ReviewRenal failure2025
Kidney diseases and single-cell sequencing research: a bibliometric analysis from 2015 to 2024.
Review in Renal failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- PRDM16 as a Multifaceted Pharmacological Target in Kidney Diseases: From Epigenetic Mechanisms to Therapeutic Strategies.Pharmaceuticals (Basel, Switzerland) · 2026Review
- The chemokine network in lupus nephritis: pathogenesis, targeted therapies, and future directions.Frontiers in pharmacology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSingle-cell RNA sequencing (scRNA-seq) has revolutionized kidney disease research by enabling high-resolution transcriptomic analysis at the cellular level. This technology can overcome the limitations of traditional bulk-sequencing; reveal disease-progression trajectories, intercellular communication networks, and cellular heterogeneity; and provide crucial insights into disease mechanisms, thereby facilitating the development of targeted therapies and personalized treatment strategies. We conducted a bibliometric analysis of publications describing the use of scRNA-seq in kidney disease research from 2015 to 2024 using the Web of Science Core Collection (WoSCC) database. Data analysis was performed using the R packages Bibliometrix, VOSviewer, and CiteSpace to systematically evaluate the research landscape and emerging trends.
resultsA total of 1,210 publications on scRNA-seq in kidney diseases were identified. China was the largest contributor among the participating countries, demonstrating consistent annual growth in publication numbers. The major research institutions were Harvard Medical School, Sun Yat-sen University, and Shanghai Jiao Tong University. Most articles in this field were published by
conclusionThis bibliometric analysis revealed the rapid growth and evolving landscape of scRNA-seq applications in kidney disease research and highlighted promising opportunities for understanding disease mechanisms and developing personalized therapeutic strategies.
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.