ReviewCells2020
Single-Cell RNA Sequencing and Its Combination with Protein and DNA Analyses.
Review in Cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 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
38 citing papers in PubMed.
- Senescent epithelial cells remodel the tumor microenvironment and drive early LUAD progression: a multiomics risk model and single-cell analysis.Cellular and molecular life sciences : CMLS · 2026Article
- Recent advances in m6A RNA modification in hepatocellular carcinoma: from mechanisms to therapeutic potential.Frontiers in molecular biosciences · 2026Review
- Article
- Review
- The Multifaceted Role of L-Type Amino Acid Transporter 1 at the Blood-Brain Barrier: Structural Implications and Therapeutic Potential.Molecular neurobiology · 2025Review
- Integrated Transcriptomic Analysis Leveraging Single-Cell and Bulk RNA Sequencing Data to Uncover Pyroptosis-Related Prognostic Signatures in HCC.Journal of hepatocellular carcinoma · 2025Article
- Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research.Acta biochimica Polonica · 2025Review
- Advanced omics approaches in liver transplant settings: current applications and future prospectives.Frontiers in immunology · 2025Review
- Identification of tumor associated neutrophils-related genes in triple-negative breast cancer for predicting prognosis and therapeutic response through integrated single-cell analysis.Frontiers in immunology · 2025Article
- Single-cell RNA sequencing in diabetic kidney disease: a literature review.Renal failure · 2024Review
- Single-cell multi-omics in the study of digestive system cancers.Computational and structural biotechnology journal · 2024Review
- Harnessing Artificial Intelligence in Multimodal Omics Data Integration: Paving the Path for the Next Frontier in Precision Medicine.Annual review of biomedical data science · 2024Review
- Exploring the current landscape of single-cell RNA sequencing applications in gastric cancer research.Journal of cellular and molecular medicine · 2024Review
- Single-cell RNA sequencing to understand host-virus interactions.Virologica Sinica · 2024Review
- Innovative aspects and applications of single cell technology for different diseases.American journal of cancer research · 2024Review
- Functional genomics in Spiralia.Briefings in functional genomics · 2023Article
- The regulatory role of cancer stem cell marker gene CXCR4 in the growth and metastasis of gastric cancer.NPJ precision oncology · 2023Article
- Advances in novel strategies for isolation, characterization, and analysis of CTCs and ctDNA.Therapeutic advances in medical oncology · 2023Review
- The utilization of single-cell sequencing technology in investigating the immune microenvironment of ccRCC.Frontiers in immunology · 2023Review
- Single-cell RNA sequencing in oral science: Current awareness and perspectives.Cell proliferation · 2022Review
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
Heterogeneity in cell populations poses a significant challenge for understanding complex cell biological processes. The analysis of cells at the single-cell level, especially single-cell RNA sequencing (scRNA-seq), has made it possible to comprehensively dissect cellular heterogeneity and access unobtainable biological information from bulk analysis. Recent efforts have combined scRNA-seq profiles with genomic or proteomic data, and show added value in describing complex cellular heterogeneity than transcriptome measurements alone. With the rising demand for scRNA-seq for biomedical and clinical applications, there is a strong need for a timely and comprehensive review on the scRNA-seq technologies and their potential biomedical applications. In this review, we first discuss the latest state of development by detailing each scRNA-seq technology, including both conventional and microfluidic technologies. We then summarize their advantages and limitations along with their biomedical applications. The efforts of integrating the transcriptome profile with highly multiplexed proteomic and genomic data are thoroughly reviewed with results showing the integrated data being more informative than transcriptome data alone. Lastly, the latest progress toward commercialization, the remaining challenges, and future perspectives on the development of scRNA-seq technologies are briefly discussed.
Indexed as
Identifiers
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.