ArticleGenome biology2013
Virmid: accurate detection of somatic mutations with sample impurity inference.
Article in Genome biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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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.
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Who cites it
41 citing papers in PubMed.
- Clonal Evolutionary Analysis during HER2 Blockade in HER2-Positive Inflammatory Breast Cancer: A Phase II Open-Label Clinical Trial of Afatinib +/- Vinorelbine.PLoS medicine · 2016Trial
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- Germline Pathogenic DROSHA Variants Are Linked to Pineoblastoma and Wilms Tumor Predisposition.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025Article
- A benchmarking study of individual somatic variant callers and voting-based ensembles for whole-exome sequencing.Briefings in bioinformatics · 2024Article
- Validation of genetic variants from NGS data using deep convolutional neural networks.BMC bioinformatics · 2023Article
- Utilizing immunogenomic approaches to prioritize targetable neoantigens for personalized cancer immunotherapy.Frontiers in immunology · 2023Review
- Bias and inconsistency in the estimation of tumour mutation burden.BMC cancer · 2022Article
- Parental mosaicism for apparent de novo genetic variants: Scope, detection, and counseling challenges.Prenatal diagnosis · 2022Review
- Combinatorial and Machine Learning Approaches for Improved Somatic Variant Calling From Formalin-Fixed Paraffin-Embedded Genome Sequence Data.Frontiers in genetics · 2022Article
- Somatic and Germline Variant Calling from Next-Generation Sequencing Data.Advances in experimental medicine and biology · 2022Article
- Non-CG DNA methylation-deficiency mutations enhance mutagenesis rates during salt adaptation in cultured Arabidopsis cells.Stress biology · 2021Article
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- GEAMP, a novel gastroesophageal junction carcinoma cell line derived from a malignant pleural effusion.Laboratory investigation; a journal of technical methods and pathology · 2020Article
- Comprehensive Outline of Whole Exome Sequencing Data Analysis Tools Available in Clinical Oncology.Cancers · 2019Review
- Article
- FERMI: A Novel Method for Sensitive Detection of Rare Mutations in Somatic Tissue.G3 (Bethesda, Md.) · 2019Article
- The use of technical replication for detection of low-level somatic mutations in next-generation sequencing.Nature communications · 2019Article
- Somatic mutation detection and classification through probabilistic integration of clonal population information.Communications biology · 2019Article
- Calling Variants in the Clinic: Informed Variant Calling Decisions Based on Biological, Clinical, and Laboratory Variables.Computational and structural biotechnology journal · 2019Review
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.
Funding
Abstract
Detection of somatic variation using sequence from disease-control matched data sets is a critical first step. In many cases including cancer, however, it is hard to isolate pure disease tissue, and the impurity hinders accurate mutation analysis by disrupting overall allele frequencies. Here, we propose a new method, Virmid, that explicitly determines the level of impurity in the sample, and uses it for improved detection of somatic variation. Extensive tests on simulated and real sequencing data from breast cancer and hemimegalencephaly demonstrate the power of our model. A software implementation of our method is available at http://sourceforge.net/projects/virmid/.
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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.