Performance of copy number variants detection based on whole-genome sequencing by DNBSEQ platforms
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RESEARCH ARTICLE
Open Access
Performance of copy number variants detection based on whole‑genome sequencing by DNBSEQ platforms Junhua Rao1†, Lihua Peng2†, Xinming Liang1†, Hui Jiang1, Chunyu Geng1, Xia Zhao1, Xin Liu2,3,6,7, Guangyi Fan3,7, Fang Chen1,2,5* and Feng Mu1,4* *Correspondence: [email protected]; [email protected] † Junhua Rao, Lihua Peng and Xinming Liang have contributed equally to this work 1 MGI, BGI-Shenzhen, Shenzhen 518083, China Full list of author information is available at the end of the article
Abstract Background: DNBSEQ™ platforms are new massively parallel sequencing (MPS) platforms that use DNA nanoball technology. Use of data generated from DNBSEQ™ platforms to detect single nucleotide variants (SNVs) and small insertions and deletions (indels) has proven to be quite effective, while the feasibility of copy number variants (CNVs) detection is unclear. Results: Here, we first benchmarked different CNV detection tools based on Illumina whole-genome sequencing (WGS) data of NA12878 and then assessed these tools in CNV detection based on DNBSEQ™ sequencing data from the same sample. When the same tool was used, the CNVs detected based on DNBSEQ™ and Illumina data were similar in quantity, length and distribution, while great differences existed within results from different tools and even based on data from a single platform. We further estimated the CNV detection power based on available CNV benchmarks of NA12878 and found similar precision and sensitivity between the DNBSEQ™ and Illumina platforms. We also found higher precision of CNVs shorter than 1 kbp based on DNBSEQ™ platforms than those based on Illumina platforms by using Pindel, DELLY and LUMPY. We carefully compared these two available benchmarks and found a large proportion of specific CNVs between them. Thus, we constructed a more complete CNV benchmark of NA12878 containing 3512 CNV regions. Conclusions: We assessed and benchmarked CNV detections based on WGS with DNBSEQ™ platforms and provide guidelines for future studies. Keywords: Copy number variant (CNV), Whole-genome sequencing (WGS), DNBSEQ, Benchmark
Background Large structural variations in the human genome, especially copy number variants (CNVs), have been widely studied, and their important roles in human diseases, such as autism [1–4], schizophrenia [5], Parkinson’s disease [6], Hirschsprung disease [7] and cancer [8], have been clearly demonstrated. In addition, different technologies and methods have been used or developed to detect CNVs. Initially, fluorescence in situ © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless
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