The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Sensitive and accurate detection of copy number variants using read depth of coverage
Open accessAbstract
Methods for the direct detection of copy number variation (CNV) genome-wide have become effective instruments for identifying genetic risk factors for disease. The application of next-generation sequencing platforms to genetic studies promises to improve sensitivity to detect CNVs as well as inversions, indels, and SNPs. New computational approaches are needed to systematically detect these variants from genome sequence data. Existing sequence-based approaches for CNV detection are primarily based on paired-end read mapping (PEM) as reported previously by Tuzun et al. and Korbel et al. Due to limitations of the PEM approach, some classes of CNVs are difficult to ascertain, including large insertions and variants located within complex genomic regions. To overcome these limitations, we developed a method for CNV detection using read depth of coverage. Event-wise testing (EWT) is a method based on significance testing. In contrast to standard segmentation algorithms that typically operate by performing likelihood evaluation for every point in the genome, EWT works on intervals of data points, rapidly searching for specific classes of events. Overall false-positive rate is controlled by testing the significance of each possible event and adjusting for multiple testing. Deletions and duplications detected in an individual genome by EWT are examined across multiple genomes to identify polymorphism between individuals. We estimated error rates using simulations based on real data, and we applied EWT to the analysis of chromosome 1 from paired-end shotgun sequence data (30×) on five individuals. Our results suggest that analysis of read depth is an effective approach for the detection of CNVs, and it captures structural variants that are refractory to established PEM-based methods.
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Cites
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Self-citationStructural Variation of Chromosomes in Autism Spectrum Disorder
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Self-citation
Cited by
VarScan 2: Somatic mutation and copy number alteration discovery in cancer by exome sequencing
Koboldt, D. C., Zhang, Q., Larson, D. E., Shen, D., McLellan, M. D., Lin, L., Miller, C. A., Mardis, E. R., Ding, L., & Wilson, R. K. (2012) · Genome Research · doi:10.1101/gr.129684.111 · Cited by 4,905
Tumour evolution inferred by single-cell sequencing
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CNVkit: Genome-Wide Copy Number Detection and Visualization from Targeted DNA Sequencing
Talevich, E., Shain, A. H., Botton, T., & Bastian, B. C. (2016) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004873 · Cited by 2,094
Genome structural variation discovery and genotyping
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Abyzov, A., Urban, A. E., Snyder, M., & Gerstein, M. (2011) · Genome Research · doi:10.1101/gr.114876.110 · Cited by 1,658
Metadata
- Authors
- Yoon, S., Xuan, Z., Makarov, V., Ye, K., & Sebat, J.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2009-08-05
- Volume
- 19
- Issue
- 9
- Pages
- 1586-1592
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2137779717
- Cited by
- 627
- References
- 12
- Type
- posted content
- Language
- en
- Open access
- hybrid
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