Evidence map›Paper›PMID 38746128›Full record

ArticlebioRxiv : the preprint server for biology2025

Single-Cell Omics for Transcriptome CHaracterization (SCOTCH): isoform-level characterization of gene expression through long-read single-cell RNA sequencing.

Zhuoran Xu, Hui-Qi Qu, Joe Chan, Shizhuo Mu, Charlly Kao, Hakon Hakonarson, Kai Wang

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Zhuoran XuGraduate Group in Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.ORCID 0000-0001-6733-541X
Hui-Qi QuThe Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA.ORCID 0000-0001-9317-4488
Joe ChanRaymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Shizhuo MuRaymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
Charlly KaoThe Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA.
Hakon HakonarsonThe Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA.ORCID 0000-0003-2814-7461
Kai WangRaymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.

Funding

The Intellectual and Developmental Disabilities Research Center (IDDRC) at CHOP/PennP50HD105354 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI ERIC D MARSH, ROBERT Thomas SCHULTZ · 2021 to 2026
$9.2M
Detection and annotation of structural variants from long-read sequencingR01GM132713 · NIGMS · CHILDREN'S HOSP OF PHILADELPHIA · PI WANG, KAI · 2019 to 2022
$1.9M
NICHD NIH HHS P50 HD105354NIGMS NIH HHS R01 GM132713
6 · The paper itself

Abstract

Recent development involving long-read single-cell transcriptome sequencing (lr-scRNA-Seq) represents a significant leap forward in single-cell genomics. With the recent introduction of R10 flowcells by Oxford Nanopore, we propose that previous computational methods designed to handle high sequencing error rates are less relevant, and that the traditional approach using short reads to compile "barcode space" (candidate barcode list) to de-multiplex long reads are no longer necessary. Instead, computational methods should now shift focus on harnessing the unique benefits of long reads to analyze transcriptome complexity. In this context, we introduce a comprehensive suite of computational methods named Single-Cell Omics for Transcriptome CHaracterization (SCOTCH). SCOTCH supports both Nanopore and PacBio sequencing platforms, and is compatible with single-cell library preparation protocols from both 10X Genomics and Parse Biosciences. Through a sub-exon identification strategy with dynamic thresholding and read mapping scores, SCOTCH precisely aligns reads to known isoforms and discover novel isoforms, efficiently addressing ambiguous mapping challenges commonly encountered in long-read single-cell data. Comprehensive simulations and real data analyses across multiple platforms (including 10X Genomics and Parse Bioscience, paired with Illumina or Nanopore sequencing technologies with R9 and R10 flowcells, as well as PacBio sequencing) demonstrated that SCOTCH outperforms existing methods in mapping accuracy, quantification accuracy and novel isoform detection, while also uncovering novel biological insights on transcriptome complexity at the single-cell level.

Identifiers

PMID38746128
PMCPMC11092450

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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.