Gene set over-representation, enrichment and network analyses for high-throughput screens

Bioconductor version: Release (2.12)

This package provides classes and methods for gene set over-representation, enrichment and network analyses on high-throughput screens. The over-representation analysis is performed based on hypergeometric tests. The enrichment analysis is based on the GSEA algorithm (Subramanian et al. PNAS 2005). The network analysis identifies enriched subnetworks based on algorithms from the BioNet package (Beisser et al., Bioinformatics 2010). A pipeline is also specifically designed for cellHTS2 object to perform integrative network analyses of high-throughput RNA interference screens. The users can build their own analysis pipeline for their own data set based on this package.

Author: Xin Wang <xinwang2hms at>, Camille Terfve <cdat2 at>, John C. Rose <jcr53 at>, Florian Markowetz <Florian.Markowetz at>

Maintainer: Xin Wang <xinwang2hms at>

To install this package, start R and enter:


To cite this package in a publication, start R and enter:



PDF Figure.pdf
PDF R Script Main vignette:Gene set enrichment and network analysis of high-throughput RNAi screen data using HTSanalyzeR
PDF   Reference Manual


biocViews Bioinformatics, CellBasedAssays, MultipleComparisons, Software
Version 2.12.1
In Bioconductor since BioC 2.7 (R-2.12)
License Artistic-2.0
Depends R (>= 2.15), igraph0, methods
Imports graph, igraph0, GSEABase, BioNet, cellHTS2, AnnotationDbi, biomaRt, RankProd
Suggests KEGG.db, GO.db,, GOstats,,,,, snow
System Requirements
Depends On Me
Imports Me Mulder2012, phenoTest
Suggests Me

Package Downloads

Package Source HTSanalyzeR_2.12.1.tar.gz
Windows Binary (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) HTSanalyzeR_2.12.1.tgz
Package Downloads Report Download Stats

Mailing Lists »

Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!

Fred Hutchinson Cancer Research Center