Avatar - Analysis and Visualization of Alteration Data

Avatar is a readily usable standalone software for analysis and visualisation of alteration data.

Avatar features interactively customizable alteration plots, extensive data import capabilities and a multi-objective optimization algorithm to find alteration patterns, e.g. gene sets with mutually exclusive alterations or small gene sets with high sample coverage.

Import dialog for study data from cBioPortal.

Optimization result dialog for interactive exploration of the Pareto-set of trade-off solutions.

Installation

Download the binaries for your operating system below:

• Windows
• Linux
• Mac OS X

For Windows and Linux extract the files from the archive and run the avatar binary. For Mac OS X double click the dmg image and then open the avatar volume from your desktop to run the avatar binary.

You can also download the jar file for Linux which needs an installed Java 11.

Publication Data

Walkthrough

To get an impression of the capabilities of Avatar, you can read the walkthrough of the Head and Neck Squamous Cell Carcinomas usecase.

Additional Data

• The preprocessed clinical attributes can be download as preprocessed-clinical-data.tsv.
• The used list of Cancer-Testis-Antigens can be downloaded as cancer-testis-antigens.txt.
• The use case file with optimization results can be downloaded as hnsc.optimized.avatar.
• The file of the BRCA analysis in the supplement based on the multi-dendrix BRCA dataset can be downloaded as multi-dendrix-BRCA.optimized.avatar.

Development

Clone this project from Github and switch to the downloaded directory:

git clone [email protected]:sysbio-bioinf/avatar.git
cd avatar

Avatar is organized as a Leiningen project. After you have installed Leiningen, you can build Avatar with the following command:

lein build

After that, the resulting standalone jar file can be found at target/avatar-x.y.z.jar.

License

Copyright © 2016-present Gunnar Völkel

Avatar is distributed under the Eclipse Public License v2.0.

Cite

If you are using this software please cite

Völkel G, Laban S, Fürstberger A, Kühlwein SD, Ikonomi N, Hoffmann TK, Brunner C, Neuberg DS, Gaidzik V, Döhner H, Kraus JM, Kestler HA. Analysis, identification and visualization of subgroups in genomics. Brief Bioinform (3): bbaa217, 2021. https://doi.org/10.1093/bib/bbaa217