ReviewTranscription
Approaches for single-cell RNA sequencing across tissues and cell types.
Review in Transcription. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Article
- From single cell analysis to 3D micro physiological systems: microfluidic tools integrating cancer cell targets for delineating natural killer cell biology.Microsystems & nanoengineering · 2026Review
- High-resolution single-cell sequencing of trans-spliced mRNA.Nature protocols · 2026Review
- Single-cell RNA sequencing in stroke and traumatic brain injury: Current achievements, challenges and future perspectives on transcriptomic profiling.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026Review
- CapMux: a Snakemake pipeline for early demultiplexing of split-pool scRNA-seq data into sample-resolved outputs.Frontiers in bioinformatics · 2026Article
- Screening Potential Diagnostic Biomarkers of Lung Adenocarcinoma Related to Immune Infiltration Based on Single-Cell Proteomic Integration Analysis.Canadian respiratory journal · 2026Article
- Plate-based 10X Genomics-compatible single-cell RNA-sequencing based on Smart-seq3xpress.BMC genomics · 2025Article
- Review
- Concurrent nanotherapeutics and regulatory updates for the management of amyotrophic lateral sclerosis: a focused review for orphan drug (Tofersen).Orphanet journal of rare diseases · 2025Review
- DiSTect: a Bayesian model for disease-associated gene discovery and prediction in spatial transcriptomics.Bioinformatics (Oxford, England) · 2025Article
- Single-Cell Transcriptomics in Inherited Retinal Dystrophies: Current Findings and Emerging Perspectives.Genes · 2025Review
- Article
- Comparison of spatial transcriptomics technologies using tumor cryosections.Genome biology · 2025Article
- Bioinformatics perspectives on transcriptomics: A comprehensive review of bulk and single-cell RNA sequencing analyses.Quantitative biology (Beijing, China) · 2025Review
- Allometry of cell types in planarians by single-cell transcriptomics.Science advances · 2025Article
- Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research.Acta biochimica Polonica · 2025Review
- Advances in long-read single-cell transcriptomics.Human genetics · 2024Review
- How to explore what is hidden? A review of techniques for vascular tissue expression profile analysis.Plant methods · 2023Review
- Enhancing sensitivity and versatility of Tn5-based single cell omics.Frontiers in epigenetics and epigenomics · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell sequencing of RNA (scRNA-seq) has advanced our understanding of cellular heterogeneity and signaling in developmental biology and disease. A large number of complementary assays have been developed to profile transcriptomes of individual cells, also in combination with other readouts, such as chromatin accessibility or antibody-based analysis of protein surface markers. As scRNA-seq technologies are advancing fast, it is challenging to establish robust workflows and up-to-date protocols that are best suited to address the large range of research questions. Here, we review scRNA-seq techniques from mRNA end-counting to total RNA in relation to their specific features and outline the necessary sample preparation steps and quality control measures. Based on our experience in dealing with the continuously growing portfolio from the perspective of a central single-cell facility, we aim to provide guidance on how workflows can be best automatized and share our experience in coping with the continuous expansion of scRNA-seq techniques.
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What OpenQuestion 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 OpenQuestion graph.