ArticleBioinformatics (Oxford, England)2013
A comparative analysis of algorithms for somatic SNV detection in cancer.
Article in Bioinformatics (Oxford, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
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Who cites it
64 citing papers in PubMed.
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- Comprehensive assessment of whole-genome sequencing-based variant calling pipelines in monozygotic twins.Briefings in bioinformatics · 2025Article
- Mitogenomic Alterations in Breast Cancer: Identification of Potential Biomarkers of Risk and Prognosis.International journal of molecular sciences · 2025Article
- CLEMENT: genomic decomposition and reconstruction of non-tumor subclones.Nucleic acids research · 2024Article
- mRNA vaccine development and applications: A special focus on tumors (Review).International journal of oncology · 2024Review
- A Novel Affordable and Reliable Framework for Accurate Detection and Comprehensive Analysis of Somatic Mutations in Cancer.International journal of molecular sciences · 2024Article
- Overexpression of SYNGAP1 suppresses the proliferation of rectal adenocarcinoma via Wnt/β-Catenin signaling pathway.Discover oncology · 2024Article
- Quantification of rare somatic single nucleotide variants by droplet digital PCR using SuperSelective primers.Scientific reports · 2023Article
- Pain-Related Gene Solute Carrier Family 24 Member 3 Is a Prognostic Biomarker and Correlated with Immune Infiltrates in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma: A Study via Integrated Bioinformatics Analyses and Experimental Verification.Computational and mathematical methods in medicine · 2023Article
- LPS-Induced Liver Injury of Magang Geese through Toll-like Receptor and MAPK Signaling Pathway.Animals : an open access journal from MDPI · 2022Article
- Direct comparison of the next-generation sequencing and iTERT PCR methods for the diagnosis of TERT hotspot mutations in advanced solid cancers.BMC medical genomics · 2022Article
- Structural and functional analysis of somatic coding and UTR indels in breast and lung cancer genomes.Scientific reports · 2021Article
- Generalizable characteristics of false-positive bacterial variant calls.Microbial genomics · 2021Article
- Branching clonal evolution patterns predominate mutational landscape in multiple myeloma.American journal of cancer research · 2021Article
- Detailed evaluation of cancer sequencing pipelines in different microenvironments and heterogeneity levels.Turkish journal of biology = Turk biyoloji dergisi · 2021Article
- Neo-Antigen mRNA Vaccines.Vaccines · 2020Review
- Comparative assessments of indel annotations in healthy and cancer genomes with next-generation sequencing data.BMC medical genomics · 2020Article
- SomaticCombiner: improving the performance of somatic variant calling based on evaluation tests and a consensus approach.Scientific reports · 2020Article
- Comparison of somatic variant detection algorithms using Ion Torrent targeted deep sequencing data.BMC medical genomics · 2019Article
4 more citing papers are in PubMed but not listed here.
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8 authors.
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Abstract
motivationWith the advent of relatively affordable high-throughput technologies, DNA sequencing of cancers is now common practice in cancer research projects and will be increasingly used in clinical practice to inform diagnosis and treatment. Somatic (cancer-only) single nucleotide variants (SNVs) are the simplest class of mutation, yet their identification in DNA sequencing data is confounded by germline polymorphisms, tumour heterogeneity and sequencing and analysis errors. Four recently published algorithms for the detection of somatic SNV sites in matched cancer-normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer-normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterized and compared to investigate the strengths and weaknesses of each SNV calling algorithm.
resultsComparing the candidate SNV sets returned by VarScan, SomaticSniper, JointSNVMix2 and Strelka revealed substantial differences with respect to the number and character of sites returned; the somatic probability scores assigned to the same sites; their susceptibility to various sources of noise; and their sensitivities to low-allelic-fraction candidates. AVAILABILITY: Data accession number SRA081939, code at http://code.google.com/p/snv-caller-review/ CONTACT: david.adelson@adelaide.edu.au SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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