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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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Détails bibliographiques
Publié dans:Nat Commun
Auteurs principaux: Belkina, Anna C., Ciccolella, Christopher O., Anno, Rina, Halpert, Richard, Spidlen, Josef, Snyder-Cappione, Jennifer E.
Format: Artigo
Langue:Inglês
Publié: Nature Publishing Group UK 2019
Sujets:
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC6882880/
https://ncbi.nlm.nih.gov/pubmed/31780669
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-019-13055-y
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