ReviewGenome medicine2017
A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications.
Review in Genome medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 629 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
629 citing papers in PubMed.
- Preparation of Postmortem Human Formalin-Fixed Paraffin-Embedded Frontal Cortex Tissue for Profiling Pyramidal Neurons Via Digital Spatial Profiling.Methods in molecular biology (Clifton, N.J.) · 2027Article
- From spectroscopic analysis to clinical imaging: emerging applications and persistent challenges of raman spectroscopy in CTCs-based liquid biopsies.Annals of medicine · 2026Review
- Scoparone protects against acetaminophen-induced acute liver injury: Insights from In vivo experiments and RNA sequencing.Biochemistry and biophysics reports · 2026Article
- Trustworthy Agentic AI in Bioinformatics: From Workflow Automation to Traceable and Validated Biological Inference.Biology · 2026Review
- Multi-Technique Integration Identifies O-GlcNAc Transferase in Fibroblast-Like Synoviocytes as a Therapeutic Target for Rheumatoid Arthritis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Single-cell RNA sequencing: a powerful tool to study heterogeneity in papillary and anaplastic thyroid carcinoma.European thyroid journal · 2026Review
- In Vitro Single-Cell Transcriptomic Profiling of Cultured Stem Cells From Apical Papilla and Dental Pulp Stem Cells: Unveiling Cellular Heterogeneity.International dental journal · 2026Article
- Multiscale learning of gene network-driven phenotypic dynamics of single cells.Molecular systems biology · 2026Article
- Mapping the path to clinical implementation of multi-omics.Nature genetics · 2026Review
- iDCF: Interpretable deconvolution of cell fractions via biologically-informed deep learning using scRNA-seq data.PLoS computational biology · 2026Article
- An Optimized Mechanical Peeling Protocol for Mouse Corneal Endothelium.Bioengineering (Basel, Switzerland) · 2026Article
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Exploring peripheral immune mechanisms and potential therapeutic drugs for Alzheimer's disease.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Understanding nerve-tumor interactions: From basic biology to therapeutic innovation.Genes & diseases · 2026Review
- Integrating Single-Cell Sequencing and Proteomics to Unravel Stem Cell Heterogeneity: Implications for Precision Regenerative Medicine.Stem cell reviews and reports · 2026Review
- Single-nucleus analysis of menstrual fluid highlights gene expression differences in epithelial cells of endometriosis donors.BMC medicine · 2026Article
- Cell type-specific contextualisation of the human phenome: towards the systematic treatment of all rare diseases.Genome medicine · 2026Article
- Single-Cell Omics Advances in Understanding Tissue Development and Complex Trait Formation in Sheep and Goats.Animals : an open access journal from MDPI · 2026Review
- Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.Journal of ovarian research · 2026Review
- Cellular immunology data enable clinical severity prediction via supervised machine learning.iScience · 2026Article
569 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
Abstract
RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative analysis of messenger RNA molecules in a biological sample and is useful for studying cellular responses. RNA-seq has fueled much discovery and innovation in medicine over recent years. For practical reasons, the technique is usually conducted on samples comprising thousands to millions of cells. However, this has hindered direct assessment of the fundamental unit of biology-the cell. Since the first single-cell RNA-sequencing (scRNA-seq) study was published in 2009, many more have been conducted, mostly by specialist laboratories with unique skills in wet-lab single-cell genomics, bioinformatics, and computation. However, with the increasing commercial availability of scRNA-seq platforms, and the rapid ongoing maturation of bioinformatics approaches, a point has been reached where any biomedical researcher or clinician can use scRNA-seq to make exciting discoveries. In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation.
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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.