To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("nem")
In most cases, you don't need to download the package archive at all.
nem
(Dynamic) Nested Effects Models and Deterministic Effects Propagation Networks to reconstruct phenotypic hierarchies
Bioconductor version: 2.14
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.) phenotypic readout of these perturbations (e.g. gene expression, protein expression). The output is a directed graph representing the phenotypic hierarchy.
Author: Holger Froehlich, Florian Markowetz, Achim Tresch, Theresa Niederberger, Christian Bender, Matthias Maneck, Claudio Lottaz, Tim Beissbarth
Maintainer: Holger Froehlich <frohlich at bit.uni-bonn.de>
Citation (from within R,
enter citation("nem")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("nem")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("nem")
| R Script | Nested Effects Models - An example in Drosophila immune response | |
| Reference Manual |
Details
| biocViews | GraphAndNetwork, Microarray, Pathways, Software |
| Version | 2.38.0 |
| In Bioconductor since | BioC 1.9 (R-2.4) |
| License | GPL (>= 2) |
| Depends | R (>= 2.0), e1071 (>= 1.5), graph(>= 1.24), plotrix, limma, cluster (>= 1.11), statmod, Hmisc, Rgraphviz |
| Imports | boot, e1071, graph, graphics, grDevices, methods, RBGL(>= 1.8.1), RColorBrewer, stats, utils, Rgraphviz |
| Suggests | Biobase(>= 1.10) |
| System Requirements | |
| URL | http://www.bioconductor.org |
| Depends On Me | lpNet |
| Imports Me | |
| Suggests Me | rBiopaxParser |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | nem_2.38.0.tar.gz |
| Windows Binary | nem_2.38.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | nem_2.38.0.tgz |
| Mac OS X 10.9 (Mavericks) | nem_2.38.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
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