ArticleMethods in molecular biology (Clifton, N.J.)2019
Supervised Machine Learning with CITRUS for Single Cell Biomarker Discovery.
Article in Methods in molecular biology (Clifton, N.J.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
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- Single-cell and multi-omic characterization of ex vivo expanded ASTRLs from stable kidney transplant recipients reveals a regulatory T cell phenotype.Scientific reports · 2026Article
- Dissecting immunophenotypic diversity in multiple myeloma via mass cytometry: a call for harmonized gating strategies.Frontiers in immunology · 2025Review
- Tetracyclines enhance antitumor T-cell immunity via the Zap70 signaling pathway.Journal for immunotherapy of cancer · 2024Article
- Minimal Residual Disease in Acute Myeloid Leukemia: Old and New Concepts.International journal of molecular sciences · 2024Review
- Interleukin-21 promotes Type-1 activation and cytotoxicity of CD56Kidney international · 2023Article
- Prediction of Clinical Outcomes with Explainable Artificial Intelligence in Patients with Chronic Lymphocytic Leukemia.Current oncology (Toronto, Ont.) · 2023Article
- Cyclone: an accessible pipeline to analyze, evaluate, and optimize multiparametric cytometry data.Frontiers in immunology · 2023Article
- A Novel Humanized PD-1/PD-L1 Mouse Model Permits Direct Comparison of Antitumor Immunity Generated by Food and Drug Administration-Approved PD-1 and PD-L1 Inhibitors.ImmunoHorizons · 2023Article
- Impact of chronic alcohol exposure on conventional and regulatory murine T cell subsets.Frontiers in immunology · 2023Article
- Activated but functionally impaired memory Tregs are expanded in slow progressors to type 1 diabetes.Diabetologia · 2022Article
- CyTOFFrontiers in immunology · 2022Review
- Mass Cytometry in Hematologic Malignancies: Research Highlights and Potential Clinical Applications.Frontiers in oncology · 2021Review
- Advanced Flow Cytometry Analysis Algorithms for Optimizing the Detection of "Different From Normal" Immunophenotypes in Acute Myeloid Blasts.Frontiers in cell and developmental biology · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
CITRUS is a supervised machine learning algorithm designed to analyze single cell data, identify cell populations, and identify changes in the frequencies or functional marker expression patterns of those populations that are significantly associated with an outcome. The algorithm is a black box that includes steps to cluster cell populations, characterize these populations, and identify the significant characteristics. This chapter describes how to optimize the use of CITRUS by combining it with upstream and downstream data analysis and visualization tools.
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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.