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LabPipe: an extensible bioinformatics toolkit to manage experimental data and metadata

Authors :
Timothy J Coats
Dahlia Salman
Leong L. Ng
Salman Siddiqui
Paul S. Monks
Robert C. Free
Wadah Ibrahim
Amisha Singapuri
Michael Wilde
C. L. Paul Thomas
Dorota Ruszkiewicz
Toru Suzuki
Rebecca Cordell
Luke Bryant
Erol A. Gaillard
Bo Zhao
Caroline Beardsmore
Neil J. Greening
Christopher E. Brightling
Source :
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-7 (2020), BMC Bioinformatics
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

Background Data 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. Results To 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. Conclusions LabPipe 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.

Details

ISSN :
14712105
Volume :
21
Database :
OpenAIRE
Journal :
BMC Bioinformatics
Accession number :
edsair.doi.dedup.....e7b464f293722e9f085db20b1895dd9d