Abstract
Background:The recent development and enormous application of parallel sequencing technology inoncology have produced immense cell-specific genetic data. However, publicly available cell-specific genetic variants are not explained by well-established guidelines. Additionally, cell-specific variants interpretation and classification has remained a challenging task, and lacksstandardization. The Association for Molecular Pathology (AMP), American Society of ClinicalOncology (ASCO), and College of American Pathologists (CAP) published the first consensusguidelines for cell-specific variants cataloging and clinical interpretation.Results:We developed a new method that followed the consensus recommendations, and applied ourmethod on open source tumor-specific databases to produce clinically actionable cancersomatic variants (CACSV) dataset in integratable formats by most clinical analytical workflows.We evaluated our method with well-known classification algorithms, and found the new methodto be comparable and more adhering to the recent guidelines.Conclusion:CACSV is a step toward cell-specific genetic variants universal interpretation, readily adaptableby most clinical laboratories pipelines and can escalate somatic variants elucidation andclassification. CACSV is made free available (https://github.com/tsobahytm/CACSV/tree/main/dataset).
DMD
Open-access Variant Explorer (DOVE): A scalable, open-access, web-based tool to aid in clinical interpretation of genetic variants in the DMD
gene
