SavvyCNV: Genome-wide CNV calling from off-target reads

被引:15
|
作者
Laver, Thomas W. [1 ]
De Franco, Elisa [1 ]
Johnson, Matthew B. [1 ]
Patel, Kashyap A. [1 ]
Ellard, Sian [1 ]
Weedon, Michael N. [1 ]
Flanagan, Sarah E. [1 ]
Wakeling, Matthew N. [1 ]
机构
[1] Univ Exeter, Inst Biomed & Clin Sci, Exeter, England
基金
英国医学研究理事会;
关键词
NEONATAL DIABETES-MELLITUS; COPY NUMBER VARIATIONS; GENE; MUTATIONS; SPECTRUM;
D O I
10.1371/journal.pcbi.1009940
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Identifying copy number variants (CNVs) can provide diagnoses to patients and provide important biological insights into human health and disease. Current exome and targeted sequencing approaches cannot detect clinically and biologically-relevant CNVs outside their target area. We present SavvyCNV, a tool which uses off-target read data from exome and targeted sequencing data to call germline CNVs genome-wide. Up to 70% of sequencing reads from exome and targeted sequencing fall outside the targeted regions. We have developed a new tool, SavvyCNV, to exploit this 'free data' to call CNVs across the genome. We benchmarked SavvyCNV against five state-of-the-art CNV callers using truth sets generated from genome sequencing data and Multiplex Ligation-dependent Probe Amplification assays. SavvyCNV called CNVs with high precision and recall, outperforming the five other tools at calling CNVs genome-wide, using off-target or on-target reads from targeted panel and exome sequencing. We then applied SavvyCNV to clinical samples sequenced using a targeted panel and were able to call previously undetected clinically-relevant CNVs, highlighting the utility of this tool within the diagnostic setting. SavvyCNV outperforms existing tools for calling CNVs from off-target reads. It can call CNVs genome-wide from targeted panel and exome data, increasing the utility and diagnostic yield of these tests. SavvyCNV is freely available at https://github.com/rdemolgen/SavvySuite. Author summary We have created SavvyCNV, a new tool for calling genetic variants. Large regions of the genome can be deleted or duplicated-these variants can have important consequences, for example causing a patient's genetic disease. However, many standard genetic tests only target a small fraction of the genome and will miss variants outside of these regions. Therefore, we developed a tool to exploit sequencing data which falls outside of these regions (due to flaws in the targeting process) to call large deletions and duplications. This allows large deletions and duplications to be detected anywhere in the genome. Researchers and diagnostic laboratories can use this tool to discover more genetic variants by reanalysing their sequencing data.
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页数:16
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