ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2008
Analysis of flow cytometry data using an automatic processing tool.
Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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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.
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Who cites it
8 citing papers in PubMed, 21 citations in OpenAlex.
- A flow cytometry-based workflow for detection and quantification of anti-plasmodial antibodies in vaccinated and naturally exposed individuals.Malaria journal · 2012Trial
- High-throughput secondary screening at the single-cell level.Journal of laboratory automation · 2013Article
- Automatic B cell lymphoma detection using flow cytometry data.BMC genomics · 2013Article
- Data reduction for spectral clustering to analyze high throughput flow cytometry data.BMC bioinformatics · 2010Article
- Scalable analysis of flow cytometry data using R/Bioconductor.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2009Article
- A survey of flow cytometry data analysis methods.Advances in bioinformatics · 2009Article
- A chromatic explosion: the development and future of multiparameter flow cytometry.Immunology · 2008Review
- Maintenance of large subpopulations of differentiated CD8 T-cells two years after cytomegalovirus infection in Gambian infants.PloS one · 2008Article
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Authors and funding
5 authors at 2 institutions in 3 countries.
Funding
Abstract
In spite of recent advances in flow cytometry technology, most cytometry data is still analyzed manually which is labor-intensive for large datasets and prone to bias and inconsistency. We designed an automatic processing tool (APT) to rapidly and consistently define and describe cell populations across large datasets. Image processing, smoothing, and clustering algorithms were used to generate an expert system that automatically reproduces the functionality of commercial manual cytometry processing tools. The algorithms were developed using a dataset collected from CMV-infected infants and combined within a graphical user interface, to create the APT. The APT was used to identify regulatory T-cells in HIV-infected adults, based on expression of FOXP3. Results from the APT were compared directly with the manual analyses of five immunologists and showed close agreement, with a concordance correlation coefficient of 0.96 (95% CI 0.91-0.98). The APT was well accepted by users and able to process around 100 data files per hour. By applying consistent criteria to all data generated by a study, the APT can provide a level of objectivity that is difficult to match using conventional manual analysis.
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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.