ReviewMolecular systems biology2024
Building and analyzing metacells in single-cell genomics data.
Review in Molecular systems biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Hidden causal inference delineates dynamic lncRNA regulation in autism spectrum disorder.Briefings in bioinformatics · 2026Article
- Linking Genetic Risk to Disease-Relevant Cellular States via Metacell-Informed Modeling with ICePop.bioRxiv : the preprint server for biology · 2026Article
- Tissue-specific adaptation of human T cells is preserved during tissue inflammation.bioRxiv : the preprint server for biology · 2026Article
- CIRCE: a scalable Python package to predict cis-regulatory DNA interactions from single-cell chromatin accessibility data.Bioinformatics (Oxford, England) · 2026Article
- Bridging unpaired single-cell multimodal data for integrative analyses with SuperMap.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- mcRigor: A Statistical Software Package for Evaluating and Optimizing Metacell Partitioning in Single-Cell Data Analysis.Journal of computational biology : a journal of computational molecular cell biology · 2026Article
- Library size-stabilized metacells construction enhances co-expression network analysis in single-cell data.PLoS computational biology · 2025Article
- Insights, opportunities, and challenges provided by large cell atlases.Genome biology · 2025Review
- mcRigor: a statistical method to enhance the rigor of metacell partitioning in single-cell data analysis.Nature communications · 2025Article
- Diffusion-based generation of gene regulatory networks from scRNA-seq data with DigNet.Genome research · 2025Article
- SuperSpot: coarse graining spatial transcriptomics data into metaspots.Bioinformatics (Oxford, England) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The advent of high-throughput single-cell genomics technologies has fundamentally transformed biological sciences. Currently, millions of cells from complex biological tissues can be phenotypically profiled across multiple modalities. The scaling of computational methods to analyze and visualize such data is a constant challenge, and tools need to be regularly updated, if not redesigned, to cope with ever-growing numbers of cells. Over the last few years, metacells have been introduced to reduce the size and complexity of single-cell genomics data while preserving biologically relevant information and improving interpretability. Here, we review recent studies that capitalize on the concept of metacells-and the many variants in nomenclature that have been used. We further outline how and when metacells should (or should not) be used to analyze single-cell genomics data and what should be considered when analyzing such data at the metacell level. To facilitate the exploration of metacells, we provide a comprehensive tutorial on the construction and analysis of metacells from single-cell RNA-seq data ( https://github.com/GfellerLab/MetacellAnalysisTutorial ) as well as a fully integrated pipeline to rapidly build, visualize and evaluate metacells with different methods ( https://github.com/GfellerLab/MetacellAnalysisToolkit ).
Indexed as
Identifiers
What Socratic holds
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.