ArticleMethods (San Diego, Calif.)2018
High throughput automated analysis of big flow cytometry data.
Article in Methods (San Diego, Calif.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
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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, 1 synthesis or guideline pooled it.
- Automated and reproducible cell identification in mass cytometry using neural networks.Briefings in bioinformatics · 2023Pooled it
- Automatic classification of circulating blood cell clusters based on multi-channel flow cytometry imaging.Engineering applications of artificial intelligence · 2026Article
- Automatic Classification of Circulating Blood Cell Clusters based on Multi-channel Flow Cytometry Imaging.bioRxiv : the preprint server for biology · 2025Article
- SingletSeeker: An unsupervised clustering approach for automated singlet discrimination in cytometry.Cytometry. Part B, Clinical cytometry · 2025Article
- Investigating Vα7.2International journal of molecular sciences · 2024Article
- Validation of Artificial Intelligence (AI)-Assisted Flow Cytometry Analysis for Immunological Disorders.Diagnostics (Basel, Switzerland) · 2024Article
- flowSim: Near duplicate detection for flow cytometry data.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2023Article
- CRUSTY: a versatile web platform for the rapid analysis and visualization of high-dimensional flow cytometry data.Nature communications · 2023Article
- Flow Cytometry: The Next Revolution.Cells · 2023Review
- COVID-19: Using high-throughput flow cytometry to dissect clinical heterogeneity.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2023Review
- AliGater: a framework for the development of bioinformatic pipelines for large-scale, high-dimensional cytometry data.Bioinformatics advances · 2023Article
- Searching for a technology-driven acute rheumatic fever test: the START study protocol.BMJ open · 2021Article
- Article
- Machine Learning of Discriminative Gate Locations for Clinical Diagnosis.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2020Article
- Systems Biology Methods Applied to Blood and Tissue for a Comprehensive Analysis of Immune Response to Hepatitis B Vaccine in Adults.Frontiers in immunology · 2020Observational
- High-throughput phenotyping reveals expansive genetic and structural underpinnings of immune variation.Nature immunology · 2020Article
- Improving the Quality and Reproducibility of Flow Cytometry in the Lung. An Official American Thoracic Society Workshop Report.American journal of respiratory cell and molecular biology · 2019Article
- Flow-Cytometric Monitoring of Minimal Residual Disease in Pediatric Patients With Acute Myeloid Leukemia: Recent Advances and Future Strategies.Frontiers in pediatrics · 2019Review
- Ways Forward for Tolerance-Inducing Cellular Therapies- an AFACTT Perspective.Frontiers in immunology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
The rapid expansion of flow cytometry applications has outpaced the functionality of traditional manual analysis tools used to interpret flow cytometry data. Scientists are faced with the daunting prospect of manually identifying interesting cell populations in 50-dimensional datasets, equalling the complexity previously only reached in mass cytometry. Data can no longer be analyzed or interpreted fully by manual approaches. While automated gating has been the focus of intense efforts, there are many significant additional steps to the analytical pipeline (e.g., cleaning the raw files, event outlier detection, extracting immunophenotypes). We review the components of a customized automated analysis pipeline that can be generally applied to large scale flow cytometry data. We demonstrate these methodologies on data collected by the International Mouse Phenotyping Consortium (IMPC).
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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.