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Day 2 - installation instructions

(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.)

Running Jupyter Notebook

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 .