Single sample network reconstruction in R
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
R
data
inst/doc
man
vignettes
DESCRIPTION
NAMESPACE
README.md
lionessR.Rproj

README.md

lionessR

Package for single sample network reconstruction in R

LIONESS, or Linear Interpolation to Obtain Network Estimates for Single Samples, can be used to reconstruct single-sample networks (http://arxiv.org/pdf/1505.06440.pdf). This package implements the LIONESS equation in R to reconstruct single-sample networks. The default network reconstruction method we use here is based on Pearson correlation. However, lionessR can run on any network reconstruction algorithms that returns a complete, weighted adjacency matrix. lionessR works for both unipartite and bipartite networks.

The easiest way to install the R package lionessR is via the devtools package from CRAN:

install.packages("devtools")
library(devtools)
devtools::install_github("mararie/lionessR")

And then load the package using: library(lionessR).

Please see the vignette for an example of co-expression network analysis using lionessR. For the example, you need to have CRAN packages igraph and reshape2 and Bioconductor package limma installed.