Abstract
BackgroundData handling in clinical bioinformatics is often inadequate. No freely available tools provide straightforward approaches for consistent, flexible metadata collection and linkage of related experimental data generated locally by vendor software.ResultsTo address this problem, we created LabPipe, a flexible toolkit which is driven through a local client that runs alongside vendor software and connects to a light-weight server. The toolkit allows re-usable configurations to be defined for experiment metadata and local data collection, and handles metadata entry and linkage of data. LabPipe was piloted in a multi-site clinical breathomics study.ConclusionsLabPipe provided a consistent, controlled approach for handling metadata and experimental data collection, collation and linkage in the exemplar study and was flexible enough to deal effectively with different data handling challenges.
Highlights
Data handling in clinical bioinformatics is often inadequate
While there are open source tools available which improve on this situation [2, 3], our team required a tool which was flexible enough to be able to handle multiple different configurations for metadata entry and experimental data linkage depending on the data being collected and the vendor software being used on local PCs
The toolkit consists of LabPipe Server (LPS): a group of light-weight REpresentational State Transfer (REST) based APIs; and LabPipe Client (LPC): a locally installed front-end to support and manage local data/metadata collection and configuration
Summary
A key challenge in clinical bioinformatics is handling the collation and collection of experimental data sets from multiple sites and research groups. While some vendor software is fully automated and provides an end-to-end system for collecting data and metadata, in many cases this is not the case and software is closed, proprietary and limited with a lack of external connectivity. This means data management is often a manual adhoc process, which leads to an approach that is inadequate, slow and potentially errorridden [1]. The toolkit consists of LabPipe Server (LPS): a group of light-weight REpresentational State Transfer (REST) based APIs; and LabPipe Client (LPC): a locally installed front-end to support and manage local data/metadata collection and configuration. The server stores configurations in a document-based NoSQL database, which allows more flexibility than a relational database
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