CANVAR: A Tool for Clinical Annotation of Variants Using ClinVar Databases

Background: Genomic medicine has transformed clinical genetics by utilizing high-throughput sequencing technologies to analyze genetic variants associated with diseases. Accurate variant classification is crucial for diagnosis and treatment decisions, and various tools and software such as the Ion Reporter Software and the Illumina Nirvana Software often used in a clinical setting utilize information from the ClinVar database/archive to aid in variant interpretation. However, these existing annotation tools may lack access to the latest ClinVar data, necessitating manual variant inspection. Aims: To address this gap in developing a tool providing the latest ClinVar data for variant annotation in clinical and research settings. Materials and Methods: We introduce CANVAR, a Python-based script that efficiently annotates variants identified from next-generation sequencing in a clinical or research context, offering comprehensive information from the latest ClinVar database. Results: CANVAR provides accurate, up-to-date variant annotations, streamlining variant analysis. Discussion: The rise in genomic data requires accurate variant annotation for clinical decision-making. Misclassification poses risks, and current tools may not always access the latest data, challenging variant interpretation. Conclusion: CANVAR contributes to enhancing variant annotation by offering comprehensive information from the latest ClinVar database for genetic variants identified through next-generation sequencing.