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Updated: Jun 4, 2025
09:45
Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
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CNVizard-a lightweight streamlit application for an interactive analysis of copy number variants
Jeremias Krause1, Carlos Classen2, Daniela Dey2
1Medical Faculty, Institute for Human Genetics and Genomic Medicine, Uniklinik RWTH Aachen, Pauwelsstrasse 30, 52074, Aachen, North-Rhine-Westphalia, Germany. jerkrause@ukaachen.de.
BMC Bioinformatics
|December 17, 2024
Summary
CNVizard is a new tool for visualizing copy number variation (CNV) data from sequencing. It streamlines analysis and offers interactive visualizations, improving genetic testing and research.
Area of Science:
- Genomics
- Bioinformatics
Background:
- Copy number variations (CNVs) analysis is crucial in clinical practice and genetic research using next-generation sequencing.
- Current open-source tools often lack comprehensive annotation, visualization capabilities, or the ability to detect single exon CNVs.
- Existing tools provide static data formats, necessitating additional efforts for visualization and formatting.
Purpose of the Study:
- To present CNVizard, an interactive Streamlit application for comprehensive visualization of CNVkit data.
- To enable streamlined analysis and visualization of CNV and structural variant (SV) data from various callers.
Main Methods:
- Development of CNVizard, an interactive web application using Streamlit.
- Integration of CNVizard with the CNVand pipeline for annotation and visualization of VCF files.
- Support for analyzing both short-read and long-read sequencing data.
Main Results:
- CNVizard provides comprehensive and interactive visualization of CNV data.
- The combination of CNVizard and CNVand allows annotation and visualization of CNV/SV VCF files from any caller.
- The tool offers an intuitive web app experience for CNV data analysis.
Conclusions:
- CNVizard and CNVand together facilitate streamlined analysis of sequencing data for CNVs and SVs.
- The integrated solution provides an intuitive, interactive web application for CNV data visualization.
- This approach enhances the utility of CNV analysis in genetic research and clinical applications.
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