plotRelevance {slalom} | R Documentation |
Plot results of a Slalom model
plotRelevance(object, n_active = 20, mad_filter = 0.4, annotated = TRUE, unannotated_dense = FALSE, unannotated_sparse = FALSE)
object |
an object of class |
n_active |
number of terms (factors) to be plotted (default is 20) |
mad_filter |
numeric(1), filter factors by this mean absolute deviation to exclude outliers. For large datasets this can be set to 0 |
annotated |
logical(1), should annotated factors be plotted? Default is
|
unannotated_dense |
logical(1), should dense unannotated factors be
plotted? Default is |
unannotated_sparse |
logical(1), should sparse unannotated factors be
plotted? Default is |
invisibly returns a list containing the two ggplot objects that make up the plot
gmtfile <- system.file("extdata", "reactome_subset.gmt", package = "slalom") genesets <- GSEABase::getGmt(gmtfile) data("mesc") model <- newSlalomModel(mesc, genesets, n_hidden = 5, min_genes = 10) model <- initSlalom(model) model <- trainSlalom(model, nIterations = 10) plotRelevance(model)