Congenica v2.5 is here. In this release, we:
- Made a significant step on our journey to intelligently, safely, and confidently Automate Variant Classification and reporting.
- Launched Congenica SpliceSiteFinder and SpliceAI, creating a suite of five solutions for confidently identifying variants impacting splice sites
- Improved your lab’s interpretive and workflow efficiency with multiple saveable Filter Presets
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Introducing Automated Classification of Known Variants
Recent studies point to recurring pathogenic and likely pathogenic variants being reported in a wide range of disorders, including:
- >70% of pathogenic variants in cardiomyopathy patients¹
- 35% of pathogenic variants in cardiac arrhythmia patients¹
- > 50% of de novo missense variants in neurodevelopmental patients²
Analyzing a 19,000-case subset of rare disease cases previously classified by Congenica, 20% (~4,000 cases) presented recurring variants. For some indications, the rates of recurring reported pathogenic and likely pathogenic variants is even higher.
However, genomic laboratories often have to reclassify previously analyzed variants when they recur. This compounds the challenges already presented by a limited workforce of trained clinical geneticists & analysts.
Our new Automated Classification of Known Variants is a game-changing advancement in our mission to increase the workflow efficiency, analytic yield, and confidence for genomic interpretations. Automated Classification of Known Variants enables you to upload known variants including pathogenicity, ACMG classifications, literature annotations, and interpretative comments, and use this data to rapidly report on cases presenting previously seen variants.
Congenica customers can now use their existing in-house datasets or their previously classified cases in Congenica to generate variant lists for automated classification. This is especially useful for labs that process high volumes of cases, work in targeted specialty areas, and perform research on new variants. Congenica customers can curate their own variant lists and interpretations based on in-house expertise or publicly available classifications, such as ClinVar. Our current Automation tool will benefit established labs analyzing genomic cases, as well as labs just starting out with clinical genomic interpretation.
Download our data sheet for more information about the necessity for automation in genomic interpretation and how Congenica Automation address these needs.
Offering Five Splicing Tools including SpliceAI & New Congenica Splice Site Finder (CSSF)
Variants in splicing sites have been implicated in a significant proportion of rare diseases. For example, splice variants were identified as causal in 4.9% diagnosed cases in the Deciphering Development Disorders study (Citation - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5955210/#SD2). With a wide variety of in silico splicing tools available today, analysts need a single platform with multiple high-quality tools to help identify the most possible splice site variants.
First, we built, validated, and launched Congenica Splice Site Finder (CSSF) to identify splice variants. CSSF is a documented, improved alternative to SpliceSiteFinder-like (SSFL), which is currently recommended in the Association for Clinical Genomic Science (ACGS) guidelines. CSSF builds on the original Splice Site Finder algorithm and SSFL implementation by using updated data from the GRCh38 reference genome to produce more comprehensive results. This means that Congenica complies with ACGS guidelines for variant interpretation, which recommend using MaxEntScan and SpliceSiteFinder in determining a variant’s likely pathogenicity.
Second, Congenica v2.5 includes SpliceAI, a tool recently shown to outperform MaxEntScan in assessing aberrant splicing in cases with rare disease variants (Citation https://www.biorxiv.org/content/10.1101/781088v1). SpliceAI is a machine learning algorithm that has only recently begun to enter use and customers on Congenica’s platform will be some of the first to have access to this improved resource for their variant interpretation.
SpliceAI and CSSF’s powerful new splicing variant solutions complement a full suite of splicing variant tools available in Congenica. You can leverage data from five unique, fully filterable splicing tools, including MaxEntScan, in the Congenica platform to predict the impact of synonymous variants, non-coding variants, and cryptic splicing variants in deep intronic regions. Congenica now provides both well-established and innovative evidence-based solutions for comprehensive interpretation of splicing variants.
Learn more about the efficacy and evidence for Congenica Splice Site Finder in our white paper.
Launching Saveable Filter Presets to Accelerate Analysis & Standardize Your Operating Procedures
We know that many labs prefer to set up standard sets of filters to create efficient, standardized workflows for variant interpretation. Previously, administrators and analysts were limited to a single set of default filters for each project.
With the new Filter Presets feature, project administrators can create and save multiple filter configurations, which users can flexibly apply within their Congenica projects. This increases efficiency and throughput by enabling analysts to rapidly explore multiple strategies for interpreting genetic variants. Filter presents can include settings for single nucleotide variants (SNVs), InDels, and Structural Variants (SVs) including Copy Number Variants (CNVs). For existing customers, your previously configured project filters will be automatically converted to a new default Filter Preset for a seamless upgrade.
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The upgrades in Congenica version 2.5 wouldn’t have been possible without the feedback and support from our partners and the genomic medicine community. We’re looking forward to further advances over the coming months, especially in Automated Variant Classification.
Subscribe to our newsletter for a webinar on this and future advancements in Automation later this summer.
Analyzing genomic data?
See how Congenica can help improve your workflow efficiency, yield and confidence in interpretation decisions.
References
- Dutch founder variants in cardiac disease - https://link.springer.com/article/10.1007/s12471-019-1250-5
- Neurodevelopmental disorders - https://europepmc.org/article/MED/29100083
