Deciphering splicing heterogeneity at single-cell resolution by SCSES

Xiao Wen, Xuan Lv, Dan Guo, Nan Han, Lei Zhou, Peizhuo Wang and Zhaoqi Liu ()
Additional contact information
Xiao Wen: China National Center for Bioinformation
Xuan Lv: China National Center for Bioinformation
Dan Guo: China National Center for Bioinformation
Nan Han: China National Center for Bioinformation
Lei Zhou: China National Center for Bioinformation
Peizhuo Wang: Xidian University
Zhaoqi Liu: China National Center for Bioinformation

Nature Communications, 2025, vol. 16, issue 1, 1-18

Abstract: Abstract Alternative splicing (AS) plays a critical role in generating cellular transcriptomic heterogeneity. While single-cell RNA sequencing (scRNA-seq) has become a standard approach for exploring this heterogeneity, it remains challenging to accurately characterize splicing changes at the single-cell level due to high dropout rates, inevitable noise, and limited coverage. To address this, we developed SCSES (Single-Cell Splicing EStimation), a computational framework designed to enhance the AS profiles. SCSES infers and completes the missing splicing changes by sharing information across similar cells and events with data diffusion. Through systematic simulation studies, SCSES outperforms existing algorithms in recovering percent spliced-in (PSI) values and diversity across cell populations. When applied to various datasets, SCSES uncovers substantial splicing heterogeneity and cell subgroups with exclusive splicing patterns, which cannot be captured by conventional single-cell gene expression clustering. Together, our study provides SCSES as a valuable tool in deciphering splicing heterogeneity and is widely capable of handling different biological scenarios, species and sequencing platforms.

Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-025-64517-5 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-64517-5

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-025-64517-5

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().