This is the README for the github repository https://github.com/dib-lab/2015-khmer-wok4-multimap.
This repository contains the pipeline underlying the blog post/micropub entitled Labeling a sparse covering of a De Bruijn graph, and utility thereof.
Contact: C. Titus Brown, titus@idyll.org, or @ctitusbrown (on Twitter).
We provide two ways to reproduce the results in the blog post -- first, instructions for a blank Ubuntu virtual machine, and second, instructions for running inside a Docker container.
You will need less than 2 GB of RAM and about 10 GB of free disk space to run all of this. It should take about 15 minutes to run.
To regenerate the figures in the blog post, see the Jupyter notebook 'figures.ipynb' in the repository.
Boot up an empty Ubuntu image (an Amazon m3.large should be enough), and run:
sudo apt-get update && \
sudo apt-get -y install python-virtualenv python-dev git bowtie2 \
samtools libboost-dev zlib1g-dev && \
sudo shutdown -r now
Log back in, and set yourself up with a virtualenv:
python -m virtualenv work . work/bin/activate pip install -U setuptools git clone https://github.com/dib-lab/nullgraph.git
Now install the 2015-wok branch of khmer:
git clone https://github.com/dib-lab/khmer.git -b 2015-wok cd khmer && make install; cd ..
Go to a sizeable working directory that you have permissions to write to; on AWS, this is /mnt.
sudo chmod a+rwxt /mnt cd /mnt
Then, clone the pipeline:
git clone https://github.com/dib-lab/2015-khmer-wok4-multimap.git wok4
and grab the data:
cd wok4 ./download-data.sh
And, finally, run the pipeline:
make KHMER=/home/ubuntu/khmer NULLGRAPH=/home/ubuntu/nullgraph
To interpret the results, please see the blog post above, or look through the Makefile.
First, if you need to install Docker, perhaps on your empty Ubuntu machine from above, do the following:
wget -qO- https://get.docker.com/ | sudo sh
If you are doing the above on a blank Ubuntu machine on e.g. AWS, make sure to give the ubuntu user permissions to run docker:
sudo usermod -aG docker ubuntu
and then log out & back in to enable those permissions.
Go to a sizeable working directory that you have permissions to write to; on AWS, this is /mnt.
sudo chmod a+rwxt /mnt cd /mnt
Then, clone the pipeline:
git clone https://github.com/dib-lab/2015-khmer-wok4-multimap.git wok4
and grab the data:
cd wok4 ./download-data.sh
And, finally, run the pipeline:
docker run -v /mnt/wok4:/pipeline titus/2015-wok
To interpret the results, please see the blog post above, or look through the Makefile.