Pigengene

DOI: 10.18129/B9.bioc.Pigengene  

Infers biological signatures from gene expression data

Bioconductor version: Release (3.17)

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, Rupesh Agrahari, Meghan Short, Isha Mehta, Neda Emami, and Sogand Sajedi

Maintainer: Habil Zare <zare at u.washington.edu>

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("Pigengene")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("Pigengene")

 

PDF	R Script	Pigengene: Computing and using eigengenes
PDF		Reference Manual
Text		NEWS

Details

biocViews	BiomedicalInformatics, Classification, Clustering, DecisionTree, DimensionReduction, GeneExpression, GraphAndNetwork, ImmunoOncology, Microarray, Network, NetworkInference, Normalization, PrincipalComponent, RNASeq, Software, SystemsBiology, Transcriptomics
Version	1.26.0
In Bioconductor since	BioC 3.4 (R-3.3) (7 years)
License	GPL (>=2)
Depends	R (>= 4.0.3), graph, BiocStyle(>= 2.18.1)
Imports	bnlearn (>= 4.7), C50 (>= 0.1.2), MASS, matrixStats, partykit, Rgraphviz, WGCNA, GO.db, impute, preprocessCore, grDevices, graphics, stats, utils, parallel, pheatmap (>= 1.0.8), dplyr, gdata, clusterProfiler, ReactomePA, ggplot2, openxlsx, DBI, DOSE
LinkingTo
Suggests	org.Hs.eg.db(>= 3.7.0), org.Mm.eg.db(>= 3.7.0), biomaRt(>= 2.30.0), knitr, AnnotationDbi, energy
SystemRequirements
Enhances
URL
Depends On Me
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Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	Pigengene_1.26.0.tar.gz
Windows Binary	Pigengene_1.26.0.zip
macOS Binary (x86_64)	Pigengene_1.26.0.tgz
macOS Binary (arm64)	Pigengene_1.26.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/Pigengene
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/Pigengene
Bioc Package Browser	https://code.bioconductor.org/browse/Pigengene/
Package Short Url	https://bioconductor.org/packages/Pigengene/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.17	Source Archive