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Showing content from https://www.bioconductor.org/packages/devel/data/annotation/html/../../../bioc/html/Pigengene.html below:

Bioconductor - Pigengene (development version)

Pigengene

This is the development version of Pigengene; for the stable release version, see Pigengene.

Infers biological signatures from gene expression data

Bioconductor version: Development (3.22)

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")): Installation

To install this package, start R (version "4.5") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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")
Details biocViews BiomedicalInformatics, Classification, Clustering, DecisionTree, DimensionReduction, GeneExpression, GraphAndNetwork, ImmunoOncology, Microarray, Network, NetworkInference, Normalization, PrincipalComponent, RNASeq, Software, SystemsBiology, Transcriptomics Version 1.35.0 In Bioconductor since BioC 3.4 (R-3.3) (8.5 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 Package Archives

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

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