle breeds, designed by National Dairy Development Board, Anand and design one (7-15K) LD panel, and evaluate the performance of two panels of INDUSCHIP-1, and a 13K subset of the same for its imputation accuracy to HD (777K or INDUSCHIP-1 level). Thus, the study was planned with the aim to design LD panel for genotype imputation to INDUSCHIP-1 level with the strategy to maximize the accuracy of imputation in Gir cattle.
2015 functional genomics variant annotation and interpretation- tools and p...
Presented at the 2015 Functional Genomics Symposium in Doha, Qatar: http://events.sidra.org/event/functional-genomics-symposium/
Genome Wide SNPs for Admixture Analysis and Selection Signatures
The presentation presents basic concepts and describes various advanced uses of Genome Wide SNP markers for Admixture Analysis and Selection Signatures. The usage of SNP markers has made tremendous progress in recent times and it shall help in application of genomic selection in developing countries including India
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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:
-How to identify pharmacogenomic diplotypes and drug recommendations from NGS data.
-How to incorporate externally called CNVs and SVs into your PGx annotations.
-How to generate customizable PGx reports from these annotations.
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:
-The sensitivity rate for the detection of known CNV events at all three probe densities.
-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:
-Data analysis scaling from Gene Panel to Genome analysis with VarSeq and VSWarehouse.
-Analysis and annotation of SNVs, Indels, CNVs, and fusions.
-A close look at a PacBio long-read trio analysis.
Come join us for this showcase in modern VarSeq analysis capabilities.
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.
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.
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Introducing VarSeq Dx as a Medical Device in the European Union
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...
Analyzing Performance of the Twist Exome with CNV Backbone at Various Probe D...
From Panels to Genomes with VarSeq: The Complete Tertiary Platform for Short ...
From Panels to Genomes with VarSeq: The Complete Tertiary Platform for Short ...
Enhance Genomic Research with Polygenic Risk Score Calculations in SVS
Enhance Genomic Research with Polygenic Risk Score Calculations in SVS
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
Best Practices for Validating a Next-Gen Sequencing Workflow
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
Maximizing the Benefits of Comprehensive Genomic Testing in Cancer Care with ...
Maximizing the Benefits of Comprehensive Genomic Testing in Cancer Care with ...
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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- 1. Exploring GWAS, Genomic Prediction, and Imputation using SVS Steve Hystad - Field Application Scientist 20 most promising Biotech Technology Providers Top 10 Analytics Solution Providers Hype Cycle for Life sciences
- 2. Use the Questions pane in your GoToWebinar window Questions during the presentation
- 3. 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)
- 4. 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
- 5. Approximate Agenda GBLUP2 3 Imputation 1 GWAS workflow, correction of data
- 6. Simulated Cattle Data 402 Bos taurus cattle from Bovine HapMap project Illumina 50k genotypes Simple oligogenic trait simulation - 5 SNPs with independent additive effects - About 62% of trait explained by simulated genetic effect Angus 5% BeefMaster 4% Brown Swiss 7% Charolais 6% Guernsey 6% Hereford 4% Holstein 15% Jersey 7% Limousin 7% N'Dama 7% Norwegian Red 5% Piedmontese 7% Red Angus 2% Romagnola 7% Santa Gertrudis 7% Sheko 5%
- 8. Q-Q Plots λ = 2.19 λ = 0.979 λ = 1.049
- 9. 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
- 11. Genomic Prediction Methods Available in SVS GBLUP - Assumes all loci contribute to the phenotype Bayes C - Estimates effects of gene loci together with parameters required to define probability distribution over events - Prior probability that any SNP will have no effect fixed Bayes C-pi - Prior probability that any SNP will have no effect unknown and allowed to vary
- 12. Why Use Genomic Prediction? Calculate breeding value (gEBV) for all subjects in a population - May be more accurate than breeding selection based only on pedigree and trait data Predict breeding values for subjects with unknown phenotypes - May avoid costly and lengthy field trials - May not always be possible to measure the phenotype Identify genetic markers with best predictive power for a trait - Assist in development of predictive tests and other assays OR ?
- 13. GBLUP Assumes all loci contribute to phenotype Incorporates genomic relationship matrix (GRM) in mixed linear model framework to account for relatedness among samples Calculates allele substitution effect (ASE) for each SNP Computes estimated breeding values (GEBV) and predicted phenotypes for all samples Also calculates: - Pseudo-heritability of trait - Genetic component of trait variance - Error component of trait variance
- 15. Why Imputation Fill in Missing Genotypes - Improve quality of GT calls Harmonizing Arrays - Facilitate meta-analyses that combine studies genotyped on different sets of variants Increase Genotypes - Increases the power and resolution of genetic association studies. - Find candidate susceptibility variants to guide fine-mapping.
- 16. Questions or more info: Email info@goldenhelix.com Request an evaluation of the software at www.goldenhelix.com Check out our abstract competition!