Automatic Clustering of Flow Cytometry Data with Density-Based Merging

作者：Guenther Walther; Noah Zimmerman; Wayne Moore; David Parks; Stephen Meehan; Ilana Belitskaya; Jinhui Pan; Leonore Herzenberg

来源：Advances in Bioinformatics, 2009, 2009: 1-7.

DOI：10.1155/2009/686759

The ability of flow cytometry to allow fast single cell interrogation of a large number of cells has made this technology ubiquitous and indispensable in the clinical and laboratory setting. A current limit to the potential of this technology is the lack of automated tools for analyzing the resulting data. We describe methodology and software to automatically identify cell populations in flow cytometry data. Our approach advances the paradigm of manually gating sequential two-dimensional projections of the data to a procedure that automatically produces gates based on statistical theory. Our approach is nonparametric and can reproduce nonconvex subpopulations that are known to occur in flow cytometry samples, but which cannot be produced with current parametric model-based approaches. We illustrate the methodology with a sample of mouse spleen and peritoneal cavity cells.

• 出版日期2009