topTerms {slalom} | R Documentation |
Show results of a Slalom model
topTerms(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 |
data.frame with factors ordered by relevance, showing term
(term names), relevance
, type
(factor type: known, annotated
or unannotated), n_prior
(number of genes annotated to the gene
set/factor), n_gain
(number of genes added/switched on for the
factor), n_loss
(number of genes turned off for the factor).
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) topTerms(model)