Pigengene
Infers biological signatures from gene expression data
Bioconductor version: Release (3.20)
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("Pigengene")):
Installation
To install this package, start R (version "4.4") 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")| Pigengene: Computing and using eigengenes | R Script | |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | BiomedicalInformatics, Classification, Clustering, DecisionTree, DimensionReduction, GeneExpression, GraphAndNetwork, ImmunoOncology, Microarray, Network, NetworkInference, Normalization, PrincipalComponent, RNASeq, Software, SystemsBiology, Transcriptomics |
| Version | 1.32.0 |
| In Bioconductor since | BioC 3.4 (R-3.3) (8 years) |
| License | GPL (>=2) |
| 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 |
| System Requirements | |
| URL |
See More
| Suggests | org.Hs.eg.db(>= 3.7.0), org.Mm.eg.db(>= 3.7.0), biomaRt(>= 2.30.0), knitr, AnnotationDbi, energy |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | iNETgrate |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | Pigengene_1.32.0.tar.gz |
| Windows Binary (x86_64) | Pigengene_1.32.0.zip |
| macOS Binary (x86_64) | Pigengene_1.32.0.tgz |
| macOS Binary (arm64) | Pigengene_1.31.2.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 |