ArticleGenome biology2022
Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies.
Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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33 citing papers in PubMed, 42 citations in OpenAlex.
- SVPG: a pangenome-based structural variant detection approach and rapid augmentation of pangenome graphs with new samples.Nature methods · 2026Article
- Comprehensive evaluation of structural variation detection for germline and somatic analysis with long-read sequencing data.Briefings in bioinformatics · 2026Article
- Genomic Variability of the HCT116 Cell Line Identified Using Oxford Nanopore Sequencing.International journal of molecular sciences · 2026Article
- A complete human pancreatic cancer genome.bioRxiv : the preprint server for biology · 2026Article
- Leveraging a spectrum of cytogenomics methods for profiling complex karyotypes in chronic lymphocytic leukemia.Human genomics · 2026Article
- Severus detects somatic structural variation and complex rearrangements in cancer genomes using long-read sequencing.Nature biotechnology · 2026Article
- Epigenomic, transcriptomic, and proteomic characterization of breast cancer cell line reference samples.Cell reports methods · 2026Article
- Generation and characterization of early stage oral cancer cell line of buccal mucosa of Indian origin.Human cell · 2025Article
- Benchmarking Ploidy Estimation Methods for Bulk and Single-Cell Whole Genome Sequencing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- SSLCNV: A Semi-supervised Learning Framework for Accurate Copy Number Variation Detection.Interdisciplinary sciences, computational life sciences · 2025Article
- Diploid donor-specific assembly enhances somatic structural variant detection in cancer genomes.bioRxiv : the preprint server for biology · 2025Article
- FocalSV enables target region-based structural variant assembly and refinement using single-molecule long-read sequencing data.Genome research · 2025Article
- CCRR: a user-friendly platform for analyzing complex chromosomal rearrangements in tumors.Bioinformatics (Oxford, England) · 2025Article
- Enhanced identification of novel pathogenic variants in hereditary hearing loss through physical phasing with integrated short and long-read sequencing data.Molecular genetics and genomics : MGG · 2025Article
- A benchmarking study of copy number variation inference methods using single-cell RNA-sequencing data.Precision clinical medicine · 2025Article
- Evaluative Methodology for HRD Testing: Development of Standard Tools for Consistency Assessment.Genomics, proteomics & bioinformatics · 2025Article
- Article
- Unraveling the hidden complexity of cancer through long-read sequencing.Genome research · 2025Review
- Review
- De novo and somatic structural variant discovery with SVision-pro.Nature biotechnology · 2025Article
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Authors and funding
39 authors at 12 institutions in 2 countries.
Funding
Abstract
backgroundThe cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples.
resultsWe systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy.
conclusionsA high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.
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