title: Bioconductor's EnrichmentBrowser: seamless navigation through combined results of set- & network-based enrichment analysis.
abstract: BACKGROUND
  Enrichment analysis of gene expression data is essential to find functional groups of genes whose interplay can explain experimental observations. Numerous methods have been published that either ignore (set-based) or incorporate (network-based) known interactions between genes. However, the often subtle benefits and disadvantages of the individual methods are confusing for most biological end users and there is currently no convenient way to combine methods for an enhanced result interpretation.
  
  
  RESULTS
  We present the EnrichmentBrowser package as an easily applicable software that enables (1) the application of the most frequently used set-based and network-based enrichment methods, (2) their straightforward combination, and (3) a detailed and interactive visualization and exploration of the results. The package is available from the Bioconductor repository and implements additional support for standardized expression data preprocessing, differential expression analysis, and definition of suitable input gene sets and networks.
  
  
  CONCLUSIONS
  The EnrichmentBrowser package implements essential functionality for the enrichment analysis of gene expression data. It combines the advantages of set-based and network-based enrichment analysis in order to derive high-confidence gene sets and biological pathways that are differentially regulated in the expression data under investigation. Besides, the package facilitates the visualization and exploration of such sets and pathways.
authors.affiliation: Institute of Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, Amalienstrasse 1780333, Munich, Germany. Ludwig.Geistlinger@bio.ifi.lmu.de.
authors.forename: Ludwig
authors.initials: L
authors.lastname: Geistlinger
authors.affiliation: Institute of Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, Amalienstrasse 1780333, Munich, Germany. Gergely.Csaba@bio.ifi.lmu.de.
authors.forename: Gergely
authors.initials: G
authors.lastname: Csaba
authors.affiliation: Institute of Bioinformatics, Department of Informatics, Ludwig-Maximilians-Universität München, Amalienstrasse 1780333, Munich, Germany. Ralf.Zimmer@bio.ifi.lmu.de.
authors.forename: Ralf
authors.initials: R
authors.lastname: Zimmer
mesh_terms: D016208:Databases, Factual; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D046228:Microarray Analysis / Q000379:methods*; D017423:Sequence Analysis, RNA; D012984:Software