CNVizard: a lightweight streamlit application for an interactive analysis of copy number variants

Methods to call, analyze and visualize copy number variations (CNVs) from massive parallel sequencing data have been widely adopted in clinical practice and genetic research. To enable a streamlined analysis of CNV data, comprehensive annotation and good visualization are indispensable. The ability to detect single exon CNVs is another important feature for genetic testing. Nonetheless, most available open-source tools come with limitations in at least one of these areas. One drawback is that available tools deliver data in an unstructured and static format which requires subsequent visualization and formatting efforts. Here we present CNVizard, a lightweight streamlit app which requires minimal computational knowledge, and which is compatible with widely used CNV processing tools (CNVkit and AnnotSV). CNVizard can process short- and long-read sequencing data and provides an intuitive webapp-like experience enabling an interactive visualization of CNV data.