ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2011
Rapid cell population identification in flow cytometry data.
Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers.
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Who cites it
91 citing papers in PubMed.
- Label-Free and High-Throughput Quantification of Nanoparticle-Cell Interactions at the Single-Cell Level with Flow Cytometry.Analytical chemistry · 2026Article
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- Computationally efficient multi-sample flow cytometry data analysis using Gaussian mixture models.BMC bioinformatics · 2025Article
- cytoGPNet: Enhancing clinical outcome prediction accuracy using longitudinal cytometry data in small cohort studies.Patterns (New York, N.Y.) · 2025Article
- Ultra-high-scale cytometry-based cellular interaction mapping.Nature methods · 2025Article
- Integrated workflow for analysis of immune enriched spatial proteomic data with IMmuneCite.Scientific reports · 2025Article
- Comprehensive evaluation and practical guideline of gating methods for high-dimensional cytometry data: manual gating, unsupervised clustering, and auto-gating.Briefings in bioinformatics · 2024Article
- ImmCellTyper facilitates systematic mass cytometry data analysis for deep immune profiling.eLife · 2024Article
- Mapping the single cell spatial immune landscapes of the melanoma microenvironment.Clinical & experimental metastasis · 2024Review
- Cytomulate: accurate and efficient simulation of CyTOF data.Genome biology · 2023Article
- Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.Proteomics · 2023Article
- A cell-level discriminative neural network model for diagnosis of blood cancers.Bioinformatics (Oxford, England) · 2023Article
- CRUSTY: a versatile web platform for the rapid analysis and visualization of high-dimensional flow cytometry data.Nature communications · 2023Article
- Cross-species comparative analysis of single presynapses.Scientific reports · 2023Article
- Computational Methods for Single-Cell Proteomics.Annual review of biomedical data science · 2023Review
- Flow Cytometry: The Next Revolution.Cells · 2023Review
- A Bayesian feature allocation model for identifying cell subpopulations using CyTOF data.Journal of the Royal Statistical Society. Series C, Applied statistics · 2023Article
- The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions.Immunoinformatics (Amsterdam, Netherlands) · 2023Review
- Non-inhibitory levels of oxygen during cultivation increase freeze-drying stress tolerance inFrontiers in microbiology · 2023Article
- Revisiting transplant immunology through the lens of single-cell technologies.Seminars in immunopathology · 2023Review
31 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
Abstract
We have developed flowMeans, a time-efficient and accurate method for automated identification of cell populations in flow cytometry (FCM) data based on K-means clustering. Unlike traditional K-means, flowMeans can identify concave cell populations by modelling a single population with multiple clusters. flowMeans uses a change point detection algorithm to determine the number of sub-populations, enabling the method to be used in high throughput FCM data analysis pipelines. Our approach compares favorably to manual analysis by human experts and current state-of-the-art automated gating algorithms. flowMeans is freely available as an open source R package through Bioconductor.
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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.