(Instructions mostly copied from :doc:`quality`!)
Use image "Ubuntu 14.04.3"
Run:
sudo apt-get -y update && \ sudo apt-get -y install trimmomatic fastqc python-pip \ samtools zlib1g-dev ncurses-dev python-dev
Install anaconda:
curl -O https://repo.continuum.io/archive/Anaconda3-4.2.0-Linux-x86_64.sh bash Anaconda3-4.2.0-Linux-x86_64.sh
Then update your environment and install khmer and sourmash:
source ~/.bashrc conda install -n root pip -y pip install https://github.com/dib-lab/khmer/archive/master.zip pip install https://github.com/dib-lab/sourmash/archive/2017-ucsc-metagenome.zip
(See the sourmash docs for this workshop for some details on the sourmash install.)
Let's also run a Jupyter Notebook in your home directory. Configure it a teensy bit more securely, and also have it run in the background.
Generate a config:
jupyter notebook --generate-config
Add a password, have it not run a browser, and put it on port 8000 by default:
cat >> ~/.jupyter/jupyter_notebook_config.py <<EOF c = get_config() c.NotebookApp.ip = '*' c.NotebookApp.open_browser = False c.NotebookApp.password = u'sha1:5d813e5d59a7:b4e430cf6dbd1aad04838c6e9cf684f4d76e245c' c.NotebookApp.port = 8000 EOF
Now, run!
jupyter notebook &
This will output some stuff; to make the prompt appear again, hit ENTER a few times.
You should now be able to visit port 8000 on your computer and see the Jupyter console; to get the URL to Jupyter, run:
echo http://$(hostname):8000/
Note
If your network blocks port 8000 (e.g. cruznet at UCSC), you can run:
ssh -N -f -L localhost:8000:localhost:8000 username@remotehost
to tunnel the remote Jupyter notebook server over SSH.
We are now ready to map and bin reads .