ArticleScientific reports2021
Benchmarking germline CNV calling tools from exome sequencing data.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- Pangenomes aid accurate detection of large insertions and deletions from targeted sequencing: the case of cardiomyopathies.Genome medicine · 2026Article
- Global patterns of mutational profiles in biliary tract cancer.Journal of hepatology · 2026Article
- Computational strategies for copy number variation detection, disease association, and beyond.Genome biology · 2026Review
- Accurate and cost-effective workflow integrating trio pooled-WES for novel gene discovery in neurodevelopmental disorders.European journal of human genetics : EJHG · 2026Article
- High Concordance of Copy Number Variants Detected by Chromosomal Microarray and Exome Sequencing in Clinical Diagnostics.Clinical genetics · 2026Article
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- Genetic variations associated with immediate hypersensitivity reactions to iodinated contrast media: A whole exome sequencing study.PloS one · 2026Article
- Uncovering minimal pathways in melanoma initiation.Nature communications · 2025Article
- Clinical and analytical validation of a combined RNA and DNA exome assay across a large tumor cohort.Communications medicine · 2025Article
- Combining chromosome conformation capture and exome sequencing for simultaneous detection of structural and single-nucleotide variants.Genome medicine · 2025Article
- Copy number normalization distinguishes differential signals driven by copy number differences in ATAC-seq and ChIP-seq.BMC genomics · 2025Article
- Navigating Genetic Testing in Nephrology: Options and Decision-Making Strategies.Kidney international reports · 2025Review
- Genome-wide association testing beyond SNPs.Nature reviews. Genetics · 2025Review
- Benchmarking of germline copy number variant callers from whole genome sequencing data for clinical applications.Bioinformatics advances · 2025Article
- Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses.NPJ genomic medicine · 2024Article
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- Biallelic structural variants in three patients with ERCC8-related Cockayne syndrome and a potential pitfall of copy number variation analysis.Scientific reports · 2024Article
- Limited Added Diagnostic Value of Whole Genome Sequencing in Genetic Testing of Inherited Retinal Diseases in a Swiss Patient Cohort.International journal of molecular sciences · 2024Article
- A method to comprehensively identify germline SNVs, INDELs and CNVs from whole exome sequencing data of BRCA1/2 negative breast cancer patients.NAR genomics and bioinformatics · 2024Article
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6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Whole-exome sequencing is an attractive alternative to microarray analysis because of the low cost and potential ability to detect copy number variations (CNV) of various sizes (from 1-2 exons to several Mb). Previous comparison of the most popular CNV calling tools showed a high portion of false-positive calls. Moreover, due to a lack of a gold standard CNV set, the results are limited and incomparable. Here, we aimed to perform a comprehensive analysis of tools capable of germline CNV calling available at the moment using a single CNV standard and reference sample set. Compiling variants from previous studies with Bayesian estimation approach, we constructed an internal standard for NA12878 sample (pilot National Institute of Standards and Technology Reference Material) including 110,050 CNV or non-CNV exons. The standard was used to evaluate the performance of 16 germline CNV calling tools on the NA12878 sample and 10 correlated exomes as a reference set with respect to length distribution, concordance, and efficiency. Each algorithm had a certain range of detected lengths and showed low concordance with other tools. Most tools are focused on detection of a limited number of CNVs one to seven exons long with a false-positive rate below 50%. EXCAVATOR2, exomeCopy, and FishingCNV focused on detection of a wide range of variations but showed low precision. Upon unified comparison, the tools were not equivalent. The analysis performed allows choosing algorithms or ensembles of algorithms most suitable for a specific goal, e.g. population studies or medical genetics.
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