ArticleBMC genomics2018
A fast detection of fusion genes from paired-end RNA-seq data.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Characteristics of fusion genes in breast cancer.Cancer cell international · 2026Review
- The Goldilocks state of transcriptional readthrough for chimeric splicing.Transcription · 2026Review
- Integrative Chimeric RNA Prediction with FASfuse.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Deciphering IGH rearrangement complexity and detection strategies in acute lymphoblastic leukaemia.NPJ precision oncology · 2025Review
- LMNA::NTRK1 Fusion-positive Leiomyosarcoma: Discrepancy between DNA-based Comprehensive Genomic Profiling and RNA Sequencing.Internal medicine (Tokyo, Japan) · 2024Article
- RTCpredictor: identification of read-through chimeric RNAs from RNA sequencing data.Briefings in bioinformatics · 2024Article
- OnACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2023Article
- Chimeric RNAs reveal putative neoantigen peptides for developing tumor vaccines for breast cancer.Frontiers in immunology · 2023Article
- Transcriptomics and solid tumors: The next frontier in precision cancer medicine.Seminars in cancer biology · 2022Review
- Exon skipping in genes encoding lineage-defining myogenic transcription factors in rhabdomyosarcoma.Cold Spring Harbor molecular case studies · 2022Article
- Feasibility of whole genome and transcriptome profiling in pediatric and young adult cancers.Nature communications · 2022Article
- Fusion Gene Detection Using Whole-Exome Sequencing Data in Cancer Patients.Frontiers in genetics · 2022Article
- ChiTaH: a fast and accurate tool for identifying known human chimeric sequences from high-throughput sequencing data.NAR genomics and bioinformatics · 2021Article
- Comparative study of bioinformatic tools for the identification of chimeric RNAs from RNA Sequencing.RNA biology · 2021Article
- SeekFusion - A Clinically Validated Fusion Transcript Detection Pipeline for PCR-Based Next-Generation Sequencing of RNA.Frontiers in genetics · 2021Article
- LongGF: computational algorithm and software tool for fast and accurate detection of gene fusions by long-read transcriptome sequencing.BMC genomics · 2020Article
- RNAmut: robust identification of somatic mutations in acute myeloid leukemia using RNA-sequencing.Haematologica · 2020Article
- Using equivalence class counts for fast and accurate testing of differential transcript usage.F1000Research · 2019Article
- Article
- Utility of multimodality molecular profiling for pediatric patients with central nervous system tumors.Neuro-oncology advancesArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFusion genes are known to be drivers of many common cancers, so they are potential markers for diagnosis, prognosis or therapy response. The advent of paired-end RNA sequencing enhances our ability to discover fusion genes. While there are available methods, routine analyses of large number of samples are still limited due to high computational demands.
resultsWe develop FuSeq, a fast and accurate method to discover fusion genes based on quasi-mapping to quickly map the reads, extract initial candidates from split reads and fusion equivalence classes of mapped reads, and finally apply multiple filters and statistical tests to get the final candidates. We apply FuSeq to four validated datasets: breast cancer, melanoma and glioma datasets, and one spike-in dataset. The results reveal high sensitivity and specificity in all datasets, and compare well against other methods such as FusionMap, TRUP, TopHat-Fusion, SOAPfuse and JAFFA. In terms of computational time, FuSeq is two-fold faster than FusionMap and orders of magnitude faster than the other methods.
conclusionsWith this advantage of less computational demands, FuSeq makes it practical to investigate fusion genes in large numbers of samples. FuSeq is implemented in C++ and R, and available at https://github.com/nghiavtr/FuSeq for non-commercial uses.
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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.