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Cardio Classifier uses the American College of Medical Genenics and Genomics (ACMG) rules for variant interpretation to classify variants associated with inherited cardiac conditions.
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This web app providess a suite of tools to support the use of allele frequency information for the assessment of rare genetic variants in Mendelian disease.
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Assessing gene and variant pathogenicity in cardiomyopathies (HCM, DCM & ARVC) by comparing large
clinical cohorts with ExAC population data.
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Microsite describing the full transcript and exon structure of titin (TTN) and the truncating variants in this
gene which are associated with Dilated Cardiomyopathy.
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CardioBoost uses an adaptive boosting machine learning algorithm to discriminate benign and pathogenic variants in genes associated with inherited cardiac conditions.
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Paralogue Annotation App utilizes information from evolutionarily related proteins, specifically paralogues, to help inform the clinical significance of missense variants associated with human diseases. |
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An integrated toolset for the analysis of de novo (sporadic) genetic sequence variants.
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Visit Cardiovascular Genetics and Genomics Research Group (CGGR) website to find out more about our interesting research projects and meet group members. |
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APPRAISE is a Bayesian logistic regression model
that integrates multiple lines of evidence to evaluate the probability that a rare variant is the cause of Long QT syndrome.
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Determine the pathogenicity of novel variants found in patients with inherited arrhythmias by assessing
paralogue annotation.
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Homologous Missense Constraint measures genetic intolerance information to help inform the clinical significance of missense variants associated with human diseases.
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A tool to support the application of the American College of Medical Genetics and Genomics (ACMG) PS4 criterion, which relates to the prevalence of a variant in affected individuals compared to controls. |