Evidence map›Paper›PMID 41400872›Full record

ArticleBioinformatics (Oxford, England)2026

Analyzing cell-type-specific isoform expression using IsoDiffR and long-read single-cell RNA sequencing.

Hu Chen, Ye Qian, Qi Dai, Ying-Feng Zheng, Zhen-Cang Zheng, Zhuo-Xing Shi

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hu ChenCollege of Life Science and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China.ORCID 0009-0007-0540-7036
Ye QianCollege of Life Science and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China.ORCID 0009-0009-8465-1137
Qi DaiCollege of Life Science and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Ying-Feng ZhengState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou 510060, China.
Zhen-Cang ZhengDepartment of Critical Care Medicine, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang 318000, China.
Zhuo-Xing ShiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou 510060, China.

Funding

National Key Research and Development Program of China 2023YFF1205000National Natural Science Foundation of China 42107148National Natural Science Foundation of China 62172369
6 · The paper itself

Abstract

motivationThe analysis of RNA isoforms using long-read single-cell RNA sequencing (scRNA-seq) represents a frontier in gene expression research, offering deeper insights beyond traditional gene-level analysis. However, specialized analytical methods tailored for this advanced technology remain scarce, underscoring the urgent need for novel tools to match the rapid pace of its development.

resultsHere, we present IsoDiffR, a robust tool designed to identify RNA isoforms with expression patterns that differ from their corresponding genes or major isoforms across cell types, enabling both pairwise and multicell-type comparisons. Using IsoDiffR, we conducted benchmark tests using simulated data and analyzed long-read scRNA-seq data from the corneal limbus of Macaca fascicularis and the human frontal cortex, uncovering previously unrecognized cell-type-specific isoforms that were not detectable using conventional approaches. Additionally, we explored the structural and functional properties of these isoforms, from their nucleotide sequences to their corresponding protein isoforms, revealing their potential biological roles. Our findings offer new perspectives on gene expression regulation at the single-cell level and provide a methodological framework for future investigations of isoform-specific functions in diverse biological contexts. AVAILABILITY AND IMPLEMENTATION: The R package is available on https://github.com/Eveqian98/IsoDiffR.

Indexed as

RNA IsoformsSequence Analysis, RNASingle-Cell AnalysisSoftwareAnimalsGene Expression ProfilingHumansMacaca fascicularisProtein IsoformsProtein IsoformsRNA Isoforms

Identifiers

PMID41400872
PMCPMC12822774

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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.