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 using LSF_DOCKER_PRESERVE_ENVIRONMENT=false, just python will work)
  • For python2.7, run source activate python2, then python

• 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!