Integrating Custom Gene Panels for Variant Innovations
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The ability to use predefined sets of genes to isolate clinically relevant variants is an important aspect of clinical variant analysis. Golden Helix’s VarSeq product houses the tools, namely our Gene Panel Manager and Match Genes set of algorithms, that enable users to create and manage reusable gene lists within projects, incorporate the ACMG Secondary Findings v3.0 gene list for the reporting of incidental findings, make use of well validated publicly available gene panels with published evidence of disease associations and create gene panels based on specific disorders or phenotypes of interest. These capabilities were covered in a webcast “Creating and Managing Reusable Gene Lists with VSClinical” by Dr. Nathan Fortier our Director of Research. In the upcoming webcast, we will dive deeper into these capabilities, implementing our gene panel tools from the user’s perspective by focusing on two clinical use cases where custom virtual gene panels are particularly useful. For the standard use case, users typically incorporate targeted gene panel-based data to hone in on any number of variants that fall within the scope of their targeted genes list. More recently, we have observed from the field application perspective, a trend among Golden Helix customers towards importing WES and WGS data followed by creating unique per sample gene panels. Therefore, the purpose of this webcast will be to showcase how simple it can be to construct and manage both styles of virtual gene panels within VarSeq in ways that will best suit the specific needs of your lab. We will share with you several clever shortcuts for users to implement filters on gene panels, to design and manage gene panels and calculate the coverage over these regions. We will also delve into the details of incorporating gene panel data into variant evaluation in VSClinical and bringing the relevant information into a final clinical report. Viewers tuning in to this webcast will be exposed to all the tools available in VarSeq for creating and managing their potential gene panel workflows.
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Integrating Custom Gene Panels for Variant Innovations
- 1. Integrating Custom Gene Panels for Variant Annotations February 9, 2021 Presented by Rana Smalling, Ph.D, Field Application Scientist
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- 3. Integrating Custom Gene Panels for Variant Annotations February 9, 2021 Presented by Rana Smalling, Ph.D, Field Application Scientist
- 4. NIH Grant Funding Acknowledgments 4 • Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under: o Award Number R43GM128485-01 o Award Number R43GM128485-02 o Award Number 2R44 GM125432-01 o Award Number 2R44 GM125432-02 o Montana SMIR/STTR Matching Funds Program Grant Agreement Number 19-51-RCSBIR-005 • PI is Dr. Andreas Scherer, CEO of Golden Helix. • The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
- 5. Who Are We? 5 Golden Helix is a global bioinformatics company founded in 1998 Filtering and Annotation ACMG & AMP Guidelines Clinical Reports CNV Analysis Pipeline: Run Workflows CNV Analysis GWAS | Genomic Prediction Large-N Population Studies RNA-Seq Large-N CNV-Analysis Variant Warehouse Centralized Annotations Hosted Reports Sharing and Integration
- 6. Cited in 1,000s of Peer-Reviewed Publications 6
- 7. Over 400 Customers Globally 7
- 8. When you choose Golden Helix, you receive more than just the software 8 Software is Vetted • 20,000+ users at 400+ organizations • Quality & feedback Simple, Subscription- Based Business Model • Yearly fee • Unlimited training & support Deeply Engrained in Scientific Community • Give back to the community • Contribute content and support Innovative Software Solutions • Cited in 1,000s of publications • Recipient of numerous NIH grant and other funding bodies
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- 11. 11 Audience Poll What is the source of your gene panel(s) (select all that apply)? A. Physician ordered clinical test. B. Established or published panels with known disease association such as Genomics England PanelApp. C. Gene list from targeted gene panel sequencing kit. D. Gene list based off internal research on your disease or phenotype of interest.
