ArticleBriefings in bioinformatics2024
irGSEA: the integration of single-cell rank-based gene set enrichment analysis.
Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers.
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Who cites it
106 citing papers in PubMed.
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- Integrative single-cell and spatial transcriptomics combined with machine learning to discover complement-associated biomarkers in temporal lobe epilepsy with hippocampal sclerosis.Functional & integrative genomics · 2026Article
- Multi-task spatial distillation reveals cell-type-resolved programmed cell death landscapes in the human kidney.Briefings in bioinformatics · 2026Article
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- Cochlear nucleus spatial transcriptomes of normal and hearing loss mice reveal a critical role of Spp1 in bushy cells.Cell research · 2026Article
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- Integrative spatiotemporal transcriptomics identifies a liver metastasis-related initial cell population associated with the SEMA3A-NRP1 axis in pancreatic ductal adenocarcinoma.Journal of translational medicine · 2026Article
- Single-cell and spatial transcriptomics identify SPP1 + trophoblast necroptosis as a potential contributor to late-onset preeclampsia via SPP1-CD44-mediated interaction with macrophages.Journal of translational medicine · 2026Article
- Exploring molecular signatures of senescence with marker, an R Toolkit for evaluating gene sets as phenotypic markers.NAR genomics and bioinformatics · 2026Article
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- Integrating single-cell and bulk transcriptomic analyses to explore key lactylation-related genes in benign prostatic hyperplasia.Scientific reports · 2026Article
- Targeting VEGF signaling and stromal remodeling enhances chemoimmunotherapy efficacy in esophageal cancer.Journal for immunotherapy of cancer · 2026Article
- Single-Cell Sequencing Reveals That CCL2+ Adipose-Derived Stem Cells Promote Diabetic Wound Healing Through the CCL2-ACKR1 Signaling Axis.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Single-cell and machine learning-integrated bulk RNA-seq analysis reveals TKT as an oxidative stress-associated diagnostic biomarker in acute myocardial infarction.Human genomics · 2026Article
46 more citing papers are in PubMed but not listed here.
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Authors and funding
12 authors.
Funding
Abstract
irGSEA is an R package designed to assess the outcomes of various gene set scoring methods when applied to single-cell RNA sequencing data. This package incorporates six distinct scoring methods that rely on the expression ranks of genes, emphasizing relative expression levels over absolute values. The implemented methods include AUCell, UCell, singscore, ssGSEA, JASMINE and Viper. Previous studies have demonstrated the robustness of these methods to variations in dataset size and composition, generating enrichment scores based solely on the relative gene expression of individual cells. By employing the robust rank aggregation algorithm, irGSEA amalgamates results from all six methods to ascertain the statistical significance of target gene sets across diverse scoring methods. The package prioritizes user-friendliness, allowing direct input of expression matrices or seamless interaction with Seurat objects. Furthermore, it facilitates a comprehensive visualization of results. The irGSEA package and its accompanying documentation are accessible on GitHub (https://github.com/chuiqin/irGSEA).
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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.