Abstract

BackgroundDNBSEQ™ 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.ResultsHere, 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.ConclusionsWe assessed and benchmarked CNV detections based on WGS with DNBSEQ™ platforms and provide guidelines for future studies.

Highlights

  • DNBSEQTM platforms are new massively parallel sequencing (MPS) platforms that use DNA nanoball technology

  • Detecting Copy number variant (CNV) based on Illumina whole-genome sequencing (WGS) data with different tools Using various CNV detection tools for Illumina WGS data, we selected five representative tools (BreakDancer [14], CNVnator [22], Pindel [23], DELLY [24] and LUMPY [25]) that are commonly used and were recently updated for detecting CNVs based on a single WGS sample

  • We found that CNVs detected by CNVnator were more enriched in exonic regions compared to those identified using the other four tools (Additional file 1: Table S3 and Additional file 2: Fig. S3), while the CNVs detected by Pindel were more enriched in intronic regions

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Summary

Introduction

DNBSEQTM platforms are new massively parallel sequencing (MPS) platforms that use DNA nanoball technology. With improvements in sequencing technologies, whole-genome sequencing (WGS) and whole-exome sequencing (WES) became more widely used in detecting CNVs without the limitations of specified target regions associated with hybridization or arrays. Several tools for CNV detection were developed based on WES [11] or WGS [12, 13] data by Illumina platforms. Within these tools, there are five main strategies considered: (1) read pair (RP), (2) read depth (RD), (3) split read (SR), (4) de novo assembly (AS), and (5) combination of approaches (CA). BreakDancer [14] applies the RP strategy and is suitable for CNV detection in a single sample, while HYDRA [15], based on the CA strategy, is suited for multiple samples, and CNAnorm [16], based on the RD strategy, is designed for case–control studies

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