Caleydo - Visualization for Molecular Biology
Caleydo is a visualization framework for molecular biology data. It is targeted at analyzing multiple heterogeneous but related tabular datasets (e.g., mRNA expression, copy number status and clinical variables), stratifications or clusters in these datasets and their relationships to biological pathways.
For user documentation please refer to the Caleydo Help. For general information and downloads based on binaries please use the Caleydo Website. This guide assumes that you want to install Caleydo from source.
Caleydo uses Java, OpenGL and the Eclipse Rich Client Platform (RCP). Things you need to install before being able to run Caleydo:
- Eclipse Kepler for RCP and RAP Developers, which you can get from the eclipse download page. Other Eclipse versions won't work.
- Install EGit in Eclipse using software updates.
- Java SDK >= 1.7
To install Caleydo use EGit within Eclipse and clone the repository. Each directory in the caleydo-dev folder corresponds to an Eclipse project. Here is a good tutorial on how to import Eclipse projects from git.
If you want to use ssh (instead of https) for communicating with github out of eclipse follow these instructions. You will have to generate a new RSA key and save it to you ~/.ssh folder. Remeber to set a passphrase for you key. This will result in a file ida_rsa and ida_rsa.pub turning up in your ssh folder. Save your public rsa key with your eclipse account folder.
When cloning the repository follow the above tutorial. Don't change the username "git" to your username!
Caleydo is an academic project currently developed by members of
- Institute for Computer Graphics and Vision at Graz University of Technology, Austria
- Institute of Computer Graphics at Johannes Kepler University Linz, Austria
- Pfister Lab at the School of Engineering and Applied Sciences, Harvard University, Cambridge, USA
- Park Lab at Harvard Medical School, Boston, USA
Caleydo makes use of a range of open source tools, bioinformatics resources and pre-packages several datasets, which we gratefully acknowledge here.
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