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...

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Bibliographic Details
Published in:	Cytometry. Part A Vol. 99; no. 2; pp. 133 - 144
Main Authors:	Ionita, Matei, Schretzenmair, Richard, Jones, Derek, Moore, Jonni, Wang, Li‐San, Rogers, Wade
Format:	Journal Article
Language:	English
Published:	Hoboken, USA John Wiley & Sons, Inc 01.02.2021 Wiley Subscription Services, Inc
Subjects:	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 Access:	Get full text
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