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Automated optimized parameters for t-distributed stochastic neighbor embedding improve visualization and allow analysis of large datasets
View ORCID ProfileAnna C. Belkina, Christopher O. Ciccolella, Rina Anno, View ORCID ProfileRichard Halpert, View ORCID ProfileJosef Spidlen, View ORCID ProfileJennifer E. Snyder-Cappione
doi: https://doi.org/10.1101/451690
Anna C. Belkina
1Department of Pathology, Boston University School of Medicine, Boston, MA
2Flow Cytometry Core Facility and Boston University School of Medicine, Boston, MA
Christopher O. Ciccolella
4Omiq, Inc, Santa Clara, CA
Rina Anno
5Department of Mathematics, Kansas State University, Manhattan, KS
Richard Halpert
6BD Life Sciences – FlowJo, Ashland, OR
Josef Spidlen
6BD Life Sciences – FlowJo, Ashland, OR
Jennifer E. Snyder-Cappione
2Flow Cytometry Core Facility and Boston University School of Medicine, Boston, MA
3Department of Microbiology, Boston University School of Medicine, Boston, MA
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Posted May 17, 2019.
Automated optimized parameters for t-distributed stochastic neighbor embedding improve visualization and allow analysis of large datasets
Anna C. Belkina, Christopher O. Ciccolella, Rina Anno, Richard Halpert, Josef Spidlen, Jennifer E. Snyder-Cappione
bioRxiv 451690; doi: https://doi.org/10.1101/451690
Automated optimized parameters for t-distributed stochastic neighbor embedding improve visualization and allow analysis of large datasets
Anna C. Belkina, Christopher O. Ciccolella, Rina Anno, Richard Halpert, Josef Spidlen, Jennifer E. Snyder-Cappione
bioRxiv 451690; doi: https://doi.org/10.1101/451690
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