ArticleRNA biology2021
Comparative study of bioinformatic tools for the identification of chimeric RNAs from RNA Sequencing.
Article in RNA biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Article
- Bioinformatic Discovery of Tumor-Specific Neoantigens Arising from Chimeric RNAs.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Integrative Chimeric RNA Prediction with FASfuse.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Regulatory Mechanisms and Functional Roles of Readthrough Transcripts in Tumorigenesis.International journal of molecular sciences · 2025Review
- Whole transcriptome analysis identifiesCancer pathogenesis and therapy · 2025Article
- Revealing the role of U2AF1 in splicing regulation and chimeric RNA dynamics.Scientific reports · 2025Article
- Effective Utilization of a Customized Targeted Hybrid Capture RNA Sequencing in the Routine Molecular Categorization of Adolescent and Adult B-Lineage Acute Lymphoblastic Leukemia: A Real-World Experience.Molecular diagnosis & therapy · 2025Article
- Article
- Architects and Partners: The Dual Roles of Non-coding RNAs in Gene Fusion Events.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Chimeric SFT2D2-TBX19 Promotes Prostate Cancer Progression by Encoding TBX19-202 Protein and Stabilizing Mitochondrial ATP Synthase through ATP5F1A Phosphorylation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- OncogenicMedComm · 2024Article
- RTCpredictor: identification of read-through chimeric RNAs from RNA sequencing data.Briefings in bioinformatics · 2024Article
- Chimeric RNAs and their implication in prostate cancer.Cancer pathogenesis and therapy · 2023Review
- Recent advances in cancer fusion transcript detection.Briefings in bioinformatics · 2023Review
- Chimeric RNAs Discovered by RNA Sequencing and Their Roles in Cancer and Rare Genetic Diseases.Genes · 2022Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Chimeric RNAs are gaining more and more attention as they have broad implications in both cancer and normal physiology. To date, over 40 chimeric RNA prediction methods have been developed to facilitate their identification from RNA sequencing data. However, a limited number of studies have been conducted to compare the performance of these tools; additionally, previous studies have become outdated as more software tools have been developed within the last three years. In this study, we benchmarked 16 chimeric RNA prediction software, including seven top performers in previous benchmarking studies, and nine that were recently developed. We used two simulated and two real RNA-Seq datasets, compared the 16 tools for their sensitivity, positive prediction value (PPV), F-measure, and also documented the computational requirements (time and memory). We noticed that none of the tools are inclusive, and their performance varies depending on the dataset and objects. To increase the detection of true positive events, we also evaluated the pair-wise combination of these methods to suggest the best combination for sensitivity and F-measure. In addition, we compared the performance of the tools for the identification of three classes (read-through, inter-chromosomal and intra-others) of chimeric RNAs. Finally, we performed TOPSIS analyses and ranked the weighted performance of the 16 tools.
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Registered trials
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