ArticleBriefings in bioinformatics2022
A comprehensive benchmarking of WGS-based deletion structural variant callers.
Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 28 citations in OpenAlex.
- Comprehensive Genomic Analysis in Hereditary Adrenal and Extra-Adrenal Paragangliomas.Endocrine pathology · 2026Article
- Article
- Decoding structural birth defects through genomic landscapes: Innovative frameworks for diagnosis (Review).International journal of molecular medicine · 2026Review
- Personalizing DNA Cancer Vaccines.Journal of personalized medicine · 2025Review
- Comparisons of performances of structural variants detection algorithms in solitary or combination strategy.PloS one · 2025Article
- SurVIndel2: improving copy number variant calling from next-generation sequencing using hidden split reads.Nature communications · 2024Article
- Molecular targets and strategies in the development of nucleic acid cancer vaccines: from shared to personalized antigens.Journal of biomedical science · 2024Review
- A large structural variant collection in Holstein cattle and associated database for variant discovery, characterization, and application.BMC genomics · 2024Article
- Whole genome sequencing increases the diagnostic rate in Charcot-Marie-Tooth disease.Brain : a journal of neurology · 2024Article
- Investigating copy number variants in schizophrenia pedigrees using a new consensus pipeline called PECAN.Scientific reports · 2024Article
- VISTA: an integrated framework for structural variant discovery.Briefings in bioinformatics · 2024Article
- Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges.Briefings in bioinformatics · 2024Review
- A graph clustering algorithm for detection and genotyping of structural variants from long reads.GigaScience · 2024Article
- A multi-platform reference for somatic structural variation detection.Cell genomics · 2022Article
- Dysgu: efficient structural variant calling using short or long reads.Nucleic acids research · 2022Article
- From molecules to genomic variations: Accelerating genome analysis via intelligent algorithms and architectures.Computational and structural biotechnology journal · 2022Review
- Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases.Genome medicine · 2021Article
- Familial Narcolepsy in Dogo Argentino Dogs Is Caused by a Tandem Duplication Mutation in HCRTR2.Journal of veterinary internal medicineArticle
Corrections and comments
- Erratum issued
Authors and funding
20 authors at 5 institutions in 4 countries.
Funding
Abstract
Advances in whole-genome sequencing (WGS) promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from WGS data presents a substantial number of challenges and a plethora of SV detection methods have been developed. Currently, evidence that investigators can use to select appropriate SV detection tools is lacking. In this article, we have evaluated the performance of SV detection tools on mouse and human WGS data using a comprehensive polymerase chain reaction-confirmed gold standard set of SVs and the genome-in-a-bottle variant set, respectively. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of the SV detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance as the SV detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low- and ultralow-pass sequencing data as well as for different deletion length categories.
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What Socratic holds
Registered trials
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 Socratic graph.