ArticleBMC bioinformatics2010
The curvHDR method for gating flow cytometry samples.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Human microglia regional heterogeneity and phenotypes determined by multiplexed single-cell mass cytometry.Nature neuroscience · 2019Article
- Less effective selection leads to larger genomes.Genome research · 2017Article
- Toward deterministic and semiautomated SPADE analysis.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2017Article
- Response of Prochlorococcus to varying CO2:O2 ratios.The ISME journal · 2015Article
- Computational prediction of manually gated rare cells in flow cytometry data.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2015Article
- SWIFT-scalable clustering for automated identification of rare cell populations in large, high-dimensional flow cytometry datasets, part 1: algorithm design.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2014Article
- Application of user-guided automated cytometric data analysis to large-scale immunoprofiling of invariant natural killer T cells.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
- Soluble guanylate cyclase modulates alveolarization in the newborn lung.American journal of physiology. Lung cellular and molecular physiology · 2013Article
- GenePattern flow cytometry suite.Source code for biology and medicine · 2013Article
- Critical assessment of automated flow cytometry data analysis techniques.Nature methods · 2013Article
- RchyOptimyx: cellular hierarchy optimization for flow cytometry.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2012Article
- flowPeaks: a fast unsupervised clustering for flow cytometry data via K-means and density peak finding.Bioinformatics (Oxford, England) · 2012Article
- A framework for analytical characterization of monoclonal antibodies based on reactivity profiles in different tissues.Bioinformatics (Oxford, England) · 2011Article
- Optimizing transformations for automated, high throughput analysis of flow cytometry data.BMC bioinformatics · 2010Article
- Data reduction for spectral clustering to analyze high throughput flow cytometry data.BMC bioinformatics · 2010Article
- Unfold High-Dimensional Clouds for Exhaustive Gating of Flow Cytometry Data.IEEE/ACM transactions on computational biology and bioinformaticsArticle
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundHigh-throughput flow cytometry experiments produce hundreds of large multivariate samples of cellular characteristics. These samples require specialized processing to obtain clinically meaningful measurements. A major component of this processing is a form of cell subsetting known as gating. Manual gating is time-consuming and subjective. Good automatic and semi-automatic gating algorithms are very beneficial to high-throughput flow cytometry.
resultsWe develop a statistical procedure, named curvHDR, for automatic and semi-automatic gating. The method combines the notions of significant high negative curvature regions and highest density regions and has the ability to adapt well to human-perceived gates. The underlying principles apply to dimension of arbitrary size, although we focus on dimensions up to three. Accompanying software, compatible with contemporary flow cytometry infor-matics, is developed.
conclusionThe method is seen to adapt well to nuances in the data and, to a reasonable extent, match human perception of useful gates. It offers big savings in human labour when processing high-throughput flow cytometry data whilst retaining a good degree of efficacy.
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