ArticleF1000Research2023
Toblerone: detecting exon deletion events in cancer using RNA-seq.
Article in F1000Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- 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
- Review
- Prediction of tumor-specific splicing from somatic mutations as a source of neoantigen candidates.Bioinformatics advances · 2024Article
- Toblerone: detecting exon deletion events in cancer using RNA-seq.F1000Research · 2023Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is driven by mutations of the genome that can result in the activation of oncogenes or repression of tumour suppressor genes. In acute lymphoblastic leukemia (ALL) focal deletions in IKAROS family zinc finger 1 (IKZF1) result in the loss of zinc-finger DNA-binding domains and a dominant negative isoform that is associated with higher rates of relapse and poorer patient outcomes. Clinically, the presence of IKZF1 deletions informs prognosis and treatment options. In this work we developed a method for detecting exon deletions in genes using RNA-seq with application to IKZF1. We developed a pipeline that first uses a custom transcriptome reference consisting of transcripts with exon deletions. Next, RNA-seq reads are mapped using a pseudoalignment algorithm to identify reads that uniquely support deletions. These are then evaluated for evidence of the deletion with respect to gene expression and other samples. We applied the algorithm, named Toblerone, to a cohort of 99 B-ALL paediatric samples including validated IKZF1 deletions. Furthermore, we developed a graphical desktop app for non-bioinformatics users that can quickly and easily identify and report deletions in IKZF1 from RNA-seq data with informative graphical outputs.
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Registered trials
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