- 12. Challenge: Optimizing Variant Filtering and NGS Pipeline 12 • Routine filtering strategies: • Variant Quality (Read depth, Genotype Quality, Filter is PASS) • Remove common variants in population frequency catalogs (1Kg Phase 3, Gnomad) • Gene impact (LOF, missense, splice variants) • ACMG autoclassifier • Virtual gene panels
- 13. Gene Panels in Clinical Variant Analysis in 13 • Clinical or research groups often identify lists of genes associated with their disease or phenotype of interest. • Users can use gene panels in VarSeq to prioritize variants found in genes from an NGS gene panel or clinical test. • Panels can be used with multiple samples or projects. • More than one panel can be applied per sample. • Established organizations also curate standard gene lists with known disease association (e.g. Genomics England PanelApp). • August 2021 Webcast: “Creating & Managing Reusable Gene Lists with VSClinical” by Dr. Nathan Fortier. https://www.goldenhelix.com/resources/webcasts/creating- managing-reusable-gene-lists-with-vsclinical/index.html Disorder Gene A Gene B Gene C
- 14. Manage Your Gene Panels With 14 • You can now easily create Gene Panels using our Gene Panel Manager in VarSeq. • Leverage Panel App for incorporating published panels and filter on genes with evidence of association with diseases or phenotypes. • Query genes for specific disorders and phenotypes and in HPO and MONDO databases. • The ACMG SF gene list comes default in VarSeq panel library. • Ways to use Gene Panels in your VarSeq projects and templates: • Add a Gene Panel Filter filter card to use your Gene Panels as filters in a VarSeq project or template. • Match Gene and Panels algorithm to enter custom list to prioritize variants and CNVs in relevant genes
- 15. ACMG Secondary Findings Genes 15 • ACMG has published a policy statement for reporting incidental findings in exome/genome sequencing. • The ACMG SF genes list was updated in May 2021. • Laboratories should report pathogenic and likely pathogenic variants occurring in the listed genes. • These genes are linked to “actionable” disorders. • This list is updated periodically, and labs should maintain an up-to-date list of genes.
- 16. Gene Panels Per Sample 16 • Sample manifest text files can be used to bring in gene panels or lists per sample in a large-scale dataset. • Use our Match Panels (Per Sample) algorithm to match panels specified in the samples table • Set up VSClinical to include specific panels in a variant evaluation and clinical report. • View selected Gene Panel along with Coverage Statistics under the Gene tab in VSClinical.
- 17. Project Demo Overview 17 For today’s demonstration we will be looking at two clinical use cases where virtual gene panels are applicable: • A somatic workflow of a multi-cancer samples on which a comprehensive cancer gene panel was performed. • A germline trio workflow for epileptic seizure disorder where the whole genome sequencing was done on the parents and proband.
- 18. 18 Product Demo
- 19. NIH Grant Funding Acknowledgments 19 • Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under: o Award Number R43GM128485-01 o Award Number R43GM128485-02 o Award Number 2R44 GM125432-01 o Award Number 2R44 GM125432-02 o Montana SMIR/STTR Matching Funds Program Grant Agreement Number 19-51-RCSBIR-005 • PI is Dr. Andreas Scherer, CEO of Golden Helix. • The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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- 22. 22 Abstract Competition The 2022 Golden Helix Innovation Awards will run from Dec. 1st, 2021 - Feb. 28th, 2022 • We want to see how YOU are using our tools to the best of their ability. • Anyone using Golden Helix Software tools is eligible to submit for entry, and no prior publication of research is required. • Submissions can be for clinical or hospital laboratory work, academic research, government, or commercial, we just want to see great examples of your workflows. • 3 winners, each receiving 1 user license for either SVS or VarSeq, and first place receiving in addition a Dell Latitude 5000 series laptop. • All winners will receive the opportunity to present their research via webcast. Goldenhelix.com/events/innovation_awards
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Editor's Notes
- Thank you Casey! I am so excited to present on this topic. Our Gene panel mgmt. tools are some of my favorite tools to use for variant annotation and filtering.
- Before we get started, I wanted express our appreciation for our grant funding from the NIH. Our research has been supported by the National institute of general medical sciences of the national institutes of health under the listed awards. Additionally we are also grateful for receiving local grant funding from the state of Montana. Our PI is Dr. Andreas Scherer who is also the CEO at Golden Helix and the content described today is the responsibility of the authors and does not officially represent the views of the NIH. So with that covered, lets take just a few minutes to talk a little bit about our company Golden Helix.
