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Updated: Jul 12, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
Computational strategies for copy number variation detection, disease association, and beyond
Amir Hossein Saeidian1,2, Hani Sabaie3, Mahdi Akbarzadeh4
1Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Abstract:
Copy number variations (CNVs) are key structural variations that contribute to human genetic diversity, evolution, and disease susceptibility. Advances in sequencing technologies and computational methods have improved CNV detection, yet association studies remain challenged by methodological limitations and a lack of standardisation. This review provides an overview of computational strategies for germline CNV detection and disease association. We highlight the value of CNV analysis for uncovering genetic contributions to complex traits and disease risk and outline an analysis workflow including key benchmarking methods. We also discuss current challenges and future directions for advancing CNV detection and association analysis.
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