This section gives detailed guidance about how to get Ximmer set up and working.
There are two ways to set up Ximmer:
- Natively - using libraries, tools and packages directly on your computer
- Using Docker
Each approach is described below in turn.
Installation and Requirements (Native)
To make Ximmer easier to use we have included support to automatically download and build the tools and other dependencies it needs. You should make sure before starting that you have at minimum the following requirements:
- Java 1.8+
- Python 2.7, preferably the Anaconda installation (you will need support for pandas, numpy and other computational libraries that are not always easy to compile in a vanilla installation).
- A recent version of R (3.4.x as of writing)
- 24GB of RAM
Ideally, these should all be directly accessible from your environment. If necessary, you can specify custom locations for them in the configuration file.
You should also make sure you have internet access while doing the installation because Ximmer will try to download some components. It may be necessary to set the “http_proxy” environment variable if your network uses a proxy.
When installing on linux, you may find that the Python and R libraries that Ximmer needs depend on the following Linux packages being installed:
- Debian / Ubuntu : libxml2-dev libcurl4-openssl-dev libblas-dev liblapack-dev libhdf5-dev libssl-dev libmariadb-client-lgpl-dev
- CentOS : libxml2-devel blas-dev lapack-dev libcurl-devel hdf5-devel
Consider: Set up Python VirtualEnv Environment
The installer will attempt to install various python packages at specific versions. If you don’t have administrative permissions to install python packages, or if you already have conflicting versions installed, this could create a problem. If you have Python virtual-env installed, you can avoid these problems by setting up a virtual-env environment to use with Ximmer. For example:
virtualenv ximmer-python source ximmer-python/bin/activate
Ximmer includes an installer script to help set up and configure it for basic operation. To get started:
git clone https://github.com/ssadedin/ximmer.git cd ximmer ./bin/install
Installation and Requirements (Docker)
If you use Docker, you can install and run Ximmer simply by building it from the Docker file. In this case the primary requirement is that you do this on a computer with enough RAM, we recommend at least 24GB of RAM for the analysis pipeline to run successfully. You may need to change your docker settings to allow it to access the RAM also.
To build the Docker image use:
git clone https://github.com/ssadedin/ximmer.git cd ximmer docker build -t ximmer .
Note: if your machine is behind a proxy, you can provide it ike this:
git clone https://github.com/ssadedin/ximmer.git cd ximmer docker build --build-arg http_proxy='http://proxy.host.com:proxy-port' -t ximmer .
Although running inside docker is essentially the same as running outside, there are a few special considerations to take care of. See Running inside Docker for tips on how to run inside Docker.
See information about how to run an analysis using Ximmer in the Running section, and how to configure CNV simulation in Simulations.