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FSomMetaClustering

Creates self-organizing maps of cytometry data with FlowSOM algorithm and meta clusters the data based on 100 fSOM-maps with consensus clustering. Performs quickly even for large datasets.

Version 1.0
Bundle tools
Categories Clustering
Authors Oskari Lehtonen (oskari.lehtonen@helsinki.fi)
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Requires R (R-package) ; FlowSOM (R-package) ; flowCore (R-package) ; ConsensusClusterPlus (R-package)
Source files component.xml fSomMetaClustering.R
Usage Example with default values

Inputs

Name Type Mandatory Description
in CSV Mandatory Input data, tab separated file. Numeric with column names

Outputs

Name Type Description
out CSV Data frame of cluster labels.
fullData CSV Membership probability for each row in the input data

Parameters

Name Type Default Description
columnsToRemove string "" Comma separated list of names of columns not to be used in clustering. Useful if you want to ignore some attribute in the data while clustering.
k int 10 The number of clusters. Max 100.
seed int 1234 Set the seed for the algorithms to make the results reproducible

Test cases

Test case Parameters IN
in
OUT
out
OUT
fullData
case1 properties in out fullData

seed=1234,
k=15,
columnsToRemove=Species


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