{"doi":"10.1093/nar/gkaf1450","title":"Accurate detection of somatic single-nucleotide variants from bulk RNA-seq data using RNA-MosaicHunter","abstract":"Somatic variants are increasingly recognized as contributors to diverse non-cancer, developmental, and aging-related disorders. However, most tools for detecting somatic single-nucleotide variants (sSNVs) were designed for DNA sequencing and primarily tailored to cancer datasets, leaving a critical gap in harnessing the rich potential of RNA-seq for sSNV identification, particularly in non-cancer tissues with low mutation rates. Here, we introduce RNA-MosaicHunter, a novel bioinformatic tool for accurate sSNV detection from bulk RNA-seq. In two benchmarking datasets, it demonstrated high precision (94.7% in TCGA and 99.3% in a cell-line mixture) with sensitivities of 53.4% and 38.9%, respectively, in the default mode that maximizes precision. We then applied RNA-MosaicHunter to profile 827 RNA-seq samples in three tissue types from the Genotype Tissue Expression project (GTEx), where it outperformed previous methods in capturing mutational characteristics associated with normal aging. We further utilized RNA-MosaicHunter to analyze RNA-seq data from 382 Alzheimer's disease (AD) brain samples and 480 age-matched controls and revealed a significantly higher burden of sSNVs in AD cerebral cortex, suggesting the potential contribution of sSNVs to AD pathogenesis. RNA-MosaicHunter enables accurate profiling and characterization of sSNVs from RNA-seq data, advancing the understanding of the role of somatic variants across diverse tissues and diseases.","journal":"Nucleic Acids Research","year":2025,"id":549864,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9484,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":69077,"name":"Yuchen Cheng","orcid":null,"position":1,"is_corresponding":false},{"id":1212483,"name":"Jayoung Ku","orcid":"0000-0002-4112-4582","position":2,"is_corresponding":false},{"id":68975,"name":"Boxun Zhao","orcid":"0000-0003-2337-5756","position":3,"is_corresponding":false},{"id":810336,"name":"Junseok Park","orcid":"0009-0004-0347-5842","position":4,"is_corresponding":false},{"id":1444567,"name":"Dachan Kim","orcid":"0000-0001-5196-8482","position":5,"is_corresponding":false},{"id":692126,"name":"Jaejoon Choi","orcid":"0000-0002-6695-2157","position":6,"is_corresponding":false},{"id":1445244,"name":"Lee Ea","orcid":null,"position":7,"is_corresponding":false},{"id":558686,"name":"August Yue Huang","orcid":"0000-0002-0416-2854","position":0,"is_corresponding":true}],"reference_count":85,"raw_metadata":null,"created_at":"2026-07-19T02:54:12.321988Z","pmid":"41505106","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}