ArticleBioinformatics (Oxford, England)2009
A geometric approach for classification and comparison of structural variants.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.
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77 citing papers in PubMed, 170 citations in OpenAlex.
- The sequence alignment problem: boundary conditions as the unifying principle.Briefings in bioinformatics · 2026Review
- Multi-tool copy number detection highlights common body size-associated variants in miniature pig breeds from different geographical regions.BMC genomics · 2025Article
- Benchmarking strategies for CNV calling from whole genome bisulfite data in humans.Computational and structural biotechnology journal · 2025Article
- VISTA: an integrated framework for structural variant discovery.Briefings in bioinformatics · 2024Article
- SVDSS: structural variation discovery in hard-to-call genomic regions using sample-specific strings from accurate long reads.Nature methods · 2023Article
- A comprehensive benchmarking of WGS-based deletion structural variant callers.Briefings in bioinformatics · 2022Article
- CNV-MEANN: A Neural Network and Mind Evolutionary Algorithm-Based Detection of Copy Number Variations From Next-Generation Sequencing Data.Frontiers in genetics · 2021Article
- SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads.Frontiers in genetics · 2021Article
- VALOR2: characterization of large-scale structural variants using linked-reads.Genome biology · 2020Article
- Review: Understanding Rare Genetic Diseases in Low Resource Regions Like Jammu and Kashmir - India.Frontiers in genetics · 2020Review
- Novel somatic alterations underlie Chinese papillary thyroid carcinoma.Cancer biomarkers : section A of Disease markers · 2020Article
- Discovery of tandem and interspersed segmental duplications using high-throughput sequencing.Bioinformatics (Oxford, England) · 2019Article
- Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine.Science China. Life sciences · 2019Review
- Predicting Local Inversions Using Rectangle Clustering and Representative Rectangle Prediction.IEEE transactions on nanobioscience · 2019Article
- Structural variants in 3000 rice genomes.Genome research · 2019Article
- MSeq-CNV: accurate detection of Copy Number Variation from Sequencing of Multiple samples.Scientific reports · 2018Article
- Identifying structural variants using linked-read sequencing data.Bioinformatics (Oxford, England) · 2018Article
- ReadXplorer 2-detailed read mapping analysis and visualization from one single source.Bioinformatics (Oxford, England) · 2016Article
- Characterization of the Poplar Pan-Genome by Genome-Wide Identification of Structural Variation.Molecular biology and evolution · 2016Article
- SV-Bay: structural variant detection in cancer genomes using a Bayesian approach with correction for GC-content and read mappability.Bioinformatics (Oxford, England) · 2016Article
17 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationStructural variants, including duplications, insertions, deletions and inversions of large blocks of DNA sequence, are an important contributor to human genome variation. Measuring structural variants in a genome sequence is typically more challenging than measuring single nucleotide changes. Current approaches for structural variant identification, including paired-end DNA sequencing/mapping and array comparative genomic hybridization (aCGH), do not identify the boundaries of variants precisely. Consequently, most reported human structural variants are poorly defined and not readily compared across different studies and measurement techniques.
resultsWe introduce Geometric Analysis of Structural Variants (GASV), a geometric approach for identification, classification and comparison of structural variants. This approach represents the uncertainty in measurement of a structural variant as a polygon in the plane, and identifies measurements supporting the same variant by computing intersections of polygons. We derive a computational geometry algorithm to efficiently identify all such intersections. We apply GASV to sequencing data from nine individual human genomes and several cancer genomes. We obtain better localization of the boundaries of structural variants, distinguish genetic from putative somatic structural variants in cancer genomes, and integrate aCGH and paired-end sequencing measurements of structural variants. This work presents the first general framework for comparing structural variants across multiple samples and measurement techniques, and will be useful for studies of both genetic structural variants and somatic rearrangements in cancer. AVAILABILITY: http://cs.brown.edu/people/braphael/software.html .
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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.