Pigengene
This is the development version of Pigengene; for the stable release version, see Pigengene.
All Bioconductor versions of Pigengene
3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9, 3.8, 3.7, 3.6, 3.5, 3.4
Infers biological signatures from gene expression data
Bioconductor version: 3.24 · Package version: 1.39.0
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>
Citation
From within R, enter citation("Pigengene"):
Habil Zare, Amir Foroushani, Rupesh Agrahari, Meghan Short, Isha Mehta, Neda Emami, and Sogand Sajedi. Pigengene: Infers biological signatures from gene expression data. doi:10.18129/B9.bioc.Pigengene, R package version 1.39.0, https://bioconductor.org/packages/Pigengene.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")
BiocManager::install("Pigengene")For older versions of R, please refer to the appropriate Bioconductor release.
Details
| Version | 1.39.0 |
| License | GPL (>=2) |
| Last updated | 2026-04-28 |
| In Bioconductor since | BioC 3.4 (R-3.3) (9 years) |
| Downloads rank | 805 of 2,456 |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | BiomedicalInformatics, Classification, Clustering, DecisionTree, DimensionReduction, GeneExpression, GraphAndNetwork, ImmunoOncology, Microarray, Network, NetworkInference, Normalization, PrincipalComponent, RNASeq, Software, SystemsBiology, Transcriptomics |
| Package Short Url | https://bioconductor.org/packages/Pigengene/ |
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("Pigengene")| Pigengene: Computing and using eigengenes | R Script | |
| Reference Manual | ||
| NEWS | Text |
Download
Follow the installation instructions to use this package in your R session.
| Source package | Pigengene_1.39.0.tar.gz |
| Windows binary (x86_64) | Pigengene_1.39.0.zip |
| macOS binary (arm64) | Pigengene_1.39.0.tgz |
| macOS binary (x86_64) | Pigengene_1.39.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/Pigengene |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/Pigengene |
| Package Downloads Report | Download Stats |
Dependencies
Depends: R (>= 4.0.3), graph, BiocStyle (>= 2.28.0)
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
Suggests: org.Hs.eg.db (>= 3.7.0), org.Mm.eg.db (>= 3.7.0), biomaRt (>= 2.30.0), knitr, AnnotationDbi, energy
Reverse dependencies
Imports Me (1): iNETgrate