ReviewOncotarget2015
Structural variation discovery in the cancer genome using next generation sequencing: computational solutions and perspectives.
Review in Oncotarget, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 45 citations in OpenAlex.
- Monitoring and Assessment of Circulating Tumor DNA in Cancers Using Ultrarapid Sensitivity as an Innovative Practice.Health science reports · 2025Article
- Germline structural variations involving the pediatric brain tumor transcriptome include disease-relevant and ancestry-related genes.Acta neuropathologica communications · 2025Article
- The landscape of PD-L1 expression and somatic mutations in hepatocellular carcinoma.Journal of gastrointestinal oncology · 2021Article
- Detection of copy number variants in African goats using whole genome sequence data.BMC genomics · 2021Article
- Detection of somatic structural variants from short-read next-generation sequencing data.Briefings in bioinformatics · 2021Review
- Classical, Molecular, and Genomic Cytogenetics of the Pig, a Clinical Perspective.Animals : an open access journal from MDPI · 2021Review
- Structural variant detection in cancer genomes: computational challenges and perspectives for precision oncology.NPJ precision oncology · 2021Review
- Shiny-SoSV: A web-based performance calculator for somatic structural variant detection.PloS one · 2020Article
- Comprehensive evaluation and characterisation of short read general-purpose structural variant calling software.Nature communications · 2019Article
- Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing.Genome biology · 2019Article
- The Iceberg under Water: Unexplored Complexity of Chromoanagenesis in Congenital Disorders.American journal of human genetics · 2019Review
- Whole-Genome Sequencing in Cancer.Cold Spring Harbor perspectives in medicine · 2019Review
- Optical mapping reveals a higher level of genomic architecture of chained fusions in cancer.Genome research · 2018Article
- Breaking point: the genesis and impact of structural variation in tumours.F1000Research · 2018Review
- Linked read sequencing resolves complex genomic rearrangements in gastric cancer metastases.Genome medicine · 2017Article
- Next generation mapping reveals novel large genomic rearrangements in prostate cancer.Oncotarget · 2017Article
- Global analysis of somatic structural genomic alterations and their impact on gene expression in diverse human cancers.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Article
- cnvCurator: an interactive visualization and editing tool for somatic copy number variations.BMC bioinformatics · 2015Article
- The Value and Significance of Metagenomics of Marine Environments. Preface.Genomics, proteomics & bioinformatics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
Somatic Structural Variations (SVs) are a complex collection of chromosomal mutations that could directly contribute to carcinogenesis. Next Generation Sequencing (NGS) technology has emerged as the primary means of interrogating the SVs of the cancer genome in recent investigations. Sophisticated computational methods are required to accurately identify the SV events and delineate their breakpoints from the massive amounts of reads generated by a NGS experiment. In this review, we provide an overview of current analytic tools used for SV detection in NGS-based cancer studies. We summarize the features of common SV groups and the primary types of NGS signatures that can be used in SV detection methods. We discuss the principles and key similarities and differences of existing computational programs and comment on unresolved issues related to this research field. The aim of this article is to provide a practical guide of relevant concepts, computational methods, software tools and important factors for analyzing and interpreting NGS data for the detection of SVs in the cancer genome.
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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.