ArticleScientific reports2016
In-depth comparison of somatic point mutation callers based on different tumor next-generation sequencing depth data.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.
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Who cites it
66 citing papers in PubMed.
- De novo single-nucleotide and copy number variation in discordant monozygotic twins reveals disease-related genes.European journal of human genetics : EJHG · 2019Trial
- An IRAT109 NAM population: Genetic characterization and mapping utility for trait dissection in japonica rice (Oryza sativa L.).The plant genome · 2026Article
- Synth4bench: generating synthetic data for benchmarking tumor-only somatic variant calling algorithms.Frontiers in bioinformatics · 2026Article
- Clinical and analytical validation of a combined RNA and DNA exome assay across a large tumor cohort.Communications medicine · 2025Article
- UNISOM: Unified Somatic Calling and Machine Learning-based Classification Enhance the Discovery of CHIP.Genomics, proteomics & bioinformatics · 2025Article
- Benchmarking UMI-aware and standard variant callers for low frequency ctDNA variant detection.BMC genomics · 2024Article
- Genomic Insights into Idiopathic Granulomatous Mastitis through Whole-Exome Sequencing: A Case Report of Eight Patients.International journal of molecular sciences · 2024Article
- DEEPOMICS FFPE, a deep neural network model, identifies DNA sequencing artifacts from formalin fixed paraffin embedded tissue with high accuracy.Scientific reports · 2024Article
- Performance analysis of conventional and AI-based variant callers using short and long reads.BMC bioinformatics · 2023Article
- Quantification of rare somatic single nucleotide variants by droplet digital PCR using SuperSelective primers.Scientific reports · 2023Article
- Multicentric pilot study to standardize clinical whole exome sequencing (WES) for cancer patients.NPJ precision oncology · 2023Article
- Mutational signature assignment heterogeneity is widespread and can be addressed by ensemble approaches.Briefings in bioinformatics · 2023Article
- Article
- Technological and computational approaches to detect somatic mosaicism in epilepsy.Neurobiology of disease · 2023Review
- Designing neoantigen cancer vaccines, trials, and outcomes.Frontiers in immunology · 2023Review
- Somatic genetic variation in healthy tissue and non-cancer diseases.European journal of human genetics : EJHG · 2023Review
- Personalized genome assembly for accurate cancer somatic mutation discovery using tumor-normal paired reference samples.Genome biology · 2022Article
- The origin of bladder cancer from mucosal field effects.iScience · 2022Article
- Detection of oncogenic and clinically actionable mutations in cancer genomes critically depends on variant calling tools.Bioinformatics (Oxford, England) · 2022Article
- Prospects and challenges of cancer systems medicine: from genes to disease networks.Briefings in bioinformatics · 2022Review
6 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Four popular somatic single nucleotide variant (SNV) calling methods (Varscan, SomaticSniper, Strelka and MuTect2) were carefully evaluated on the real whole exome sequencing (WES, depth of ~50X) and ultra-deep targeted sequencing (UDT-Seq, depth of ~370X) data. The four tools returned poor consensus on candidates (only 20% of calls were with multiple hits by the callers). For both WES and UDT-Seq, MuTect2 and Strelka obtained the largest proportion of COSMIC entries as well as the lowest rate of dbSNP presence and high-alternative-alleles-in-control calls, demonstrating their superior sensitivity and accuracy. Combining different callers does increase reliability of candidates, but narrows the list down to very limited range of tumor read depth and variant allele frequency. Calling SNV on UDT-Seq data, which were of much higher read-depth, discovered additional true-positive variations, despite an even more tremendous growth in false positive predictions. Our findings not only provide valuable benchmark for state-of-the-art SNV calling methods, but also shed light on the access to more accurate SNV identification in the future.
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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.