Rapid, Reliable, and Interpretable Copy Number Variant Curation Visualizations for Diagnostic Settings with SeeNV

Area of Science:

• Genomics
• Bioinformatics
• Clinical Diagnostics

Background:

• Copy number variants (CNVs) are significant genomic alterations linked to various diseases.
• Accurate CNV identification is challenging with whole-exome sequencing (WES) due to technical noise.
• Manual curation of CNV calls is time-consuming and prone to errors.

Purpose of the Study:

• To introduce SeeNV, a command-line tool designed to streamline manual curation of CNVs.
• To improve the efficiency and accuracy of CNV assessment in clinical settings.
• To facilitate large-scale CNV analysis using WES data.

Main Methods:

• SeeNV generates static infographics for each CNV.
• Infographics include sample/cohort sequencing coverage and population frequency data.
• The tool was validated using publicly available WES and whole-genome sequencing data.

Main Results:

• SeeNV enables rapid CNV curation, averaging 4.3 seconds per call.
• Achieved high analytical sensitivity (0.95 recall) and good positive predictive value (0.74 precision).
• The tool aids in precise assessment of CNV calls.

Conclusions:

• SeeNV effectively addresses the challenges of manual CNV curation from WES data.
• The tool enhances the speed and reliability of CNV analysis in diagnostic laboratories.
• SeeNV is freely available, promoting wider adoption in genomic research and diagnostics.