README.md

output: github_document

gep2pep

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" (finding pathways that are consistently dysregulated by a set of drugs) and "gene2drug" analysis (finding drugs that dysregulate a set of pathways or a single gene).

Two papers have been published in Bioinformatics covering gep2pep methods:

Two corresponding webtools are online, which use Cmap data for both types of analysis:

Gep2pep is maintained by Francesco Napolitano alt text

Download and Installation

The latest stable release can be downloaded from Bioconductor at https://bioconductor.org/packages/release/bioc/html/gep2pep.html. The latest development versions is at https://bioconductor.org/packages/devel/bioc/html/gep2pep.html. Installation instructions ar provided there.

Additional in progress versions can be found on Github at https://github.com/franapoli/gep2pep, downloaded and then installed as follows:

> install.packages("path-to-downloaded-source", repos=NULL)

News

v1.3.1

v1.1.1

v1.0.0



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gep2pep documentation built on Nov. 8, 2020, 5:59 p.m.