ArticleNature methods2016
Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis.
Article in Nature methods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 230 papers, 2 of them syntheses that pooled it.
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
230 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Guidelines for bioinformatics of single-cell sequencing data analysis in Alzheimer's disease: review, recommendation, implementation and application.Molecular neurodegeneration · 2022Pooled it
- ERICH3: vesicular association and antidepressant treatment response.Molecular psychiatry · 2021Pooled it
- Antibody-drug conjugate engineering: from design to efficacy and safety.Signal transduction and targeted therapy · 2026Review
- PathwayBench: a multi-criterion benchmark of pseudobulk pathway activity scoring methods reveals rank-window competition as a mechanism of biological signal loss in single-cell RNA-seq.Research square · 2026Article
- PathwayEmbed: a computational tool to quantify intracellular signaling transduction states from transcriptomic data.Bioinformatics (Oxford, England) · 2026Article
- Macrophage-Fibroblast Crosstalk Shapes Wound Repair Signaling In Vitro.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Linking Genetic Risk to Disease-Relevant Cellular States via Metacell-Informed Modeling with ICePop.bioRxiv : the preprint server for biology · 2026Article
- Mosaic: Single-Cell Atlas of Stress.Cells · 2026Review
- MEAST: a novel framework for analyzing gene set stability in single cell transcriptomics.Scientific reports · 2026Article
- Single-nucleus brain transcriptomics reveals microglia dysfunction in multiple system atrophy.Nature communications · 2026Article
- Incorporating prior information in gene expression network-based cancer heterogeneity analysis.Biostatistics (Oxford, England) · 2025Article
- The Specification and Functional Maturation of Sub-Cerebral Projection Neurons Derived from Human Induced Pluripotent Stem Cells.Stem cells and development · 2025Article
- TAF1 is required for fetal but not adult hematopoiesis in mice.Developmental cell · 2025Article
- A comprehensive molecular atlas of the mesenchymal cell types in the mouse liver.EMBO reports · 2025Article
- SURF: A Self-Supervised Deep Learning Method for Reference-Free Deconvolution in Spatial Transcriptomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Single-cell RNA-sequencing of circulating tumour cells: A practical guide to workflow and translational applications.Cancer metastasis reviews · 2025Review
- Advancing biological understanding of cellular senescence with computational multiomics.Nature genetics · 2025Review
- gwSPADE: gene frequency-weighted reference-free deconvolution in spatial transcriptomics.Nucleic acids research · 2025Article
- Unified mass imaging maps the lipidome of vertebrate development.Nature methods · 2025Article
- Mouse-Specific Single cell cytokine activity prediction and Estimation (MouSSE).PLoS computational biology · 2025Article
170 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
The transcriptional state of a cell reflects a variety of biological factors, from cell-type-specific features to transient processes such as the cell cycle, all of which may be of interest. However, identifying such aspects from noisy single-cell RNA-seq data remains challenging. We developed pathway and gene set overdispersion analysis (PAGODA) to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability among measured cells.
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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 OpenQuestion graph.