Computational flow cytometry: helping to make sense of high-dimensional immunology data
By Yvan Saeys, S. van Gassen, B. Lambrecht. Nature reviews. Immunology, 2016
457 citations recorded by the source corpus.
Subfields: Immunology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/1d3a8b68d481f70dbf901fcdf1f50613152c4755
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In Immunology
- F. Mair
- Martin Prlic
- Florent Ginhoux
- M. Guilliams
- Yvan Saeys
- B. Lambrecht
- Evan W. Newell
- B. Malissen
In Molecular Biology
- Martin Prlic
- F. Mair
- Yvan Saeys
- Michael Poidinger
- Jonathan M. Irish
- B. Lambrecht
- Evan W. Newell
- S. van Gassen
Citations in the corpus
- Mass cytometry of follicular lymphoma tumors reveals intrinsic heterogeneity in proteins including HLA-DR and a deficit in non-malignant plasmablast and germinal center B cell populations (2017, methodology): “The dimensionality reduction similarity mapping tool viSNE (22) was used to create two-dimensional t-SNE visualizations of multidimensional cellular phenotypes (9,24,27).”
- OMIP-044: 28-color immunophenotyping of the human dendritic cell compartment (2018, methodology): “Given that exhaustive analysis using manual two-dimensional gating is not feasible (24,25), several novel approaches for exploratory analysis of high-dimensional single-cell data sets have been reported in the past years, among them t-stochastic neighbor embedding (t-SNE) (26,27), which can be used ”
- Unsupervised High-Dimensional Analysis Aligns Dendritic Cells across Tissues and Species (2016, methodology): “Recent progress in the unsupervised analysis of high-dimensional flow cytometry datasets has rendered the identification process of cell subsets more objective and more reproducible (Saeys et al., 2016).”
- SOM-based embedding improves efficiency of high-dimensional cytometry data analysis (2019, background): “Comprehensive reviews of the algorithms are available [19, 27, 10, 11].”
- Evaluation of UMAP as an alternative to t-SNE for single-cell data (2018, methodology): “Common such techniques[1] include Isomap, Diffusion Map and t-SNE[2] (also renamed viSNE[3]).”
- Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types (2017, methodology): “All these aspects are further demonstrated using a typical exploration work fl ow with Cytosplore +HSNE in the Supplementary Movie 1.”