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A tool to visualize variant effect maps from MaveDBhttps://www.mavedb.org/ as genophenograms with added tracks for structure information. MaveVis is deployed as a webtool athttp://vis.varianteffect.org.

Mavevis can be used in multiple different modes:

• Awebtool, deployed as a docker container
• ARestFul webservice available from the same docker deployment
• AnR-package
• Acommand line tool

The webtool can be found athttp://vis.varianteffect.org. But if you'd like to deploy it yourself you can get the built docker image athttps://hub.docker.com/r/jweile/mavevis. You will of course need an installation ofDocker. Then you can pull the image and deploy it as a container:

$ docker pull jweile/mavevis:latest#Assuming we want to map the web interface to port 80:$ docker run -t -p 80:80 --name mavevis jweile/mavevis:latest

If you insist on building the image from scratch, you can check out the git repo, and use the provided make file:

$ git clone https://github.com/VariantEffect/mavevis.git$cd docker$ make build

A detailed manual of the webservice can be foundhere.

At the most basic level, MaveVis is available as an R-package, with the following dependencies:

• R 3.1.2 or higher
• An installation ofDSSP (tested with v3.0.0)
• An installation ofFreeSASA (tested with v2.0.2)
• An installation ofClustalOmega (tested with v1.2.4)
• hgvsParseR
• rapimave
• yogitools
• httr
• gdata
• hash

• devtools
• testthat
• roxygen2
• cgir

#Use apt to install meta-dependencies$ sudo apt install r-base wget g++ make libcurl4-openssl-dev libssl-dev \    libxml2 libxml2-dev libjson-c-dev dssp clustalo#Download and build FreeSASA$ wget https://github.com/mittinatten/freesasa/releases/download/2.0.2/freesasa-2.0.2.tar.gz$ tar xzf freesasa-2.0.2.tar.gz$cd freesasa-2.0.2$ ./configure --disable-xml$ make$ sudo make install#Clean-up build directory$cd ..$ rm -r freesasa*#Install R-packages$ R> install.packages("devtools")> library(devtools)> install_github("jweile/yogitools")> install_github("jweile/cgir")> install_github("VariantEffect/hgvsParseR")> install_github("VariantEffect/rapimave")> install_github("VariantEffect/mavevis")>q()

A full manual for all functions included in the R-package can be foundhere.

The main dashboard() function in the R-package can also be accessed as a CLI script, to avoid having to open an interactive session. You need to install the R-package as described above to use the script. You can then download themavevis_launcher.R script from the docker directory and use it as follows:

Rscript mavevis_launcher.R scoresetID=<ssid> uniprot=<uniprot>     pdb=<pdb-ids> mainChain=<chains> [WT=<seq>| seqOffset=<num>|     synMed=<num>| stopMed=<num>| pngRes=<num>| outFormats={png|pdf|svg}]

The following parameters are mandatory:ssid is the URI of a score set in MaveDB,uniprot is the uniprot accession corresponding to the target of the scoreset,pdb is a comma-separated list of PDB accessions to use for the structure tracks,mainChain is a comma-separated list of PDB chain identifiers (e.g. A)

Depending on the scoreset, the following parameters may also be required:seqOffset the offset of the scoreset position indexes with respect to the uniprot sequence;synMed the expected score of a synonymous or wt-like variant;stopMed the expected score of a null-like or stop variant.

Finally, the following parameters are optional:WT is the WT sequence, which defaults to the one provided by MaveDB;outFormats is a comma-separated list of output file formats, with allowed values png, pdf, and svg;pngRes is the resolution (in DPI) to be used for any PNG output file.