ArticleGenome biology2019
Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing.
Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 295 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
295 citing papers in PubMed.
- Structural Variants in the Human Genome Associated With Gut Microbiome and Blood Metabolic Traits With Potential Causal Links.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Detecting pathogenic structural variation in families with undiagnosed rare disease in a national genome project.European journal of human genetics : EJHG · 2026Article
- Diagnostic discovery of structural variants causing foveal hypoplasia using SVRare and long-read nanopore sequencing.European journal of human genetics : EJHG · 2026Article
- Structural Variant benchmarking frameworks: Parameterization, matching logic, and evaluation assumptions presented through HG002 and NA12878.PLoS computational biology · 2026Article
- Comprehensive evaluation of structural variation detection for germline and somatic analysis with long-read sequencing data.Briefings in bioinformatics · 2026Article
- A pangenome framework uncovers the role of deletions in repeated evolution of cave-derived traits.Genome research · 2026Article
- Integrated Analysis of SNPs and Structural Variations via High-depth Whole-genome Sequencing Reveals the Genetic Architecture and Optimizes Genomic Prediction in Chickens.Poultry science · 2026Article
- A Personalized Haplotype-Resolved Near-Gapless Genome Framework for Somatic Variant Discovery in Hepatocellular Carcinoma.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Computational strategies for copy number variation detection, disease association, and beyond.Genome biology · 2026Review
- Benchmarking of real-time, field-deployable whole-genome sequencing ofMicrobial genomics · 2026Article
- The importance and clinical utility of reanalysis of exome and genome sequencing data.Kidney research and clinical practice · 2026Article
- Article
- From fragments to full pictures: how long-read sequencing platforms are revolutionizing oncology research.Molecular biology reports · 2026Review
- Fifteen Years of the Genome Analysis Toolkit as the De Facto Standard in Short-Read Variant Calling.International journal of molecular sciences · 2026Review
- NanoVar: a comprehensive workflow for structural variant detection to uncover the genome's hidden patterns.Nature protocols · 2026Review
- Integrating Long-Read Structural Variant Analysis with single-nucleus RNA-seq to Elucidate Gene Expression Effects in Disease.bioRxiv : the preprint server for biology · 2026Article
- Somatic structural variants drive upper tract urothelial carcinoma muscle invasiveness via activation of TPX2 transcription.EBioMedicine · 2026Article
- De Novo Assembly of Eight Commercial Crossbred Pig Genomes Provides Insights into the Potential Functional Impact of Structural Variation Hotspots.Biomolecules · 2026Article
- Multiplatform comparisons and annotation of structural variants highlight the utility of the T2T reference genome in human diagnostics.GigaScience · 2026Article
- Article
235 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundStructural variations (SVs) or copy number variations (CNVs) greatly impact the functions of the genes encoded in the genome and are responsible for diverse human diseases. Although a number of existing SV detection algorithms can detect many types of SVs using whole genome sequencing (WGS) data, no single algorithm can call every type of SVs with high precision and high recall.
resultsWe comprehensively evaluate the performance of 69 existing SV detection algorithms using multiple simulated and real WGS datasets. The results highlight a subset of algorithms that accurately call SVs depending on specific types and size ranges of the SVs and that accurately determine breakpoints, sizes, and genotypes of the SVs. We enumerate potential good algorithms for each SV category, among which GRIDSS, Lumpy, SVseq2, SoftSV, Manta, and Wham are better algorithms in deletion or duplication categories. To improve the accuracy of SV calling, we systematically evaluate the accuracy of overlapping calls between possible combinations of algorithms for every type and size range of SVs. The results demonstrate that both the precision and recall for overlapping calls vary depending on the combinations of specific algorithms rather than the combinations of methods used in the algorithms.
conclusionThese results suggest that careful selection of the algorithms for each type and size range of SVs is required for accurate calling of SVs. The selection of specific pairs of algorithms for overlapping calls promises to effectively improve the SV detection accuracy.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.