Package: nem
Title: Nested Effects Models to reconstruct phenotypic hierarchies
Version: 2.12.0
Author: Holger Froehlich, Florian Markowetz, Achim Tresch, Christian
        Bender, Matthias Maneck, Claudio Lottaz, Tim Beissbarth
Description: The package 'nem' allows to reconstruct features of
        pathways from the nested structure of perturbation effects. It
        takes as input (1.) a set of pathway components, which were
        perturbed, and (2.) high-dimensional phenotypic readout of
        these perturbations (e.g. gene expression or morphological
        profiles). The output is a directed graph representing the
        phenotypic hierarchy.
Reference: Markowetz F, Bloch J, Spang R: Non-transcriptional pathway
        features reconstructed from secondary effects of RNA
        interference, Bioinformatics, 2005, 21:4026-4032. Froehlich H,
        Fellmann M, Sueltmann H, Poustka A, Beissbarth T: Large Scale
        Statistical Inference of Signaling Pathways from RNAi and
        Microarray Data, BMC Bioinformatics, 2007, 8:386. Froehlich H,
        Fellmann M, Sueltmann H, Poustka A, Beissbarth T: Estimating
        Large Scale Signaling Networks through Nested Effects Models
        from Intervention Effects in Microarray Data. Bioinformatics,
        2008, 24:2650-2656. Froehlich H, Beissbarth T, Tresch A, Kostka
        D, Jacob J, Spang R, Markowetz F: Analyzing gene perturbation
        screens with nested effects models in R and bioconductor,
        Bioinformatics, 2008, 24:2549-50. Froehlich H, Tresch A,
        Beissbarth T: Nested effects models for learning signaling
        networks from perturbation data, Biometrical Journal, 2009,
        2:304-323.
Maintainer: Christian Bender <c.bender@dkfz-heidelberg.de>
Depends: R (>= 2.0), e1071 (>= 1.5), graph (>= 1.24), Rgraphviz (>=
        1.22), plotrix, limma, time (>= 1.0), cluster (>= 1.11)
Imports: boot, e1071, graph, graphics, grDevices, methods, RBGL (>=
        1.8.1), RColorBrewer, Rgraphviz, stats, utils
Suggests: Biobase (>= 1.10)
LazyLoad: Yes
biocViews: Microarray, Bioinformatics, GraphsAndNetworks, Pathways
URL: http://www.bioconductor.org
License: GPL (>= 2)
Packaged: 2010-04-23 21:11:00 UTC; biocbuild
Built: R 2.11.0; ; 2010-04-24 02:29:11 UTC; windows
