ArticleNature communications2021
SCISSOR: a framework for identifying structural changes in RNA transcripts.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 17 citations in OpenAlex.
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- Data-driven RNA phenotyping captures genetically regulated dimensions of the transcriptome.American journal of human genetics · 2026Article
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- BayesCNV: A Bayesian Hierarchical Model for Sensitive and Specific Copy Number Estimation in Cell Free DNA.Diagnostics (Basel, Switzerland) · 2026Article
- ELViS: an R package for estimating copy number levels of viral genomic segments at base-resolution.Bioinformatics (Oxford, England) · 2025Article
- The offonome reveals on and off states of gene expression near the detection limit of RNA-seq.Scientific reports · 2025Article
- Integrating bulk and single-cell data to predict the prognosis and identify the immune landscape in HNSCC.Journal of cellular and molecular medicine · 2024Article
- High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer.Cancer cell · 2022Article
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- Prioritizing risk genes as novel stratification biomarkers for acute monocytic leukemia by integrative analysis.Discover oncology · 2022Article
- Immune checkpoint blockade reprograms systemic immune landscape and tumor microenvironment in obesity-associated breast cancer.Cell reports · 2021Article
- Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway.Cell reports · 2021Article
- SCISSOR: a framework for identifying structural changes in RNA transcripts.Nature communications · 2021Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
Abstract
High-throughput sequencing protocols such as RNA-seq have made it possible to interrogate the sequence, structure and abundance of RNA transcripts at higher resolution than previous microarray and other molecular techniques. While many computational tools have been proposed for identifying mRNA variation through differential splicing/alternative exon usage, challenges in its analysis remain. Here, we propose a framework for unbiased and robust discovery of aberrant RNA transcript structures using short read sequencing data based on shape changes in an RNA-seq coverage profile. Shape changes in selecting sample outliers in RNA-seq, SCISSOR, is a series of procedures for transforming and normalizing base-level RNA sequencing coverage data in a transcript independent manner, followed by a statistical framework for its analysis ( https://github.com/hyochoi/SCISSOR ). The resulting high dimensional object is amenable to unsupervised screening of structural alterations across RNA-seq cohorts with nearly no assumption on the mutational mechanisms underlying abnormalities. This enables SCISSOR to independently recapture known variants such as splice site mutations in tumor suppressor genes as well as novel variants that are previously unrecognized or difficult to identify by any existing methods including recurrent alternate transcription start sites and recurrent complex deletions in 3' UTRs.
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