# Enriching metabolomics data through diffusion [](https://travis-ci.org/b2slab/FELLA) [](https://codecov.io/github/b2slab/FELLA?branch=master) This repository contains the `FELLA` package. `FELLA` is a metabolomics data enrichment tool that contextualises the experimental results using KEGG reactions, enzymes, modules and pathways. - The input for our package is a __list of affected metabolites__ between experimental conditions. - The layout of the analysis is in a __comprehensive human-readable layout__, exportable to several formats, containing a biological interpetation of the experiment. The subnetwork displayed to the user is found using diffusive processes on a graph that represents the known biological annotations at several molecular levels. To use this package type in your terminal: ```bash R CMD build FELLA R CMD INSTALL FELLA ``` Alternatively, you can use `devtools` if you experience some trouble building the vignette. Working in the package directory, this should do the trick: ```r devtools::install(build_vignettes = T) ``` Once `FELLA` is installed, you may load it by typing in your R terminal ```r library("FELLA") ``` To get the global picture about `FELLA` usage, you may browse its __vignette__ ```r browseVignettes("FELLA") ``` All of the functions in `FELLA` have a (very basic) documentation, inclusive the package and the sample data `FELLA.sample` and `input.sample`. In addition, there is a shiny app to facilitate the usage of the package. Before launching it, a database should be built. For example, for Homo sapiens excluding the hsa01100 pathway: ```r g <- buildGraphFromKEGGREST( organism = "hsa", filter.path = "hsa01100" ) buildDataFromGraph(g) ``` Then we can launch the shiny app ```r FELLA:::launchApp( host = "127.0.0.1", port = 8888 ) ``` and leave the command active. Going to the direction http://127.0.0.1:8888 will start the analysis.