README.md

In aib-group/PFP: Pathway Fingerprint Framework in R

PFP: Pathway fingerprint analysis in R

This package implements the pathway fingerprint framework. A biomedical pathway is characterized as a spectrum-like vector called “pathway fingerprint”, which contains similarities to basic pathways. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular pathways, especially for large-scale pathway comparisons and clustering analyses.

Prerequisites

To install PFP, please note especially a depencies of PFP, org.Mm.eg.db are only available from Bioconductor. Install the Bioconductor dependencies package first:

if (!requireNamespace("BiocManager"))
    install.packages("BiocManager")
BiocManager::install("org.Mm.eg.db")

It also allows users to install the latest development version from github, which requires devtools package has been installed on your system (or can be installed using install.packages("devtools")). Note that devtools sometimes needs some extra non-R software on your system -- more specifically, an Rtools download for Windows or Xcode for OS X. There's more information about devtools here.

## install PFP from github, require biocondutor dependencies package pre-installed
if (!require(devtools)) 
  install.packages("devtools") 
devtools::install_github("aib-group/PFP") 

After installation, you can load PFP into current workspace by typing or pasting the following codes:

R library("PFP")

Contributing

For very simple changes such as fixing typos, you can just edit the file by clicking the button Edit. For more complicated changes, you will have to manually create a pull request after forking this repository.

License

PFP is a free and open source software, licensed under GPL 2.0.

aib-group/PFP documentation built on Dec. 27, 2020, 1:13 a.m.