ArticleGenome research2024
Accurate estimation of pathway activity in single cells for clustering and differential analysis.
Article in Genome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Renin cells orchestrate a neuro-endocrine microenvironment of the kidney arterial tree in health and disease.JCI insight · 2026Article
- NADThe EMBO journal · 2026Article
- Identification and Characterization of Cancer-Related Risk Metabolic Subpathways Reveal Their Functional Significance in Cancer.International journal of molecular sciences · 2026Article
- Progressive neurodegeneration in human dorsal root ganglion from diabetes to painful neuropathy.bioRxiv : the preprint server for biology · 2026Article
- FUNCellA: A Tool for Single-Sample Enrichment Analysis and Relative Pathway Activity Estimation in Single-Cell RNA Sequencing Data.Computational and structural biotechnology journal · 2026Article
- Pathway Analysis Interpretation in the Multi-Omic Era.Biotech (Basel (Switzerland)) · 2025Review
- Hypoxia-Induced Metabolic Reprogramming and Markings of Cell Fate in Concentric Arterial Hypertrophy.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Inferring which and how biological pathways and gene sets change is a key question in many studies that utilize single-cell RNA sequencing. Typically, these questions are addressed by quantifying the enrichment of known gene sets in lists of genes derived from global analysis. Here we offer SiPSiC, a new method to infer pathway activity in every single cell. This allows more sensitive differential analysis and utilization of pathway scores to cluster cells and compute UMAP or other similar projections. We apply our method to COVID-19, lung adenocarcinoma and glioma data sets, and demonstrate its utility. SiPSiC analysis results are consistent with findings reported in previous studies in many cases, but SiPSiC also reveals the differential activity of novel pathways, enabling us to suggest new mechanisms underlying the pathophysiology of these diseases and demonstrating SiPSiC's high accuracy and sensitivity in detecting biological function and traits. In addition, we demonstrate how it can be used to better classify cells based on activity of biological pathways instead of single genes and its ability to overcome patient-specific artifacts.
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Registered trials
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 Socratic graph.