Bioconductor version: Release (3.6)
Pigengene package provides an efficient way to infer biological signatures from gene expression profiles. The signatures are independent from the underlying platform, e.g., the input can be microarray or RNA Seq data. It can even infer the signatures using data from one platform, and evaluate them on the other. Pigengene identifies the modules (clusters) of highly coexpressed genes using coexpression network analysis, summarizes the biological information of each module in an eigengene, learns a Bayesian network that models the probabilistic dependencies between modules, and builds a decision tree based on the expression of eigengenes.
Author: Habil Zare, Amir Foroushani, and Rupesh Agrahari
Maintainer: Habil Zare <zare at txstate.edu>
Citation (from within R,
enter citation("Pigengene")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("Pigengene")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("Pigengene")
R Script | Pigengene: Computing and using eigengenes | |
Reference Manual | ||
Text | NEWS |
biocViews | BiomedicalInformatics, Classification, Clustering, DecisionTree, DimensionReduction, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkInference, Normalization, PrincipalComponent, RNASeq, Software, SystemsBiology, Transcriptomics |
Version | 1.4.20 |
In Bioconductor since | BioC 3.4 (R-3.3) (1.5 years) |
License | GPL (>=2) |
Depends | R (>= 3.3.0), graph |
Imports | bnlearn, C50, MASS, matrixStats, partykit, Rgraphviz, WGCNA, GO.db, impute, preprocessCore, grDevices, graphics, stats, utils, parallel, pheatmap (>= 1.0.8) |
LinkingTo | |
Suggests | org.Hs.eg.db, org.Mm.eg.db, biomaRt(>= 2.30.0), knitr, BiocStyle, AnnotationDbi, energy |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | Pigengene_1.4.20.tar.gz |
Windows Binary | Pigengene_1.4.20.zip |
Mac OS X 10.11 (El Capitan) | Pigengene_1.4.20.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/Pigengene |
Package Short Url | http://bioconductor.org/packages/Pigengene/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.6 | Source Archive |
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