Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives
作者： Min Zhao , Qingguo Wang , Quan Wang , Peilin Jia , Zhongming Zhao
DOI: 10.1186/1471-2105-14-S11-S1
关键词:
摘要: Copy number variation (CNV) is a prevalent form of critical genetic that leads to an abnormal copies large genomic regions in cell. Microarray-based comparative genome hybridization (arrayCGH) or genotyping arrays have been standard technologies detect subject copy changes 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 widely applied identify CNVs both healthy and diseased individuals. Correspondingly, strong demand for CNV analyses fuelled development numerous computational methods tools detection. In this article, we review recent advances pertaining detection using whole exome data. Additionally, discuss their strengths weaknesses suggest directions future development.
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