Talk Get in time your bioinformatic recipes with RunnerPyzza: an easy to use queue system for laboratory networks


Recent developments in biological technologies have dropped both the cost and the time needed to obtain large amounts of biological data: on the other hand the processing of raw data in biological meaningful results is the real bottleneck, since an expert bioinformatician is needed. This is true, despite the fact that most of the bioinformatic protocols are standardized and, in many cases, easy to automate; moreover, many bioinformaticians already have a series of pipelines (or "recipes") available for the most common daily tasks: the only problem is to make those recipes available to the non bioinformatician members of the laboratory that are not able to setup and run a bioinformatic task.
In order to reduce the amount of repetitive work from the bioinformatician stack and to make those pipelines easier, we developed RunnerPyzza, an easy to use client-server queue manager written in python, structured in three parts: one main server, many workers and many clients. The main server receives all the pipelines (or the "pyzza recipes") that will be run (or “cooked”) on the workers, which don't need any particular setup, other than be accessible through ssh; the server manages the queue performing load balancing on the available workers and taking trace about those results. Furthermore, there are many possible solutions to submit a job and access the results (the desired “pyzza”), by using the various available clients that can run on the main OS (GUIs, web pages, command line tools).
RunnerPyzza comes with a series of default recipes that cover some of the most common bioinformatic tasks; anyway the preparation of custom recipes is easy and should transform each pipeline in a handy tool for the whole laboratory.

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