A comprehensive benchmark of transcriptome-wide fusion detection using long-read RNA sequencing

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• 4 methods
• 9 configurations
• 4 protocols
• 3 datasets
• 21 evaluations
• 597 results
• 5 evidence claims
• 1 use case

Results

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Claims

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• Evidence summary: tumour RNA fusion detection workflows: Summary Four comparisons join the Seraseq reference and paediatric NCH cohort evidence; values cannot be pooled across studies. Tamura et al. 2026 ran 12 short-read callers on haematologic cancer cell lines; one, Genomon, comes from a co-author's group. On 61 driver fusions in conventional RNA-seq of 170 cell lines, Arriba detected all 61 (TPR 1), FusionCatcher 0.98, STAR-Fusion 0.93, InFusion 0.43 and STARChip 0.41. On 24 driver fusions in targeted RNA-seq of 26 cell lines, Arriba again reached 1 and STAR-Fusion 0.92, InFusion 0.17 and STARChip 0. A driver fusion entered these truth sets only if at least four callers, including the one scored, found it and it had literature or RT-PCR support, so fusions that most callers miss are under-represented and these values may overstate sensitivity. Against a consensus of the other callers, the number of single-caller calls, a measure of review burden, ranged on conventional RNA-seq from 327 for TrinityFusion-D and 1,061 for STAR-Fusion (PPV 0.39) to 9,567 for Arriba (PPV 0.08), 22,445 for FusionCatcher and 695,295 for Pizzly. On nanopore long reads from 51 paediatric B-ALL samples (Lin et al. 2026), scored on the dominant fusion per sample, JAFFAL reached sensitivity 0.76, LongGF 0.70 and FusionSeeker 0.63, with precision 0.79 to 0.95; the authors' own FUSILLI reached 0.81. At about one eighth of the depth, sensitivity was 0.09 to 0.27. In an independent long-read benchmark (Dorney et al. 2026 preprint), no caller exceeded F1 0.35 on 400 simulated fusions at 100 Gb and 95% read identity: CTAT-LR-Fusion 0.35 (recall 0.28, precision 0.46), JAFFAL 0.29, Genion 0.20, FusionSeeker 0.14, GFSeeker 0.07 and LongGF 0.04. On all ONT PCR-cDNA reads of the MCF7 cell line, CTAT-LR-Fusion's calls matched 20 of 53 previously reported fusions, with 51 other calls; JAFFAL matched 19 with 38 other calls and FusionSeeker 11 with 359. The other calls mix real fusions missing from the literature list and false calls. On the Huh7 cell line, pooling six long-read callers per long-read platform and three short-read callers for Illumina, PacBio Kinnex recovered 20 of 34 previously reported fusions, ONT PCR-cDNA 17 and Illumina 15. Against karyotyping, FISH and RT-PCR in 101 adult and paediatric acute leukaemia patients (Kim et al. 2026), an Arriba workflow with manual review detected 40 of 48 conventionally detected fusions (sensitivity 83.3%) and called fusions in 21.4% of 56 conventionally negative results; these count against specificity, although the authors describe several as well-known recurrent fusions and confirmed one by RT-PCR and Sanger sequencing. These are cell lines, simulations and leukaemia samples: no linked comparison covers solid-tumour specimens, FFPE tissue or novel-fusion discovery, only Kim et al. score against orthogonal clinical assays, none reports interval estimates, and none establishes clinical performance. (amp-oncology-rna-20261007-source-pmc8642973: Seraseq and NCH results; rna-fusion-20261009-source-tamura2026-supplementary: Supplementary Tables 3 and 5; rna-fusion-20261009-source-tamura2026: Methods and Author contributions; rna-fusion-20261009-source-lin2026: Tables 3 and 6, Results; rna-fusion-longread-20261011-source-dorney2026: see claims.csv of its batch; rna-fusion-longread-20261011-source-dorney2026-repository: see claims.csv of its batch; rna-fusion-leukaemia-20261011-source-kim2025: see claims.csv of its batch)
• Relevance of Huh7 known-fusion recovery by platform (Dorney et al. 2026) to "Select a tumour RNA fusion-detection workflow": Assessed by Huh7 recovery of 34 previously reported fusions by library type, union of callers (Dorney et al. 2026) (rna-fusion-longread-20261011-source-dorney2026: Results; Methods 'Simulation datasets', 'Public long-read datasets', 'Benchmark evaluation criteria'; Competing interests)
• Relevance of K562 known-fusion recovery (Dorney et al. 2026) to "Select a tumour RNA fusion-detection workflow": Assessed by K562 ONT long-read RNA-seq, recovery of 6 known fusions and count of other calls (Dorney et al. 2026) (rna-fusion-longread-20261011-source-dorney2026: Results; Methods 'Simulation datasets', 'Public long-read datasets', 'Benchmark evaluation criteria'; Competing interests; rna-fusion-longread-20261011-source-dorney2026-repository: Figures/Input_dataframes/stat_summary.tsv; counts_SGNex_summary.tsv.gz; SimulatedData/Data_Analysis_Scripts/Precision_Recall_ReadSupp_stats.R; CellLineData/SGNex_DiscoveryNRecall.R)
• Relevance of MCF7 known-fusion recovery (Dorney et al. 2026) to "Select a tumour RNA fusion-detection workflow": Assessed by MCF7 ONT long-read RNA-seq, recovery of 53 known fusions and count of other calls (Dorney et al. 2026) (rna-fusion-longread-20261011-source-dorney2026: Results; Methods 'Simulation datasets', 'Public long-read datasets', 'Benchmark evaluation criteria'; Competing interests; rna-fusion-longread-20261011-source-dorney2026-repository: Figures/Input_dataframes/stat_summary.tsv; counts_SGNex_summary.tsv.gz; SimulatedData/Data_Analysis_Scripts/Precision_Recall_ReadSupp_stats.R; CellLineData/SGNex_DiscoveryNRecall.R)
• Relevance of Simulated long-read fusion detection (Dorney et al. 2026) to "Select a tumour RNA fusion-detection workflow": Assessed by Simulated long-read fusion detection, 400 fusions at three depths and three read identities (Dorney et al. 2026) (rna-fusion-longread-20261011-source-dorney2026: Results; Methods 'Simulation datasets', 'Public long-read datasets', 'Benchmark evaluation criteria'; Competing interests; rna-fusion-longread-20261011-source-dorney2026-repository: Figures/Input_dataframes/stat_summary.tsv; counts_SGNex_summary.tsv.gz; SimulatedData/Data_Analysis_Scripts/Precision_Recall_ReadSupp_stats.R; CellLineData/SGNex_DiscoveryNRecall.R)

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