Network Fingerprint Framework in R

An implementation of the network fingerprint framework that introduced in paper "Network fingerprint: a knowledge-based characterization of biomedical networks" (Cui, 2015) . This method worked by making systematic comparisons to a set of well-studied "basic networks", measuring both the functional and topological similarity. A biological could be characterized as a spectrum-like vector consisting of similarities to basic networks. It shows great potential in biological network study.


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

Prerequisites

NFP is free available on CRAN. To install NFP, please note especially two depencies of NFP, graph and KEGGgraph are only available from Bioconductor. Appanrantly, function install.packages can not insall Biocondutor packages. There is a function biocLite, a wrapper around install.packages provided by Bioconductor, can be used to install both CRAN and Bioconductor packages simply. More details on biocLite is available from https://www.bioconductor.org/install/#why-biocLite. Thus, users can install NFP install the latest released version using biocLite directly:

source("http://bioconductor.org/biocLite.R")
biocLite("NFP")

or install the Bioconductor dependencies package first:

biocLite(c("graph","KEGGgraph"))
install.packages("NFP")

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 NFP from github, require biocondutor dependencies package pre-installed
if (!require(devtools) 
  install.packages("devtools") 
devtools::install_github("yiluheihei/NFP") 

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

library("NFP")

Moreover, gene similarity data used in our {\it NFP} package is stored in a external data repository NFPdata for the large size (about 16 MB). More details on how to construct External Data Repositories using the Additional_repositories field see The Coatless Professor blog post. Thus, users must install the {\it NFPdata} before the networkfinger print analyis as following code.

if (!require("NFPdata")) {
    install_data_package()
}

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.

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

Cui X, He H, He F, et al. Network fingerprint: a knowledge-based characterization of biomedical networks. Scientific reports, 2015, 5.

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Reference manual

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install.packages("NFP")

0.99.2 by Yang Cao, 10 months ago


https://github.com/yiluheihei/NFP


Report a bug at https://github.com/yiluheihei/NFP/issues


Browse source code at https://github.com/cran/NFP


Authors: Yang Cao [aut, cre], Fei Li [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports igraph, stringr, magrittr, plyr, ggplot2, apcluster, KEGGgraph, dplyr, tidyr, methods

Depends on graph

Suggests knitr, testthat, BiocStyle, graphite, NFPdata


See at CRAN