ReviewTransplantation2019
Single-cell Transcriptomics and Solid Organ Transplantation.
Review in Transplantation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed.
- Pre-transplant TCR Network Topology Predicts Kidney Allograft Rejection Independent of HLA Mismatch.bioRxiv : the preprint server for biology · 2026Article
- Transforming multi-omics data into images for disease classification: A review of techniques and tools.Journal of pathology informatics · 2026Review
- Transforming heart transplantation care with multi-omics insights.Journal of translational medicine · 2025Review
- The single-cell revolution in transplantation: high-resolution mapping of graft rejection, tolerance, and injury.Frontiers in immunology · 2025Review
- Application of spatial-omics to the classification of kidney biopsy samples in transplantation.Nature reviews. Nephrology · 2024Review
- Transcriptional Profiling Underscores the Role of Preprocurement Allograft Metabolism and Innate Immune Status on Outcomes in Human Liver Transplantation.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024Article
- Single nuclei transcriptomics delineates complex immune and kidney cell interactions contributing to kidney allograft fibrosis.Kidney international · 2023Article
- Robust segregation of donor and recipient cells from single-cell RNA-sequencing of transplant samples.Frontiers in transplantation · 2023Article
- An optimized protocol for single nuclei isolation from clinical biopsies for RNA-seq.Scientific reports · 2022Article
- Kidney cell type-specific changes in the chromatin and transcriptome landscapes following epithelialPhysiological genomics · 2022Article
- Detection of infiltrating fibroblasts by single-cell transcriptomics in human kidney allografts.PloS one · 2022Article
- T Cells With ActivatedFrontiers in immunology · 2022Article
- Cancer Risk and Mutational Patterns Following Organ Transplantation.Frontiers in cell and developmental biology · 2022Review
- Single-Cell RNA sequencing reveals immune cell dynamics and local intercellular communication in acute murine cardiac allograft rejection.Theranostics · 2022Article
- Single-cell transcriptomic identified HIF1A as a target for attenuating acute rejection after heart transplantation.Basic research in cardiology · 2021Article
- Advances in single-cell sequencing: insights from organ transplantation.Military Medical Research · 2021Review
- Maintenance Immunosuppression in Solid Organ Transplantation: Integrating Novel Pharmacodynamic Biomarkers to Inform Calcineurin Inhibitor Dose Selection.Clinical pharmacokinetics · 2020Review
- Single cell transcriptomics of mouse kidney transplants reveals a myeloid cell pathway for transplant rejection.JCI insight · 2020Article
- Banff Digital Pathology Working Group: Going digital in transplant pathology.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Single-cell RNA sequencing (scRNA-seq) allows the measurement of transcriptomes from individual cells providing new insights into complex biological systems. scRNA-seq has enabled the identification of rare cell types, new cell states, and intercellular communication networks that may be masked by traditional bulk transcriptional profiling. Researchers are increasingly using scRNA-seq to comprehensively characterize complex organs in health and disease. The diversity of immune cell types, some present at low frequency, in a transplanted organ undergoing rejection makes scRNA-seq ideally suited to characterize transplant pathologies because it can quantify subtle transcriptional differences between rare cell types. In this review, we discuss single-cell sequencing methods and their application in transplantation to date, current challenges, and future directions. We believe that the remarkably rapid pace of technological development in this field makes it likely that single-cell technologies such as scRNA-seq will have an impact on clinical transplantation within a decade.
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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.