Basic docker image for ad-hoc genomic analyses - combines a lot of the tools that are handy for exploring data on a ubuntu base image.
-
Python 2 and 3 are both installed (using conda)
- For python 3.6, you'll use
python3
(if you are usingLSF_DOCKER_PRESERVE_ENVIRONMENT=false
, justpython
will work) - For python2.7, run
source activate python2
, thenpython
- For python 3.6, you'll use
-
R 3.4 and some basic packages are installed. For convenience, it can be useful to set up a specific folder in which to keep your own library installs for testing. This will keep them persistent across sessions. Add something like this to your .Rprofile:
devlib <- paste('/gscuser/cmiller/usr/lib/R',paste(R.version$major,R.version$minor,sep="."),sep="") if (!file.exists(devlib)) dir.create(devlib) x <- .libPaths() .libPaths(c(devlib,x)) rm(x,devlib)
This is great for quickly prototyping, but don't forget that if you're sharing code with others, you'll need to create a new container with the proper libraries installed so they can also use it!