The following publications are possibly variants of this publication:
- Detection of common copy number variation with application to population clustering from next generation sequencing dataJunbo Duan, Ji-Gang Zhang, Hong-Wen Deng, Yu-Ping Wang. embc 2012: 1246-1249 [doi]
- Copy number variation detection using next generation sequencing read countsHeng Wang, Dan Nettleton, Kai Ying. bmcbi, 15:109, 2014. [doi]
- Copy number variation estimation from multiple next-generation sequencing samplesJunbo Duan, Ji-Gang Zhang, Hongbao Cao, Hong-Wen Deng, Yu-Ping Wang. bcb 2012: 555-557 [doi]
- Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectivesMin Zhao, Qingguo Wang, Quan Wang, Peilin Jia, Zhongming Zhao. bmcbi, 14(S-11), 2013. [doi]
- Population clustering based on copy number variations detected from next generation sequencing dataJunbo Duan, Ji-Gang Zhang, Mingxi Wan, Hong-Wen Deng, Yu-Ping Wang. jbcb, 12(4), 2014. [doi]
- BagGMM: Calling copy number variation by bagging multiple Gaussian mixture models from tumor and matched normal next-generation sequencing dataYaoyao Li, Junying Zhang, Xiguo Yuan. dsp, 88:90-100, 2019. [doi]
- SeqCNV: a novel method for identification of copy number variations in targeted next-generation sequencing dataYong Chen, Li Zhao, Yi Wang, Ming Cao, Violet Gelowani, Mingchu Xu, Smriti A. Agrawal, Yumei Li, Stephen P. Daiger, Richard A. Gibbs, Fei Wang, Rui Chen. bmcbi, 18(1), 2017. [doi]