topTerms: Show results of a Slalom model

Description Usage Arguments Value Examples

Description

Show results of a Slalom model

Usage

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topTerms(object, n_active = 20, mad_filter = 0.4, annotated = TRUE,
  unannotated_dense = FALSE, unannotated_sparse = FALSE)

Arguments

object

an object of class Rcpp_SlalomModel

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 TRUE

unannotated_dense

logical(1), should dense unannotated factors be plotted? Default is FALSE

unannotated_sparse

logical(1), should sparse unannotated factors be plotted? Default is FALSE

Value

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).

Examples

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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)

PMBio/Rslalom documentation built on May 28, 2019, 2:23 p.m.