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Robust Cross-Platform Workflows: How Technical and Scientific Data Sci. Eng. (2017) 2:232–244 https://doi.org/10.1007/s41019-017-0050-4 Robust Cross-Platform Workflows: How Technical and Scientific Communities Collaborate to Develop, Test and Share Best Practices for Data Analysis 1,2 2,3 2,4 2,5 Steffen Mo¨ller • Stuart W. Prescott • Lars Wirzenius • Petter Reinholdtsen • 6 7 8,9,10 11 Brad Chapman • Pjotr Prins • Stian Soiland-Reyes • Fabian Klo¨tzl • 12 13 2 2,9 Andrea Bagnacani • Matu´sˇ Kalasˇ • Andreas Tille • Michael R. Crusoe Received: 13 June 2017 / Revised: 1 October 2017 / Accepted: 18 October 2017 / Published online: 16 November 2017 Ó The Author(s) 2017. This article is an open access publication Abstract Information integration and workflow technolo- essential to have all the flexibility of open-source tools and gies for data analysis have always been major fields of open-source workflow descriptions. Workflows in data- investigation in bioinformatics. A range of popular work- driven science such as computational biology have con- flow suites are available to support analyses in computa- siderably gained in complexity. New tools or new releases tional biology. Commercial providers tend to offer with additional features arrive at an enormous pace, and prepared applications remote to their clients. However, for new reference data or concepts for quality control are most academic environments with local expertise, novel emerging. A well-abstracted workflow and the exchange of data collection techniques or novel data analysis, it is the same across work groups have an enormous impact on the efficiency of research and the further development of the field. High-throughput sequencing adds to the ava- & Steffen Mo¨ller lanche of data available in the field; efficient computation [email protected] and, in particular, parallel execution motivate the transition 1 Rostock University Medical Center, Institute for Biostatistics from traditional scripts and Makefiles to workflows. We and Informatics in Medicine and Ageing Research, Rostock, here review the extant software development and distri- Germany bution model with a focus on the role of integration testing 2 Debian Project, https://www.debian.org and discuss the effect of common workflow language on 3 School of Chemical Engineering, UNSW, Sydney, distributions of open-source scientific software to swiftly NSW 2052, Australia and reliably provide the tools demanded for the execution 4 QvarnLabs, Helsinki, Finland of such formally described workflows. It is contended that, alleviated from technical differences for the execution on 5 University Center for Information Technology, University of Oslo, Oslo, Norway local machines, clusters or the cloud, communities also gain the technical means to test workflow-driven interac- 6 Harvard School of Public Health, Boston MA, USA tion across several software packages. 7 University Medical Center Utrecht, Utrecht, The Netherlands 8 eScience Lab, School of Computer Science, The University Keywords Continuous integration testing Á Common of Manchester, Manchester, UK workflow language Á Container Á Software distribution Á 9 Common Workflow Language Project, Automated installation http://www.commonwl.org 10 Apache Software Foundation, Forest Hill MD, USA 11 Max-Planck-Institute for Evolutionary Biology, Plo¨n, 1 Introduction Germany 12 Department of Systems Biology and Bioinformatics, An enormous amount of data is available in public data- University of Rostock, Rostock, Germany bases, institutional data archives or generated locally. This 13 Computational Biology Unit, Department of Informatics, remote wealth is immediately downloadable, but its inter- University of Bergen, Bergen, Norway pretation is hampered by the variation of samples and their 123 Robust Cross-Platform Workflows: How Technical and Scientific Communities Collaborate to… 233 biomedical condition, the technological preparation of the 2 Methods sample and data formats. In general, all sciences are challenged with data management, and particle physics, The foundations of functional workflows are sources for astronomy, medicine and biology are particularly known readily usable software. The software tools of interest are for data-driven research. normally curated by maintainers into installable units that The influx of data further increases with more technical we will generically call ‘‘packages’’. We reference the advances and higher acceptance in the community. With following package managers that can be installed on one more data, the pressure raises on researchers and service single system and, together, represent all bioinformatics groups to perform analyses quickly. Local compute facil- open-source software packages in use today: ities grow and have become extensible by public clouds, • Debian GNU/Linux (http://www.debian.org) is a soft- which all need to be maintained and the scientific execu- ware distribution that encompasses the kernel (Linux) tion environment be prepared. plus a large body of other user software including Software performing the analyses steadily gains func- graphical desktop environments, server software and tionality, both for the core analyses and for quality control. specialist software for scientific data processing. New protocols emerge that need to be integrated in existing Debian and its derivatives share the deb package for- pipelines for researchers to keep up with the advances in mat with a long history of community support for knowledge and technology. Small research groups with a bioinformatics packages [26, 27]. focus on biomedical research sensibly avoid the overhead • GNU Guix (https://www.gnu.org/software/guix/)isa entailed in developing full solutions to the analysis problem package manager of the GNU project that can be or becoming experts in all details of these long workflows, installed on top of other Linux distributions and rep- instead concentrating on the development of a single soft- resents the most rigorous approach towards dependency ware tool for a single step in the process. Best practices management. GNU Guix packages are uniquely iso- emerge, are evaluated in accompanying papers and are then lated by a hash value computed over all inputs, shared with the community in the most efficient way [37]. including the source package, the configuration and all Over the past 5 years, with the avalanche of high- dependencies. This means that it is possible to have throughput sequencing data in particular, the pressure on multiple versions of the same software and even dif- research groups has risen drastically to establish routines in ferent combinations of software, e.g. Apache with ssl non-trivial data processing. Companies like Illumina offer and without ssl compiled in on a single system. hosted bioinformatics services (http://basespace.illumina. • Conda (https://conda.io/docs/) is a package installation com/) which developed into a platform in its own right. tool that, while popularised by the Anaconda Python This paper suggests workflow engines to take the position distribution, can be used to manage software written in of a core interface between the users and a series of any language. Coupled with Bioconda [7](https://bio communities to facilitate the exchange, verification and conda.github.io/), its software catalogue provides efficient execution of scientific workflows [32]. Prominent immediate access to many common bioinformatics examples of workflow and workbench applications are packages. Apache Taverna [38], with its seeds in the orchestration of • Brew (https://brew.sh) is a package manager that dis- web interfaces; Galaxy [1, 11], which is popular for tributes rules to compile source packages, originally allowing the end-users’ modulation of workflows in nucleic designed to work on macOS but capable of managing acid sequencing analysis and other fields; the lightweight software on Linux environments as well. highly compatible Nextflow [8]; and KNIME [5] which has emerged from machine learning and cheminformatics The common workflow language (CWL) [3] is a set of environments and is now also established for bioinfor- open-community-made standards with a reference imple- matics routine sequence analyses [13].1 mentation for maintaining workflows with a particular Should all these workflow frameworks bring the soft- strength for the execution of command-line tools. CWL ware for the execution environment with them (Fig. 1)or will be adopted also by already established workflow suites should they depend on system administrators to provide the like Galaxy and Apache Taverna. It is also of interest as an executables and data they need? abstraction layer to reduce complexity in current hard- coded pipelines. The CWL standards provide 1 For a growing list of alternative workflow engines and formalisms, • formalisms to derive command-line invocations to see https://github.com/common-workflow-language/common-work flow-language/wiki/Existing-Workflow-systems and https://github. software com/pditommaso/awesome-pipeline. An overview of workbench • modular, executable descriptions of workflows with applications in bioinformatics is in [23, 36] and [18] pp. 35–39, http:// auto-fulfillable specifications of run-time dependencies bora.uib.no/bitstream/handle/1956/10658/thesis.pdf#page=35. 123 234 S. Mo¨ller et al. Fig. 1 Workflow specifications comprise formal references to a range of packages to be installed without specifying the execution environment. The separation between problem- specific software, and the packages a Linux distribution provides, is fluid The community embracing the CWL standards provides versions of two
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