FlowSOM: Using self-organizing maps for visualization and interpretation of cytometry data

FlowSOM offers visualization options for cytometry data, by using Self-Organizing Map clustering and Minimal Spanning Trees.

AuthorSofie Van Gassen, Britt Callebaut and Yvan Saeys
Date of publicationNone
MaintainerSofie Van Gassen <sofie.vangassen@ugent.be>
LicenseGPL (>= 2)

View on Bioconductor


AddFlowFrame Man page
AggregateFlowFrames Man page
BuildMST Man page
BuildSOM Man page
CountGroups Man page
Dist.MST Man page
FlowSOM Man page
FlowSOMSubset Man page
FMeasure Man page
Initialize Man page
MapDataToCodes Man page
MetaClustering Man page
metaClustering_consensus Man page
NewData Man page
PeaksAndValleys Man page
PlotCenters Man page
PlotClusters2D Man page
PlotGroups Man page
PlotMarker Man page
PlotNumbers Man page
PlotPies Man page
plotStarLegend Man page
PlotStars Man page
PlotStarsSD Man page
PlotVariable Man page
ProcessGatingML Man page
Purity Man page
QueryStarPlot Man page
ReadInput Man page
SaveClustersToFCS Man page
SOM Man page
UpdateNodeSize Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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