topTerms {slalom} | R Documentation

## Show results of a Slalom model

### Description

Show results of a Slalom model

### Usage

    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

    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)

[Package slalom version 1.9.0 Index]