ArticleNAR genomics and bioinformatics2024
Comparative analysis of single-cell pathway scoring methods and a novel approach.
Article in NAR genomics and bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Ptbp1 Condensates With Phase Separation-Like Features in Cardiomyocyte Nuclei Regulate Splicing of Proliferative Genes in Neonatal Cardiomyocytes.Development, growth & differentiation · 2026Article
- Analytical Methods and Application of Single-Cell and Single-Nucleus Transcriptomics in the Study of Ischemic Stroke.Biomolecules · 2026Review
- Multi-task spatial distillation reveals cell-type-resolved programmed cell death landscapes in the human kidney.Briefings in bioinformatics · 2026Article
- scResponse: A Rank-Based Method for Identifying Cell States That Contribute to Immunotherapy Response by Single-Cell Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- An Insulin-Exosome-TNFAIP8 Axis Drives Stromal Fibrosis and Therapeutic Resistance in Pancreatic Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Development of a pediatric immune cell atlas and characterization of CD4+ T cells in food allergy.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2026Review
- Monocytes Defined by Platelet Interactions and Oxidative Stress Signaling Underlie HIV-Associated Atherosclerosis.Journal of the American Heart Association · 2026Article
- Robust and efficient annotation of cell states through gene signature scoring.Genome research · 2026Article
- UCell and pyUCell: single-cell gene signature scoring for R and Python.Bioinformatics (Oxford, England) · 2026Article
- Single nuclei and spatial profiling of sacrococcygeal teratomas reveals cellular composition and X inactivation heterogeneity.NPJ precision oncology · 2026Article
- Integrated multi omics and machine learning reveal mitochondrial immunometabolic networks in sepsis associated encephalopathy.Scientific reports · 2025Article
- Characterizing macrophage diversity in colorectal malignancies through single-cell genomics.Frontiers in immunology · 2025Review
- Chaperonins in Hepatocellular Carcinoma: Unveiling Their Role in Tumor Proliferation and Immune Modulation Through Multiomics Analysis.International journal of genomics · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Single-cell gene set analysis (scGSA) provides a useful approach for quantifying molecular functions and pathways in high-throughput transcriptomic data, facilitating the biological interpretation of complex human datasets. However, various factors such as gene set size, quality of the gene sets and the dropouts impact the performance of scGSA. To address these limitations, we present a single-cell Pathway Score (scPS) method to measure gene set activity at single-cell resolution. Furthermore, we benchmark our method with six other methods: AUCell, AddModuleScore, JASMINE, UCell, SCSE and ssGSEA. The comparison across all the methods using two different simulation approaches highlights the effect of cell count, gene set size, noise, condition-specific genes and zero imputation on their performance. The results of our study indicate that the scPS is comparable with other single-cell scoring methods and detects fewer false positives. Importantly, this work reveals critical variables in the scGSA.
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Registered trials
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