FLAME

Description

FLAME (FLow analysis with Automated Multivariate Estimation) uses finite mixture model clustering techniques with novel algorithms and models to define and characterize discrete populations in flow cytometric data. Saumyadipta Pyne, et al. (2009) developed the FLAME method and implemented it as a suite of GenePattern modules:
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• FLAMEPreprocess performs a series of preprocessing operations on flow cytometric data files, including data transformation, column/channel selection, bi-exponential transformation, and optional live-cell gating.
• FLAMEMixtureModel clusters each preprocessed sample data file over a range of possible cluster numbers.
• FLAMEChooseOptimalClusterNumber determines the optimal number of clusters for each sample based on the range of cluster numbers provided to FLAMEMixtureModel.
• FLAMEMetacluster takes the data samples, which have been optimally clustered into subpopulations, and matches the subpopulations so that a given population can be identified uniformly across all samples.

The following additional modules are provided for examining the clusters FLAME identified in a specified sample:

• FLAMEContourDataGenerator generates data which allows the FLAMEViewer to draw a 3-D contour plot of the clusters in the sample.
• FLAMEViewer displays a 3-D scatterplot and, if FLAMEContourDataGenerator was run, a 3-D contour plot of the clusters in the sample.
• FLAMEContourViewer.Pipeline runs the FLAMEContourDataGenerator and FLAMEViewer modules. Using the pipeline is more convenient than running the two modules individually.

References

• Automated High-dimensional Flow Cytometric Data Analysis
  Saumyadipta Pyne, Xinli Hu, Kui Wang, Elizabeth Rossin, Tsung-I Lin, Lisa M. Maier, Clare Baecher-Allan, Geoffrey J. McLachlan, Pablo Tamayo, David A. Hafler, Philip L. De Jager, and Jill P. Mesirov.
  PNAS (2009) 106:8519-8524.
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