**Welcome to the repository of VSClust** developed at the [Protein Research Group](http://www.sdu.dk/en/Om_SDU/Institutter_centre/Bmb_biokemi_og_molekylaer_biologi/Forskning/Forskningsgrupper/Protein.aspx) Department of Biochemistry and Molecular Biology [University of Southern Denmark](http://www.sdu.dk) ## Citation When using VSClust, please cite our paper: Veit Schw�mmle, Ole N Jensen; VSClust: Feature-based variance-sensitive clustering of omics data, Bioinformatics, , bty224, https://doi.org/10.1093/bioinformatics/bty224 We provide a shiny app for interactive analysis, a command-line version for running VSClust as script in R and a docker version of the tool to avoid installation issues. ## Shiny app ### Web service You can use the implementation on our web server http://computproteomics.bmb.sdu.dk: http://computproteomics.bmb.sdu.dk/Apps/VSClust Be aware that the tool does allow only one user to run the background R calculations at a time. Therefore the app might become temporarily irresponsive. However, multiple sessions are separated and your data won't be shared between sessions or overwritten. ### Local implementation #### Docker The easiest option is to use the docker image: `docker pull veitveit/vsclust` `docker run -t -i -p 3838:3838 veitveit/vsclust` and access the server through http://localhost:3838 #### Bioconda Install the package conda install -c bioconda vsclust run_vsclust_app.sh and access the shiny app through http://localhost:3838 #### Manual installation Install the following R libraries: Mfuzz, matrixStats, limma, qvalue, yaml, shiny, clusterProfiler, RDAVIDWebService, parallel, shinyjs and shinythemes. In R: `source("https://bioconductor.org/biocLite.R")` `biocLite(c("Mfuzz", "DOSE", "matrixStats", "limma", "yaml", "qvalue", "shiny", "clusterProfiler", "RDAVIDWebService", "parallel", "shinyjs", "shinythemes"))` Download the files into a folder and install the library *e1071FuzzVec*. You might need to compile the library on your computer: Run `R CMD INSTALL e1071FuzzVec_Installation` from the command line. You need to be in the VSClust folder. For Windows users, replace `R` by `InstallationPath/R.exe`. You can run the shiny app from the server.R or ui.R files using [Rstudio](http://rstudio.com) or run the app on a [shiny-server](https://www.rstudio.com/products/shiny/shiny-server/) Be aware that you need to have all files, the R libraries described in Installation *and* the modified e1071 library installed. ### Build and use Docker image A Dockerfile has been created on the basis of an OpenSuse distribution. Copy the repository to a folder and carry out the following command to build the images (takes a while) `docker build -t veitveit/vsclust .` You can run the image by `docker run -t -i -p 3838:3838 veitveit/vsclust` and access the server through http://localhost:3838 ## Command line All operations but the gene set enrichment can be performed via command line running the R script `runVSClust.R` ### Usage Given that you installed the *e1071FuzzVec* library, open the R script and change the relevant file names and parameters. The different operations are described in the R file. ### Installation The *e1071FuzzVec* library needs to be compiled and installed, see above. ## Contact For software issues and general questions, please submit an issue. ## License GPL-2 or higher