ArticleGenome research2015
Discriminating somatic and germline mutations in tumor DNA samples without matching normals.
Article in Genome research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
- Article
- Improved tumor-only variant calling and mutation burden estimation with VarNet-T.Nature communications · 2026Article
- Clinical Implementation of Matched Tumor/Germline Sequencing Improves Accuracy of Tumor Genomic Profiling and Therapeutic Recommendations.The Journal of molecular diagnostics : JMD · 2025Article
- Detecting likely germline variants during tumor-based molecular profiling.The Journal of clinical investigation · 2025Review
- Predicting high confidence ctDNA somatic variants with ensemble machine learning models.Scientific reports · 2025Article
- Characteristics of genomic alterations and heavy metals in hypertensive patients with non‑small cell lung cancer.Oncology letters · 2025Article
- Differences in Genomic Alterations and Accumulations of Heavy Metals Between Advanced Non-small Cell Lung Cancer Patients with and without Bone Metastasis.Journal of Cancer · 2024Article
- Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures.Nature communications · 2023Article
- Guadecitabine plus ipilimumab in unresectable melanoma: five-year follow-up and integrated multi-omic analysis in the phase 1b NIBIT-M4 trial.Nature communications · 2023Article
- Differences of genomic alterations and heavy metals in non-small cell lung cancer with different histological subtypes.Journal of cancer research and clinical oncology · 2023Article
- Somatic mosaicism in inborn errors of immunity: Current knowledge, challenges, and future perspectives.Seminars in immunology · 2023Review
- Genomic Signatures from Clinical Tumor Sequencing in Patients with Breast Cancer Having Germline BRCA1/2 Mutation.Cancer research and treatment · 2023Article
- Targeting the DNA Damage Response Pathways and Replication Stress in Colorectal Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022Article
- Differences in actionable genomic alterations between brain metastases and non‑brain metastases in patients with non‑small cell lung cancer.International journal of oncology · 2022Article
- Estimating tumor mutational burden from RNA-sequencing without a matched-normal sample.Nature communications · 2022Article
- Computational methods and translational applications for targeted next-generation sequencing platforms.Genes, chromosomes & cancer · 2022Review
- TOSCA: an automated Tumor Only Somatic CAlling workflow for somatic mutation detection without matched normal samples.Bioinformatics advances · 2022Article
- Fusion transcripts and their genomic breakpoints in polyadenylated and ribosomal RNA-minus RNA sequencing data.GigaScience · 2021Article
- UNMASC: tumor-only variant calling with unmatched normal controls.NAR cancer · 2021Article
- Ideafix: a decision tree-based method for the refinement of variants in FFPE DNA sequencing data.NAR genomics and bioinformatics · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor analyses commonly employ a correction with a matched normal (MN), a sample from healthy tissue of the same individual, in order to distinguish germline mutations from somatic mutations. Since the majority of variants found in an individual are thought to be common within the population, we constructed a set of 931 samples from healthy, unrelated individuals, originating from two different sequencing platforms, to serve as a virtual normal (VN) in the absence of such an associated normal sample. Our approach removed (1) >96% of the germline variants also removed by the MN sample and (2) a large number (2%-8%) of additional variants not corrected for by the associated normal. The combination of the VN with the MN improved the correction for polymorphisms significantly, with up to ∼30% compared with MN and ∼15% compared with VN only. We determined the number of unrelated genomes needed in order to correct at least as efficiently as the MN is about 200 for structural variations (SVs) and about 400 for single-nucleotide variants (SNVs) and indels. In addition, we propose that the removal of common variants with purely position-based methods is inaccurate and incurs additional false-positive somatic variants, and more sophisticated algorithms, which are capable of leveraging information about the area surrounding variants, are needed for optimal accuracy. Our VN correction method can be used to analyze any list of variants, regardless of sequencing platform of origin. This VN methodology is available for use on our public Galaxy server.
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