- To get started, let me tell you about our company - GoldenHelix is a global bioinformatics company that provides industry leading solutions for researchers and clinical practices to analyze next generation sequencing data and generate clinical reports. We were founded in 1998 based on pharmacogenomics work done at Glaxosmithkline, and they still invest in our company today. We currently have 2 flagship products, VarSeq and SNP and variation suite (SVS for short): VarSeq, is our suite of clinical tertiary analysis tools, tailored for variant annotation and filtration. Varseq allows users to automate variant classification based on the AMP or ACMG standards and guidelines and can also be used to detect copy number variations ranging from single exome to large aneuploidy level events. Additionally, users can finalize and standardize their variant interpretations within VarSeq using our clinical reporting feature. Paired with VarSeq is VSWarehouse which serves as a repository for the large amounts of data being generated by our users. Warehouse also allows users to easily query their data, and define different levels of user access for team members. SNP and VariationSuite (SVS for short) is our research platform, one of our earliest flagship products, which enables researchers to perform complex analysis and visualizations on genomic and phenotypic data. SVS has a range of tools to perform GWAS, Genomic Prediction, RNA-Seq analysis and processing of CNVs.
- Our suite of products have been very well received by the industry. In fact, (or Not to brag, but..) since we began, we’ve been we’ve been cited in thousands of peer-reviewed publications which include reputable journals like Science, Nature, Nature genetics and that’s a reflection of our customer base.
- We’re also proud to say that we work with over 400 organizations all over the globe. top-tier institutions, Stanford and Yale government organizations, NCI USDA And Several clinics and genetic testing labs, We have exceeded 20,000 installs of our products with 1,000’s of unique users. And this is relevant to you because…
- With Golden Helix, you’re getting more than just the software - Over the course of 20+ years our products have received a lot user feedback. We immediately incorporate this feedback into developing and releasing newer versions of our products. Updates to our software capability is constantly directed from our user feedback and awareness of the industry needs. **In order to stay relevant in the community we regularly attend conferences and provide useful product information via eBooks, tutorials, and blog posts which can be found on our website. ***Your access to the software is via a simple subscription-based model – we’ll never charge per sample nor per version. And, our support and training staff are always available to get you up to speed quickly with your analysis. ** We strive to maintain industry leader status for our software and so we actively pursue research grants to support the advancement of our software capability.
- In terms of our software menu for Varseq – we provide users the capability to start with an initial FASTQ file all the way down to a clinical report. This is achievable through our partnership with Sentieon which handles the alignment and variant calling steps to produce the BAM and VCF files. This output serves as the basis for CNV detection and import data for your tertiary analysis in VarSeq. If you are performing NGS based CNV analysis, Golden Helix is the industry leader. This is supported by studies like the Robarts Research Institute study showing our 100% concordance with MLPA. Additionally, the imported variants in your VarSeq project can be run through VSClinical’s automated ACMG and AMP guidelines. After completing secondary and tertiary processing, all analysis can be rendered into a clinical report which can be stored in VSWarehouse enabling researchers and clinicians to access to this information and to view previous findings.
- A major value proposition of Varseq is the automation of workflows and incorporation of guidelines for doing variant annotations and interpretations. There is a lot to consider when reviewing all the components for the guidelines manually, which makes all the hard work in automating this process so valuable. And for the users, our goal is to not only expose you to the cutting-edge tools, but also simplify their usage without ever losing the technical detail required with any variant evaluation. One way to simplify the user experience is to conceptually separate the VarSeq application into stages. As briefly mentioned earlier, Stage 1 is the importing, detection, and filtering of variants and in this context, we want to hone in on variants of interest by utilizing specific genes in a defined panel, whether that list is limited to genes in a targeted panel or you want to apply a panel to WES scale or WGS data. Then in Stage 2 of the process, we will go through and do the evaluation of your variants using the ACMG or AMP guidelines in VSClinical. VSClinical is embedded in Varseq and you can think of it as an interpretation hub, where we synthesize all the evidence gathered about the variants and automate their classification and scoring. For today’s conversation, we will keep that in the context of variants in your specified genes in a panel once it’s confirmed that we have adequate coverage over those genes. With VarSeq and VSClinical we are automating as many steps as we can, and this of course includes rendering the final interpretation of results in a clinical report. This final report will also include details on the coverage and the clinically relevant findings from those genes in your panel.
