clubber: removing the bioinformatics bottleneck in big data analyses

<p><em>clubber</em> is our automated cluster-load balancing system developed for optimizing these “big data” analyses. Its plug-and-play framework encourages re-use of existing solutions for bioinformatics problems. <em>clubber</em>’s goals are to reduce computation times and to facilitate use of cluster computing. The first goal is achieved by automating the balance of parallel submissions across available high performance computing (HPC) resources. Notably, the latter can be added on demand, including cloud-based resources, and/or featuring heterogeneous environments. The second goal of making HPCs user-friendly is facilitated by an interactive web interface and a RESTful API, allowing for job monitoring and result retrieval. We used <em>clubber</em> to speed up our pipeline for annotating molecular functionality of metagenomes.</p> <p><em>clubber</em> is available as docker image at the Docker store:</p> <blockquote> <p>https://store.docker.com/community/images/bromberglab/clubber</p> </blockquote> <p>Run <em>clubber</em> locally using: </p> <blockquote> <p>docker run -d -p 80:80 bromberglab/clubber:latest</p> </blockquote> <p>Sources can be found at:</p> <blockquote> <p>https://bitbucket.org/bromberglab/clubber</p>