# 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](https://www.bioconductor.org). Install the Bioconductor dependencies package first: ```R 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](https://github.com/hadley/devtools). ```R ## 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.