CNVnator: An approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing
Open accessAbstract
Copy number variation (CNV) in the genome is a complex phenomenon, and not completely understood. We have developed a method, CNVnator, for CNV discovery and genotyping from read-depth (RD) analysis of personal genome sequencing. Our method is based on combining the established mean-shift approach with additional refinements (multiple-bandwidth partitioning and GC correction) to broaden the range of discovered CNVs. We calibrated CNVnator using the extensive validation performed by the 1000 Genomes Project. Because of this, we could use CNVnator for CNV discovery and genotyping in a population and characterization of atypical CNVs, such as de novo and multi-allelic events. Overall, for CNVs accessible by RD, CNVnator has high sensitivity (86%–96%), low false-discovery rate (3%–20%), high genotyping accuracy (93%–95%), and high resolution in breakpoint discovery (<200 bp in 90% of cases with high sequencing coverage). Furthermore, CNVnator is complementary in a straightforward way to split-read and read-pair approaches: It misses CNVs created by retrotransposable elements, but more than half of the validated CNVs that it identifies are not detected by split-read or read-pair. By genotyping CNVs in the CEPH, Yoruba, and Chinese-Japanese populations, we estimated that at least 11% of all CNV loci involve complex, multi-allelic events, a considerably higher estimate than reported earlier. Moreover, among these events, we observed cases with allele distribution strongly deviating from Hardy-Weinberg equilibrium, possibly implying selection on certain complex loci. Finally, by combining discovery and genotyping, we identified six potential de novo CNVs in two family trios.
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Copy-number effects were addressed by deriving copy-number profiles from input sequencing, excluding regions with a strong deletion (<0.25) in any sample, and normalizing by copy number.
“To control for copy number changes, we first called copy number profiles from input sequencing data using CNVnator37. We then removed all regions where at least one sample had a strong deletion (<0.25), and normalized by copy number.”
From Insulator dysfunction and oncogene activation in IDH mutant gliomas (2016) · cites this paper as [37]
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- Authors
- Abyzov, A., Urban, A. E., Snyder, M., & Gerstein, M.
- Affiliations
- Yale University (US)
- Stanford Medicine (US)
- Stanford University (US)
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2011-02-07
- Volume
- 21
- Issue
- 6
- Pages
- 974-984
- ISSN
- 1088-9051 (ISSN-L)
- PMC
- PMC3106330
- OpenAlex
- W2150506261
- Cited by
- 1,658
- References
- 31
- Citations by year
- 2026: 80 · 2025: 111 · 2024: 132 · 2023: 130 · 2022: 148 · 2021: 180 · 2020: 172 · 2019: 141 · 2018: 136 · 2017: 78 · 2016: 74 · 2015: 93 · 2014: 77 · 2013: 52 · 2012: 38
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genome Research (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Yale University
- National Institutes of Health (1s10rr019895-01)
- National Center for Research Resources (RR 19895, S10_RR019895)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- copy number variation, mean shift, de novo CNVs, Hardy-Weinberg equilibrium, natural selection, family trios, population genomics, 1000 Genomes Project
- MeSH terms
- Algorithms, Base Composition, Ethnicity, Genotype, Humans, Sensitivity and Specificity, Software, Genome, Human, Sequence Analysis, DNA, Metagenomics, DNA Copy Number Variations
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