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

Bioconductor version: 2.10

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

Maintainer: Xin Wang <Xin.Wang at>

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



PDF R Script 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
Depends R (>= 2.10), igraph0, GSEABase, BioNet, cellHTS2, RankProd, methods
Imports graph, igraph0, GSEABase, BioNet, cellHTS2, AnnotationDbi, biomaRt
Suggests KEGG.db, GO.db,, GOstats,,,,, snow
System Requirements
License Artistic-2.0
Depends On Me
Imports Me Mulder2012, phenoTest
Suggests Me RedeR
Version 2.8.3
Since Bioconductor 2.7 (R-2.12)

Package Downloads

Package Source HTSanalyzeR_2.8.3.tar.gz
Windows Binary (32- & 64-bit)
MacOS 10.5 (Leopard) binary HTSanalyzeR_2.8.3.tgz
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