ArticleProceedings of the National Academy of Sciences of the United States of America2014
Automated identification of stratifying signatures in cellular subpopulations.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 256 papers, 1 of them a synthesis that pooled it.
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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
256 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medical Treatment of Lung Cancer: Can Immune Cells Predict the Response? A Systematic Review.Frontiers in immunology · 2020Pooled it
- Trial
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- Single-Cell Immune Competency Signatures Associate with Survival in Phase II GVAX and CRS-207 Randomized Studies in Patients with Metastatic Pancreatic Cancer.Cancer immunology research · 2020Trial
- Multivariate Computational Analysis of Gamma Delta T Cell Inhibitory Receptor Signatures Reveals the Divergence of Healthy and ART-Suppressed HIV+ Aging.Frontiers in immunology · 2018Trial
- Pro-inflammatory Monocyte Phenotype and Cell-Specific Steroid Signaling Alterations in Unmedicated Patients With Major Depressive Disorder.Frontiers in immunology · 2018Trial
- Understanding the Immune Response Changes to Clinical Interventions for Epstein-Barr Virus Infection Prior to Lymphoma Development in Children After Organ Transplants (UNEARTH).Pediatric transplantation · 2026Article
- Distinct immunomodulatory effects of synthetic progestins compared with natural progesterone in human immune cells.ImmunoHorizons · 2026Article
- Self-explaining artificial intelligence for the classification of B cell non-Hodgkin lymphoma: A diagnostic decision support study.PLoS medicine · 2026Article
- Critical illness expands a transcriptionally distinct hypometabolic CD8bioRxiv : the preprint server for biology · 2026Article
- Immune profiling in orthopaedic diseases using mass cytometry : a narrative review of applications and future directions.Bone & joint research · 2026Article
- Application and characterization of the multiple instance learning framework in flow cytometry.Scientific reports · 2026Article
- Capturing the full spectrum of T cell responses with spectral flow cytometry.Oxford open immunology · 2026Review
- IRF4 Promotes Immune Evasion and Shapes the Tumor Microenvironment in Follicular Lymphoma.Blood cancer discovery · 2025Article
- Application of artificial intelligence in laboratory hematology: Advances, challenges, and prospects.Acta pharmaceutica Sinica. B · 2025Review
196 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Elucidation and examination of cellular subpopulations that display condition-specific behavior can play a critical contributory role in understanding disease mechanism, as well as provide a focal point for development of diagnostic criteria linking such a mechanism to clinical prognosis. Despite recent advancements in single-cell measurement technologies, the identification of relevant cell subsets through manual efforts remains standard practice. As new technologies such as mass cytometry increase the parameterization of single-cell measurements, the scalability and subjectivity inherent in manual analyses slows both analysis and progress. We therefore developed Citrus (cluster identification, characterization, and regression), a data-driven approach for the identification of stratifying subpopulations in multidimensional cytometry datasets. The methodology of Citrus is demonstrated through the identification of known and unexpected pathway responses in a dataset of stimulated peripheral blood mononuclear cells measured by mass cytometry. Additionally, the performance of Citrus is compared with that of existing methods through the analysis of several publicly available datasets. As the complexity of flow cytometry datasets continues to increase, methods such as Citrus will be needed to aid investigators in the performance of unbiased--and potentially more thorough--correlation-based mining and inspection of cell subsets nested within high-dimensional datasets.
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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.