Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives
By Min Zhao, Qingguo Wang, Quan Wang, P. Jia, Zhongming Zhao. BMC Bioinformatics, 2013
529 citations recorded by the source corpus.
Copy number variation (CNV) is a prevalent form of critical genetic variation that leads to an abnormal number of copies of large genomic regions in a cell. Microarray-based comparative genome hybridization (arrayCGH) or genotyping arrays have been standard technologies to detect large regions subject to copy number changes in genomes until most recently high-resolution sequence data can be analyzed by next-generation sequencing (NGS). During the last several years, NGS-based analysis has been widely applied to identify CNVs in both healthy and diseased individuals. Correspondingly, the strong demand for NGS-based CNV analyses has fuelled development of numerous computational methods and tools for CNV detection. In this article, we review the recent advances in computational methods pertaining to CNV detection using whole genome and whole exome sequencing data. Additionally, we discuss their strengths and weaknesses and suggest directions for future development.
Subfields: Cancer Research, Genetics
View Paper: https://www.semanticscholar.org/paper/1da1ecb0dd4976ec3fd9f5207520a21f9f039c6e
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Citations in the corpus
- Design and Analysis of Single-Cell Sequencing Experiments. (2015, methodology): “The numerous published methods for CNV detection using next-generation sequencing were discussed in a recent review (Zhao et al., 2013).”
- CNVkit: Genome-Wide Copy Number Detection and Visualization from Targeted DNA Sequencing (2016, methodology): “More recently, methods have been developed to obtain copy number information from whole-genome sequencing data ([3]; reviewed by [4]).”
- Genomic variant annotation and prioritization with ANNOVAR and wANNOVAR (2015, background): “…(such as BWA 2 and Bowtie 3 ), to assemble new genomes 4 (such as FERMI 5 , Abyss 6 and SoapDenovo 7 ), to perform data quality control 8 and to call single-nucleotide variants (SNVs) 9 (such as Genome Analysis Toolkit (GATK) 10 ) or structural variants (SVs) 11 (such as CNVnator 12 and ERDS 13 ).”