This function realizes the complete pipeline functionality: single gene expression values are culstered to metagenes using a self-organizing map. Based on these metagenes, visualizations (e.g. expression portraits), downstreaming sample similarity analyses (e.g. hierarchical clustering, ICA) and functional enrichment analyses are performed. The results are given within a separate folder and can be browsed using the summary HTML file.
the opossom environment created with
# Example with artificial data env <- opossom.new(list(dataset.name="Example", dim.1stLvlSom=20)) env$indata <- matrix(rnorm(1000), 100, 10) opossom.run(env)
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