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TrinityFusion-UC v0.3.4 (Tamura et al. 2026)

TrinityFusion-UC as run in the cited comparison.

Overview

TrinityFusion-UC as run in the cited comparison.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

4 evaluations · 24 results. Different protocols are not a single leaderboard.

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, conventional RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	0.42 f1-score fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'F1' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, conventional RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	1,026 false-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'False negative' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, conventional RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	590 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'False positive' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, conventional RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	0.5 precision fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'Positive predictive value' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, conventional RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	0.36 recall fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'True positive rate' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, conventional RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	583 true-positive-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'True positive' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, targeted RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	0.33 f1-score fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'F1' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, targeted RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	183 false-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'False negative' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, targeted RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	6 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'False positive' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, targeted RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	0.89 precision fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'Positive predictive value' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, targeted RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	0.2 recall fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'True positive rate' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: All fusions, targeted RNA-seq of haematologic cell lines, consensus truth (Tamura et al. 2026 Supplementary Table 3) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	47 true-positive-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on all fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-all-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 3, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'True positive' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, conventional RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	0.77 f1-score fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'F1' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, conventional RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	23 false-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'False negative' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, conventional RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	0 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'False positive' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, conventional RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	1 precision fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'Positive predictive value' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, conventional RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	0.62 recall fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'True positive rate' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, conventional RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: CCLE haematologic malignancy cell lines, conventional RNA-seq (170 cell lines)	38 true-positive-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, conventional RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-conventional Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Conventional RNA-seq of cell lines', row 'TrinityFusion-UC', column 'True positive' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, targeted RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	0.91 f1-score fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'F1' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, targeted RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	4 false-negative-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'False negative' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, targeted RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	0 false-positive-count count · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'False positive' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, targeted RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	1 precision fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'Positive predictive value' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, targeted RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	0.83 recall fraction · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'True positive rate' (PDF page text)
Configuration: TrinityFusion-UC v0.3.4 (Tamura et al. 2026)	Protocol: Driver fusions, targeted RNA-seq of haematologic cell lines, validated truth (Tamura et al. 2026 Supplementary Table 5) Dataset: Haematologic cancer cell lines, hybridisation-capture targeted RNA-seq (26 cell lines)	20 true-positive-count count · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source TrinityFusion-UC on driver fusions, targeted RNA-seq (Tamura et al. 2026) rna-fusion-20261009-protocol-tamura2026-driver-targeted Aggregation: Not reported Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies; Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Supplementary Table 5, 'Targeted RNA-seq of cell lines', row 'TrinityFusion-UC', column 'True positive' (PDF page text)

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Comparison of gene fusion detection algorithms reveals frequently overlooked driver fusions in hematologic malignancies · Original source · NPJ Precision Oncology 10:199, published 2026-04-04; PMC13230599 full-text XML
Tamura et al. 2026, Supplementary Information (Supplementary Tables 1-12) · Original source · 41698_2026_1397_MOESM1_ESM.pdf as served by the publisher

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Technical metadata and extraction receipts

Stable ID: rna-fusion-20261009-config-tamura2026-trinityfusion-uc

areas: rna-transcriptomes
contexts: clinical_research
method types: conventional_pipeline
reported name: TrinityFusion-UC
version: v0.3.4
foundation model eligible: false
protocol: Recommended parameters; alignment method de novo assembly & STAR; aligner STAR v2.7.8a; GRCh38; filtered output used where available
source locator: Supplementary Table 1; Methods 'Detection of gene fusions by each algorithm'

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