Artigo Acesso aberto Revisado por pares

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform

2016; Elsevier BV; Volume: 22; Issue: 3 Linguagem: Inglês

10.1177/1087057116679993

ISSN

2472-5560

Autores

Ioannis K. Moutsatsos, Imtiaz Hossain, Claudia Agarinis, Fred Harbinski, Yann Abraham, Luc Dobler, Xian Zhang, Christopher J. Wilson, Jeremy L. Jenkins, Nicholas Holway, John A. Tallarico, Christian N. Parker,

Tópico(s)

Scientific Computing and Data Management

Resumo

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

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