SWIFT—Scalable Clustering for Automated Identification of Rare Cell Populations in Large, High-Dimensional Flow Cytometry Datasets, Part 2: Biological Evaluation

A multistage clustering and data processing method, SWIFT (detailed in a companion manuscript), has been developed to detect rare subpopulations in large, high-dimensional flow cytometry datasets. An iterative sampling procedure initially fits the data to multidimensional Gaussian distributions, the...

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Detalles Bibliográficos
Autores principales: Mosmann, Tim R, Naim, Iftekhar, Rebhahn, Jonathan, Datta, Suprakash, Cavenaugh, James S, Weaver, Jason M, Sharma, Gaurav
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BlackWell Publishing Ltd 2014
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4238823/
https://www.ncbi.nlm.nih.gov/pubmed/24532172
http://dx.doi.org/10.1002/cyto.a.22445

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4238823/
https://www.ncbi.nlm.nih.gov/pubmed/24532172
http://dx.doi.org/10.1002/cyto.a.22445

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