Example data for the EnrichmentBrowser package

Description Usage Arguments Value Author(s) Examples


Functionality to construct example data sets for demonstration. This includes expression data, gene sets, gene regulatory networks, and enrichment analysis results.


1 what = c("eset", "gs", "grn", "ea.res"), ... )



Kind of example data set to be constructed. This should be one out of:

  • eset: Expression set

  • gs: Gene set list

  • grn: Gene regulatory network

  • ea.res: Enrichment analysis result object as returned by the functions sbea and nbea


Additional arguments to fine-tune the specific example data sets.

For what='eset':

  • type: Expression data type. Should be either 'ma' (Microarray intensity measurements) or 'rseq' (RNA-seq read counts).

  • nfeat: Number of features/genes. Defaults to 100.

  • nsmpl: Number of samples. Defaults to 12.

  • blk: Create sample blocks. Defaults to TRUE.

  • norm: Should the expression data be normalized? Defaults to FALSE.

  • de.ana: Should an differential expression analysis be carried out automatically? Defaults to FALSE.

For what='gs':

  • gnames: gene names from which the sets will be sampled. Per default the sets will be drawn from c(g1, ..., g100).

  • n: number of sets. Defaults to 10.

  • min.size: minimal set size. Defaults to 15.

  • max.size: maximal set size. Defaults to 25.

For what='grn':

  • nodes: gene node names for which edges will be drawn. Per default node names will be c(g1, ..., g100).

  • edge.node.ratio: ratio number of edges / number of nodes. Defaults to 3, i.e. creates 3 times more edges than nodes.

For what='ea.res':

  • eset: Expression set. Calls"eset") per default.

  • gs: Gene sets. Calls"gs") per default.

  • method: Enrichment analysis method. Defaults to 'ora'.

  • alpha: Statistical significance level. Defaults to 0.05.


Depends on the 'what' argument.


Ludwig Geistlinger <>


    eset <-"eset")

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