ArticleNature communications2026
SCOTCH: isoform-level characterization of gene expression through long-read single-cell RNA sequencing.
Article in Nature communications, 2026. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- SCOTCH: isoform-level characterization of gene expression through long-read single-cell RNA sequencing.Nature communications · 2026Article
- Current trends and challenges in deciphering single molecule resolution maps of single cell transcriptomes.Briefings in bioinformatics · 2026Review
- Risk of Alzheimer's disease in Down syndrome: Insights gained by multi-omics.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Advancing automated cell type annotation with large language models and single-cell isoform sequencing.Computational and structural biotechnology journal · 2025Review
Corrections and comments
- Update of
Authors and funding
7 authors.
Funding
Abstract
Recent advances in long-read single-cell transcriptome sequencing (lr-scRNA-Seq) enable full-length isoform profiling at single-cell resolution. We present SCOTCH (Single-Cell Omics for Transcriptome CHaracterization), an end-to-end, platform-independent pipeline for isoform characterization from lr-scRNA-Seq data, supporting Nanopore and PacBio sequencing as well as 10X Genomics and Parse Biosciences protocols. SCOTCH models isoforms as combinations of non-overlapping sub-exons and applies dynamic thresholding for robust isoform assignment while efficiently address ambiguous mapping issues. By refining sub-exon boundaries through integration of read coverage with existing annotations and applying an iterative clustering strategy to reconstruct novel transcripts, SCOTCH reliably recovers more true novel isoforms than existing splice-graph-based methods, with poly(A)-aware filtering further reducing false-positive structures. Extensive simulations demonstrate improved quantification of known isoforms and enhanced reconstruction of novel isoforms. Analyses of human blood and cerebral organoid datasets across multiple platforms further confirm SCOTCH's ability to resolve cell-type-specific transcriptome profiles and uncover experimentally supported novel isoforms.
Indexed as
Identifiers
What OpenQuestion holds
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.