This site is a development preview. As such the content and styling may not be final and is subject to change before going into production. To see more information about the redesign click here.

gep2pep

This is the development version of gep2pep; for the stable release version, see gep2pep.

Creation and Analysis of Pathway Expression Profiles (PEPs)

Bioconductor version: Development (3.18)

Pathway Expression Profiles (PEPs) are based on the expression of pathways (defined as sets of genes) as opposed to individual genes. This package converts gene expression profiles to PEPs and performs enrichment analysis of both pathways and experimental conditions, such as "drug set enrichment analysis" and "gene2drug" drug discovery analysis respectively.

Author: Francesco Napolitano <franapoli at gmail.com>

Maintainer: Francesco Napolitano <franapoli at gmail.com>

Citation (from within R, enter citation("gep2pep")):

Installation

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

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

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

BiocManager::install("gep2pep")

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("gep2pep")
Introduction to gep2pep HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DifferentialExpression, DimensionReduction, GO, GeneExpression, GeneSetEnrichment, Pathways, Software
Version 1.21.0
In Bioconductor since BioC 3.7 (R-3.5) (5.5 years)
License GPL-3
Depends
Imports repo (>= 2.1.1), foreach, stats, utils, GSEABase, methods, Biobase, XML, rhdf5, digest, iterators
Linking To
Suggests WriteXLS, testthat, knitr, rmarkdown
System Requirements
Enhances
URL
See More
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package gep2pep_1.21.0.tar.gz
Windows Binary gep2pep_1.21.0.zip (64-bit only)
macOS Binary (x86_64) gep2pep_1.21.0.tgz
macOS Binary (arm64) gep2pep_1.21.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/gep2pep
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/gep2pep
Bioc Package Browser https://code.bioconductor.org/browse/gep2pep/
Package Short Url https://bioconductor.org/packages/gep2pep/
Package Downloads Report Download Stats