ArticleBioinformatics (Oxford, England)2020
RNAIndel: discovering somatic coding indels from tumor RNA-Seq data.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Confounding factors in assessing the enriched expression of somatic mutant alleles in bulk tumor samples.Genome research · 2026Article
- Molecular risk markers define risk of relapse in myeloid leukemia of Down syndrome beyond measurable residual disease.Blood advances · 2026Article
- Small Nucleotide Variant Analysis Using RNA Fusion Panel (SMURF): Making the Most of RNAseq Data in Solid Tumours.Journal of clinical laboratory analysis · 2026Article
- RNA-based cancer vaccines: mechanisms, clinical progress, and translational challenges.Immunologic research · 2025Review
- Variant calling from RNA-Seq data reveals allele-specific differential expression of pathogenic cancer variants.Communications medicine · 2025Article
- A new genomic framework to categorize pediatric acute myeloid leukemia.Nature genetics · 2024Article
- Detecting Somatic Insertions/Deletions (Indels) Using Tumor RNA-Seq Data.Methods in molecular biology (Clifton, N.J.) · 2024Article
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- Article
- Dynamics of Age- versus Therapy-Related Clonal Hematopoiesis in Long-term Survivors of Pediatric Cancer.Cancer discovery · 2023Article
- Integrated Genomic Analysis Identifies UBTF Tandem Duplications as a Recurrent Lesion in Pediatric Acute Myeloid Leukemia.Blood cancer discovery · 2022Article
- Distinct genomic landscape of Chinese pediatric acute myeloid leukemia impacts clinical risk classification.Nature communications · 2022Article
- Integrated genomic analyses identify high-risk factors and actionable targets in T-cell acute lymphoblastic leukemia.Blood science (Baltimore, Md.) · 2022Article
- CBFB-MYH11 fusion transcripts distinguish acute myeloid leukemias with distinct molecular landscapes and outcomes.Blood advances · 2021Article
- Emerging molecular subtypes and therapeutic targets in B-cell precursor acute lymphoblastic leukemia.Frontiers of medicine · 2021Review
- Finding a suitable library size to call variants in RNA-Seq.BMC bioinformatics · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
11 authors.
Funding
Abstract
motivationReliable identification of expressed somatic insertions/deletions (indels) is an unmet need due to artifacts generated in PCR-based RNA-Seq library preparation and the lack of normal RNA-Seq data, presenting analytical challenges for discovery of somatic indels in tumor transcriptome.
resultsWe present RNAIndel, a tool for predicting somatic, germline and artifact indels from tumor RNA-Seq data. RNAIndel leverages features derived from indel sequence context and biological effect in a machine-learning framework. Except for tumor samples with microsatellite instability, RNAIndel robustly predicts 88-100% of somatic indels in five diverse test datasets of pediatric and adult cancers, even recovering subclonal (VAF range 0.01-0.15) driver indels missed by targeted deep-sequencing, outperforming the current best-practice for RNA-Seq variant calling which had 57% sensitivity but with 14 times more false positives. AVAILABILITY AND IMPLEMENTATION: RNAIndel is freely available at https://github.com/stjude/RNAIndel. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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