ArticleNucleic acids research2025
SCIG: Machine learning uncovers cell identity genes in single cells by genetic sequence codes.
Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Single-Cell Analysis Reveals a Critical Role for Macrophage Epsins in Regulating the Origin of Foam Cells in Atherosclerosis.Arteriosclerosis, thrombosis, and vascular biology · 2025Article
- Transcription factor 4 maintains endothelial cell identity by inhibiting endothelial to mesenchymal transition.Nucleic acids research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Deciphering cell identity genes is pivotal to understanding cell differentiation, development, and cell identity dysregulation involving diseases. Here, we introduce SCIG, a machine-learning method to uncover cell identity genes in single cells. In alignment with recent reports that cell identity genes (CIGs) are regulated with unique epigenetic signatures, we found CIGs exhibit distinctive genetic sequence signatures, e.g. unique enrichment patterns of cis-regulatory elements. Using these genetic sequence signatures, along with gene expression information from single-cell RNA-seq data, SCIG uncovers the identity genes of a cell without a need for comparison to other cells. CIG score defined by SCIG surpassed expression value in network analysis to reveal the master transcription factors (TFs) regulating cell identity. Applying SCIG to the human endothelial cell atlas revealed that the tissue microenvironment is a critical supplement to master TFs for cell identity refinement. SCIG is publicly available at https://doi.org/10.5281/zenodo.14726426 , offering a valuable tool for advancing cell differentiation, development, and regenerative medicine research.
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Registered trials
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