ArticleGenome biology2024
Mining alternative splicing patterns in scRNA-seq data using scASfind.
Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Alternative Splicing: Molecular Mechanisms, Biological Functions, Diseases, and Potential Therapeutic Targets.MedComm · 2025Review
- Single-cell mapping of alternative splicing linked to checkpoint immunotherapy response.Nucleic acids research · 2025Article
- DOLPHIN advances single-cell transcriptomics beyond gene level by leveraging exon and junction reads.Nature communications · 2025Article
- Mining alternative splicing patterns in scRNA-seq data using scASfind.Genome biology · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Single-cell RNA-seq (scRNA-seq) is widely used for transcriptome profiling, but most analyses focus on gene-level events, with less attention devoted to alternative splicing. Here, we present scASfind, a novel computational method to allow for quantitative analysis of cell type-specific splicing events using full-length scRNA-seq data. ScASfind utilizes an efficient data structure to store the percent spliced-in value for each splicing event. This makes it possible to exhaustively search for patterns among all differential splicing events, allowing us to identify marker events, mutually exclusive events, and events involving large blocks of exons that are specific to one or more cell types.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.