Cargando…
Background fluorescence and spreading error are major contributors of variability in high‐dimensional flow cytometry data visualization by t‐distributed stochastic neighboring embedding
Multidimensional single‐cell analysis requires approaches to visualize complex data in intuitive 2D graphs. In this regard, t‐distributed stochastic neighboring embedding (tSNE) is the most popular algorithm for single‐cell RNA sequencing and cytometry by time‐of‐flight (CyTOF), but its application...
Autores principales: | Mazza, Emilia Maria Cristina, Brummelman, Jolanda, Alvisi, Giorgia, Roberto, Alessandra, De Paoli, Federica, Zanon, Veronica, Colombo, Federico, Roederer, Mario, Lugli, Enrico |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6175173/ https://www.ncbi.nlm.nih.gov/pubmed/30107099 http://dx.doi.org/10.1002/cyto.a.23566 |
Ejemplares similares
-
Fast Discriminative Stochastic Neighbor Embedding Analysis
por: Zheng, Jianwei, et al.
Publicado: (2013) -
High-dimensional single cell analysis identifies stem-like cytotoxic CD8(+) T cells infiltrating human tumors
por: Brummelman, Jolanda, et al.
Publicado: (2018) -
Shape-aware stochastic neighbor embedding for robust data visualisations
por: Wängberg, Tobias, et al.
Publicado: (2022) -
CRUSTY: a versatile web platform for the rapid analysis and visualization of high-dimensional flow cytometry data
por: Puccio, Simone, et al.
Publicado: (2023) -
Exposure to intergroup conspiracy theories promotes prejudice which spreads across groups
por: Jolley, Daniel, et al.
Publicado: (2019)