SG-ADVISER CNV: copy-number variant annotation and interpretation

Area of Science:

• Genomics
• Bioinformatics
• Medical Genetics

Background:

• Copy-number variants (CNVs) are linked to various diseases, including cancer, autism, schizophrenia, and developmental delay.
• Most clinically significant CNVs arise de novo, requiring robust interpretation of novel genetic events.

Purpose of the Study:

• To introduce the Scripps Genome ADVISER CNV annotation pipeline and Web server.
• To bridge the gap between CNV detection and clinical interpretation through in-depth annotation and functional prediction.

Main Methods:

• A Web server interface connected to a high-performance computing environment for CNV annotation calculations.
• A table-based user interface supporting diverse annotation-based variant filtration strategies and statistical analyses.

Main Results:

• Annotations include variant location, impact on gene coding regions, allele frequencies (including the Wellderly cohort), and overlap with databases like ClinVar, DGV, and DECIPHER.
• An "ADVISER score" provides summary variant classification based on ACMG guidelines.
• Demonstrated >90% sensitivity and specificity in detecting pathogenic CNVs.

Conclusions:

• Scripps Genome ADVISER CNV empowers users without bioinformatics expertise to analyze large CNV datasets.
• The tool is publicly available at http://genomics.scripps.edu/ADVISER/ for broader research and clinical application.