Evidence map›Paper›PMID 30565893›Full record

ArticleMolecular genetics & genomic medicine2019

Evaluation of copy number variant detection from panel-based next-generation sequencing data.

Ruen Yao, Tingting Yu, Yanrong Qing, Jian Wang, Yiping Shen

Abstract read
In one paragraph

Article in Molecular genetics & genomic medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

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  8. Comprehensive Molecular Analysis ofDiagnostics (Basel, Switzerland) · 2021
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  18. Observational
  19. SMN1 gene copy number analysis for spinal muscular atrophy (SMA) in a Turkish cohort by CODE-SEQ technology, an integrated solution for detection of SMN1 and SMN2 copy numbers and the "2+0" genotype.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2020
    Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ruen YaoDepartment of Medical Genetics and Molecular Diagnostic Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0003-4147-5291
Tingting YuDepartment of Medical Genetics and Molecular Diagnostic Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yanrong QingDepartment of Medical Genetics and Molecular Diagnostic Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jian WangDepartment of Medical Genetics and Molecular Diagnostic Laboratory, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yiping ShenDivision of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTargeted gene capture and next-generation sequencing (NGS) has been widely utilized as a robust and cost-effective approach for detecting small variants among a group of disease genes. Copy number variations (CNV) can also be inferred from the read-depth information but the accuracy of CNVs called from panel-based NGS data has not been well evaluated.

methodsSequencing data were acquired from patients underwent routine clinical targeted panel sequencing testing. Pathogenic CNVs detected from targeted panel sequencing data were evaluated using CNVs generated by two clinical accepted platforms, namely chromosome microarray analysis (CMA) and multiple ligation-dependent probe amplification (MLPA) as benchmarks. CNVkit was used in our study to call CNVs from sequencing data using read-depth information. CMA and MLPA tests were used to confirm and further assess the size and breakpoints of CNVs.

resultsThe size of CNVs detected using panel-based NGS data are over 300 kb. The sizes of CNVs detected are slightly larger (102.3% on average) using the NGS platform than using the CMA platform, and the size accuracy improved as the size of variants increases. The breakpoints of CNVs detected using NGS data are quite close (within 2.3% of margin) to the breakpoints detected by CMA. CNVs on sex chromosomes, however, are less concordant between NGS and CMA platforms.

conclusionCopy number variations covering adequate exons on autosomes can be accurately detected using targeted panel sequencing data as using CMA. CNVs detected from sex chromosomes need further evaluation and validation. Except for exon-level deletion/duplication and CNV on sex chromosome, our data support the use of panel-based NGS data for routine clinical detection of pathogenic CNVs.

Indexed as

DNA Copy Number VariationsGenetic TestingHigh-Throughput Nucleotide SequencingHumansMuscular Dystrophy, DuchenneSensitivity and SpecificitySequence Analysis, DNAchromosomal microarray analysiscopy number variationnext-generation sequencing

Identifiers

PMID30565893
PMCPMC6382442

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.