Tailor: Targeting heavy tails in flow cytometry data with fast, interpretable mixture modeling

Automated clustering workflows are increasingly used for the analysis of high parameter flow cytometry data. This trend calls for algorithms which are able to quickly process tens of millions of data points, to compare results across subjects or time points, and to provide easily actionable interpre...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Cytometry. Part A Jg. 99; H. 2; S. 133 - 144
Hauptverfasser:	Ionita, Matei, Schretzenmair, Richard, Jones, Derek, Moore, Jonni, Wang, Li‐San, Rogers, Wade
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken, USA John Wiley & Sons, Inc 01.02.2021 Wiley Subscription Services, Inc
Schlagworte:	Algorithms Annotations Automation Clustering clustering algorithms computation and informatics Data points Flow cytometry high‐parameter flow cytometry mixture modeling Phenotypes Probabilistic models Source code mixture modeling computation and informatics high-parameter flow cytometry clustering algorithms
ISSN:	1552-4922, 1552-4930, 1552-4930
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!