- So before jumping into the demo, we would like to make this a little bit interactive and conduct a quick poll, just to get an idea from the listeners in our audience: if you do use virtual gene panels in your variant analysis, what is the source of your gene panels? (Casey will take us through the process) Thanks for that feedback, I see that majority of users have gone with Option …. Which is excellent because e will be talking about that during the demo. So now I will go into some detail on the use of gene panels for variant annotation.
- Firstly, our intrinsic challenge is we want to develop efficient ways to filter through our NGS data. In any workflow, regardless of whether that’s a gene panel, WES, WGS, germline, or somatic, there are going to be standard filtering strategies for identifying clinically relevant variants. On the list below, I have some examples of standard filtering strategies. In a classic per sample variant filtering strategy, it is very common to use quality fields from the VCF as a first pass. We want identify variants with sufficient read depth and genotype quality, for example, and in so doing filter out potential false positives. Another typical filtering strategy that can substantially narrow down to your rare variants is to filter on population frequency databases to remove those that are common in the healthy population. We also want to isolate any variants that affect the gene negatively. While we’re not focusing on any one particular gene we want to filter out variants that are going to impact the gene in some ay that we care about for example LOF or missense mutations or variants that affect splicing. One other powerful filter that Golden Helix provides that is very unique to our software is the ACMG autoclassifier which can be used to isolate any variant that would be pathogenic or likely pathogenic according to the ACMG guidelines. Another hugely beneficial tool for focusing your analysis is to leverage the patient phenotype or deploy a targeted panel**. I’ve provided an extreme example to show the influence of each of these steps and how useful it can be to use a gene panel to filter your variants. The image on the right is an example based on whole genome sequencing of a breast carcinoma, where we’re starting with millions of variants, and you can directly see how effectively each level of filtering reduces the number of variants. After narrowing down the high quality, rare variants that will impact the genes in some way, I can then use a breast cancer gene panel to hone in on the variants that are relevant to this patient, and that gets me down to 32 variants, and then using the ACMG classifier and that brings me down to 5 clinically relevant variants and so you can see how using this strategy, and specifically the gene panel, I was able to find my candidates very quickly. And so, my objective today in this webcast is to teach you all the ways you can deploy the panel using some of our latest features…
- So now we know how powerful the panels can be in a filtering strategy, so let’s talk about how we utilize them in Varseq. When doing clinical variant analysis, lab often identify groups of genes that are in some way linked to the disease or phenotype they are studying or a research group may need some guidance with identifying a list of genes relevant to their disorder of interest. VarSeq is open to any kind of panel that users want to create. We provide users the tools to prioritize those variants that fall within the scope of targeted gene lists, whether that’s from a NGS panel or specific clinical test but we also offer users the tools that can help to build a workflow from scratch. Panels that you create in Varseq are reusable across any number of samples or projects and more than one panel can be applied at the same time. You can also incorporate panels from known organizations or public source tools that curate standard gene lists with well established disease associations, for example Genomics England curates PanelApp, a collection of verified gene lists for a variety of human disorders. For more of an intro on the subject, I will point you to our webcast from last August, “Creating and Managing Reusable Gene Panels” when Dr. Nathan Fortier gave an initial breakdown these features – here’s a link if you want to get an intro to the topic. The purpose of today’s webcast is to elaborate on these features a bit more and dive into what are all the components that a user has to account for when utilizing panels.
- One of our recently developed features is the Manage Gene Panels wizard, shown in the image on the right. With this tool, new panels can be easily added by manually copying and pasting in your own panels or you can search the gene lists supplied by Genomics England PanelApp or you can do phenotype based searches of gene-disease associations in the HPO and MONDO ontologies and our gene panel library also includes by default versions 2.0 and 3.0 of the ACMG SF genes list. Most users will be familiar with these resources but what you can really appreciate is that you now can access these lists directly in our gene panel manager**. This image is just a brief preview of the tools, but I will show you when we get into the demonstration, how these gene panels can be easily integrated into your VarSeq projects and templates using our gene panel filter card and our Match Gene and Panels algorithms.
