Computational study demonstrates efficient detection of copy number variations in amplicon sequencing data, indicating improved diagnosis for inherited diseases and cancer.
Molecular diagnosis is an essential step of patient care. An increasing number of Copy Number Variations (CNVs) have been identified that are involved in inherited and somatic diseases. However, there are few existing tools to identify them among amplicon sequencing data generated by Next Generation Sequencing (NGS). We present here a new tool, CovCopCan, that allows the rapid and easy detection of CNVs in inherited diseases, as well as somatic data of patients with cancer, even with a low ratio of cancer cells to healthy cells. This tool could be very useful for molecular geneticists to rapidly identify CNVs in an interactive and user-friendly way.
No takes yet. Share an insight, caveat, or question.
Derouault et al. (2020) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: