ArticleGenome biology2014
MSEA: detection and quantification of mutation hotspots through mutation set enrichment analysis.
Article in Genome biology, 2014. 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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Who cites it
41 citing papers in PubMed.
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- A comprehensive database for identifying and interpreting ctDNA driver genes and variants in cancer.Scientific data · 2025Article
- Advances in predicting breast cancer driver mutations: Tools for precision oncology (Review).International journal of molecular medicine · 2025Review
- Integrative multi-omics characterization of hepatocellular carcinoma in Hispanic patients.Journal of the National Cancer Institute · 2024Article
- Gsw-fi: a GLM model incorporating shrinkage and double-weighted strategies for identifying cancer driver genes with functional impact.BMC bioinformatics · 2024Article
- Adaptation of a mutual exclusivity framework to identify driver mutations within oncogenic pathways.American journal of human genetics · 2024Article
- Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools.Journal of molecular evolution · 2023Review
- The roles of sexual selection and sexual conflict in shaping patterns of genome and transcriptome variation.Nature ecology & evolution · 2023Review
- Computational Methods Summarizing Mutational Patterns in Cancer: Promise and Limitations for Clinical Applications.Cancers · 2023Review
- SWEET: a single-sample network inference method for deciphering individual features in disease.Briefings in bioinformatics · 2023Article
- WMDS.net: a network control framework for identifying key players in transcriptome programs.Bioinformatics (Oxford, England) · 2023Article
- ESCCdb: A comprehensive database and key regulator exploring platform based on cross dataset comparisons for esophageal squamous cell carcinoma.Computational and structural biotechnology journal · 2023Article
- Pan-cancer illumination of TRIM gene family reveals immunology regulation and potential therapeutic implications.Human genomics · 2022Article
- DriverRWH: discovering cancer driver genes by random walk on a gene mutation hypergraph.BMC bioinformatics · 2022Article
- Bacille Calmette-Guérin vaccine reprograms human neonatal lipid metabolism in vivo and in vitro.Cell reports · 2022Article
- Landscape of drug-resistance mutations in kinase regulatory hotspots.Briefings in bioinformatics · 2021Article
- The NCI Genomic Data Commons.Nature genetics · 2021Article
- OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.Nucleic acids research · 2021Article
- Cancer-Associated circRNA-miRNA-mRNA Regulatory Networks: A Meta-Analysis.Frontiers in molecular biosciences · 2021Article
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Authors and funding
6 authors.
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Abstract
Many cancer genes form mutation hotspots that disrupt their functional domains or active sites, leading to gain- or loss-of-function. We propose a mutation set enrichment analysis (MSEA) implemented by two novel methods,MSEA-clust and MSEA-domain, to predict cancer genes based on mutation hotspot patterns. MSEA methods are evaluated by both simulated and real cancer data. We find approximately 51% of the eligible known cancer genes form detectable mutation hotspots. Application of MSEA in eight cancers reveals a total of 82 genes with mutation hotspots,including well-studied cancer genes, known cancer genes re-found in new cancer types, and novel cancer genes.
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