From the desktop to the grid: scalable bioinformatics via workflow conversion

BMC Bioinformatics

Software

Stephan Aiche¹  Knut Reinert¹  Oliver Kohlbacher²  Johannes Veit²  Andras Szolek²  Marc Röttig²  Luis de la Garza²  Sandra Gesing³ 

[1] Algorithmic Bioinformatics, Computer Science Institute, Freie Universität Berlin, Takustr. 9, 14195, Berlin, Germany;Center for Bioinformatics and Dept. of Computer Science, University of Tübingen, Sand 14, 72070, Tübingen, Germany;College of Engineering, University of Notre Dame, 257 Fitzpatrick Hall, 46556, Notre Dame, IN, United States;

关键词: Workflow;    Interoperability;    KNIME;    Grid;    Cloud;    Galaxy;    gUSE;   

DOI  :  10.1186/s12859-016-0978-9

 received in 2015-11-12, accepted in 2016-03-03,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundReproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the complexity of such experiments into the joint collaboration of small, repeatable, well defined tasks, each with well defined inputs, parameters, and outputs, offers the immediate benefit of identifying bottlenecks, pinpoint sections which could benefit from parallelization, among others. Workflows rest upon the notion of splitting complex work into the joint effort of several manageable tasks.There are several engines that give users the ability to design and execute workflows. Each engine was created to address certain problems of a specific community, therefore each one has its advantages and shortcomings. Furthermore, not all features of all workflow engines are royalty-free —an aspect that could potentially drive away members of the scientific community.ResultsWe have developed a set of tools that enables the scientific community to benefit from workflow interoperability. We developed a platform-free structured representation of parameters, inputs, outputs of command-line tools in so-called Common Tool Descriptor documents. We have also overcome the shortcomings and combined the features of two royalty-free workflow engines with a substantial user community: the Konstanz Information Miner, an engine which we see as a formidable workflow editor, and the Grid and User Support Environment, a web-based framework able to interact with several high-performance computing resources. We have thus created a free and highly accessible way to design workflows on a desktop computer and execute them on high-performance computing resources.ConclusionsOur work will not only reduce time spent on designing scientific workflows, but also make executing workflows on remote high-performance computing resources more accessible to technically inexperienced users. We strongly believe that our efforts not only decrease the turnaround time to obtain scientific results but also have a positive impact on reproducibility, thus elevating the quality of obtained scientific results.

【 授权许可】

CC BY   
© de la Garza et al. 2016