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Overview Congenica 3.3 improves genomic data analysis and automates workflow
Congenica 3.3 improves genomic data analysis and automates workflow
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Congenica 3.3 improves genomic data analysis and automates workflow

2/1/2022    |    0 min read

Data interpretation is by far the most time-consuming and resource-intensive step of the NGS workflow. Any time savings that can be found have a significant impact on overall costs and sample throughput.


The release of Congenica v3.3, the first of our product releases for 2022, enables our customers to benefit from the use of Congenica’s award winning artificial intelligence (AI) combined with other features of the Congenica clinical decision support platform to enable rapid analysis, interpretation and reporting of complex genomic data to aid the diagnosis of genetic diseases.

 

Features of Congenica v3.3

  • Variant pathogenicity predictions and prioritization using Congenica’s award-winning Artificial Intelligence (AI), which delivers:
    • 4 x faster analyses
    • Increased diagnostic yield and reduced time spent in analysis, effectively prioritizing the causal variant 85% of the time
    • Justification and confidence scores for every prediction
  • New functionality with gnomAD Gene Constraint scores providing:
    • New ways to identify relevant variants, increasing the chance of diagnosis
    • 2 x faster interpretation of Constraint-related ACMG criteria
  • Improved functionality in gnomAD SNV AF data for ref 3
  • Usability improvements, including
    • Integrated log2ratio browser for SV’
    • Capability to add variants to an automation ‘curated variant list’ during interpretation workflow, reducing the need to classify previously seen variants.

Congenica’s clinical decision support platform is backed by ISO 13485, ISO 27001 and CE Marked In Vitro Diagnostic certifications and includes automated, exportable audit logs so clinicians can be confident in the quality of their results. In addition, Congenica can be deployed anywhere in the world, on multiple types of infrastructure – from a local on-premise server to a global cloud instance.

 

An accurate model for predicting causal variants Congenica AI has been demonstrated to Have 95.5% accuracy in predicting the pathogenicity of Clinvar 3- and 4-star variants Rank the causal variant in the to

 

This latest release forms part of our ongoing commitment to delivering customers around the world with the best scalable software for end-to-end genomic analysis, supported by our professional and Clinical Consulting Services team.


To find out how the latest version of our software can help you, contact us today for a demo. Demo online at www.congenica.com/demo


Demo Congenica AI to see the benefits
An accurate model for predicting causal variants Congenica AI has been demonstrated to Have 95.5% accuracy in predicting the pathogenicity of Clinvar 3- and 4-star variants Rank the causal variant in th (1)