Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets

Accurate and comprehensive extraction of information from high-dimensional single cell datasets necessitates faithful visualizations to assess biological populations. A state-of-the-art algorithm for non-linear dimension reduction, t-SNE, requires multiple heuristics and fails to produce clear repre...

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Detalles Bibliográficos
Autores principales: Belkina, Anna C., Ciccolella, Christopher O., Anno, Rina, Halpert, Richard, Spidlen, Josef, Snyder-Cappione, Jennifer E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6882880/
https://www.ncbi.nlm.nih.gov/pubmed/31780669
http://dx.doi.org/10.1038/s41467-019-13055-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6882880/
https://www.ncbi.nlm.nih.gov/pubmed/31780669
http://dx.doi.org/10.1038/s41467-019-13055-y

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