- One thing you may notice while exploring the Gene Panel manager is that VS provides a couple versions of the ACMG SF gene lists. In May 2021, the American College of Medical Genetics and Genomics released an updated policy statement for reporting incidental findings in exome and genome sequencing data along with a corresponding list of genes. These recommendations state that laboratories should report as incidental findings certain types of mutations occurring in the listed genes,as they are linked to “actionable disorrders. This list is updated periodically, and labs wishing to follow the ACMG recommendations must keep a current list of these genes. We realize that gene panels evolve, So, our inclusion of current versions of this list by default in our Gene panel manager helps lab to stay up to date. (You can see ACMG SF 2.0 had 59 genes, and now were up to 73 genes with version 3.0). So everything we talked about so far has been a general application of panels, where we assume the analysis has been limited to a targeted gene panel or maybe you’re running all your samples through the same virtual panel.
- However, a more recent trend we have seen with our customers are workflows in which each individual sample has to have its unique set of genes. This is especially relevant as large scale WES and WGS analyses or large cohort amalyses have become more common usage and users want to bring in unique gene panels per sample. Good news is, VarSeq has algorithms that will handle per sample gene panel workflows and will adjust the gene panel filter accordingly as you move through the samples in a cohort. When you import your samples into VarSeq you have a sample manifest that includes any information about the sample that you want to bring in, but most importantly this manifest includes a column for you to define the list of genes that are specific for that sample and that can add a level of efficiency to any general workflow for a large scale WGS or WES analysis. These imported gene panels can then be accessed for annotation and filtering using our Per Sample Match Gene list or Match Panels algorithms. An additional point, which will become clear in the demo, is that VSClinical can be configured to specify the panels that should be included in your clinical reports and makes it easy to see the coverage statistics for the specified genes both in the VSClinical evaluation and also in the final report. SO for example if youre working with WGS data, We are not reporting on the coverage for the entire genome but focusing on the coverage for the panel despite the fact that we’re working with whole genome level data.
- So now that I’ve given you some background, let’s take a look at some clinical examples. First example is a straightforward somatic workflow of on a batch of cancer samples , and we’ll use this to demonstrate a per sample gene panel workflow, creating and managing panels from the Gene Panel manager and also investigate any secondary findings from the ACMG SF list, Example 2 is a germline trio for epileptic seizure disorder where whole genome sequencing was done on parents and proband. We will touch on creating a template that is applicable for a whole genome trio analysis to show how powerful the gene panel filter is for identifying relevant pathogenic variants.
- With that, let’s get into the demo! And that brings us to the end of the demonstration. I hope this presentation shed some light on how easy it is to incorporate gene panels in your variant annotation and filtering in VarSeq. So, what we've covered are the basics, but you can always hop on a session with us and we could dive deeper into getting your panels integrated and some other shortcuts. If you would like to revisit this, the webcasts are recorded and on our website for you to rewatch, and we encourage you check out our other blogs and webcasts on this topic,
- In closing, I would like to once again express our appreciation for our grant funding from NIH. We are very grateful for the ongoing support that has helped us to continually improve our product offerings. Thanks for hosting this event, Casey. And thank you, our attendees for joining the webinar, and I will now hand back over to Casey to talk about marketing and special offers we have, and also take any questions.
- Can we leverage phenotypes or disorders instead of searching based on a panel? absolutely, the same approaches discussed today applies to using phenotypes and leveraging the PhoRank algorithm 2. Can you use a bed file to define the panel? yes but as panels evolve you'll have to make sure to update your bed file target regions to encompass the genes. The bed files also serve as the means of defining target regions for coverage calculation as well, so always be sure to have your bed files ready when building your VarSeq projects 3. Can we subset the imported data to the panels so to limit the number of variants in the project? Yes, you just use the bed file to define your target regions at import and subset the total variants to those targeted regions. Super helpful in narrowing down the number of variants in WGS data
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