ReviewNucleic acids research2014
Single-cell RNA-seq: advances and future challenges.
Review in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 444 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
444 citing papers in PubMed.
- A statistical framework for disease classification with scRNA-Seq Data.bioRxiv : the preprint server for biology · 2026Article
- GEM-GPT Enables Personalized Cell Type-Resolved Therapeutic Design for Systems Pharmacology.bioRxiv : the preprint server for biology · 2026Article
- Single-Cell RNA-Seq Reveals Chromosomal Instability-Associated Transcriptomic Profiles in Breast Cancer.Biomedicines · 2026Article
- Multiomics identifies a prognostic signature and SPIB as a potential regulator of gastric cancer lymph node metastasis.iScience · 2026Article
- Identifying phenotype-genotype-function coupling in 3D organoid imaging using Shape, Appearance and Motion Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- Single-bacterium RNA-seq protocol to uncover heterogeneous expression of coding and noncoding genes in Bacteroides thetaiotaomicron.STAR protocols · 2026Article
- Multi-Omics and Machine Learning Integration Identifies Key Endothelial Modules in Carotid Artery Stenosis.Journal of clinical laboratory analysis · 2026Article
- Review
- Spatial single-cell proteotyping reveals immunotherapy-resistant features within the complex tumor microenvironment of metastatic NSCLC.The Journal of clinical investigation · 2026Article
- Comparison between a conventional tool and deep learning models for RNA velocity analysis of scRNA-Seq data.Molecular genetics and genomics : MGG · 2026Article
- Hybrid Encoding and Adaptive Guidance for Enhanced Single-Cell Multi-omics Clustering.Interdisciplinary sciences, computational life sciences · 2026Article
- RegFormer: a single-cell foundation model powered by gene regulatory hierarchies.Nature communications · 2026Article
- Evaluating the Utilities of Foundation Models in Single-Cell Data Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Single-cell chromatin accessibility and cis-regulatory element analyses in plants using the scPlantReg platform.Nature plants · 2026Article
- Embeddings from language models are good learners for single-cell data analysis.Patterns (New York, N.Y.) · 2026Article
- Deciphering the Heterogeneity of Pulmonary Macrophages in Response to Fine Particles.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Analyzing cell-type-specific isoform expression using IsoDiffR and long-read single-cell RNA sequencing.Bioinformatics (Oxford, England) · 2026Article
- RNA-Seq and XAI Can be Used as Tools to Aid Pathologists in the Process of Cancer Diagnosis.Methods in molecular biology (Clifton, N.J.) · 2026Article
- circPVT1 regulates EMT and induces macrophage polarization to promotes the progression of renal cell carcinoma.Frontiers in immunology · 2026Article
- Single-cell RNA-seq reveals the piperlongumine is a potential drug for ischemic stroke.PloS one · 2026Article
384 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phenotypically identical cells can dramatically vary with respect to behavior during their lifespan and this variation is reflected in their molecular composition such as the transcriptomic landscape. Single-cell transcriptomics using next-generation transcript sequencing (RNA-seq) is now emerging as a powerful tool to profile cell-to-cell variability on a genomic scale. Its application has already greatly impacted our conceptual understanding of diverse biological processes with broad implications for both basic and clinical research. Different single-cell RNA-seq protocols have been introduced and are reviewed here-each one with its own strengths and current limitations. We further provide an overview of the biological questions single-cell RNA-seq has been used to address, the major findings obtained from such studies, and current challenges and expected future developments in this booming field.
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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.