The nPYc-Toolbox, a Python module for the pre-processing, quality-control and analysis of metabolic profiling datasets

As large-scale metabolic phenotyping studies become increasingly common, the need for systemic methods for pre-processing and quality control (QC) of analytical data prior to statistical analysis has become increasingly important, both within a study, and to allow meaningful inter-study comparisons....

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Veröffentlicht in:Bioinformatics (Oxford, England) England), 2019-12, Vol.35 (24), p.5359-5360
Hauptverfasser: Sands, Caroline J, Wolfer, Arnaud M, Correia, Gonçalo D S, Sadawi, Noureddin, Ahmed, Arfan, Jiménez, Beatriz, Lewis, Matthew R, Glen, Robert C, Nicholson, Jeremy K, Pearce, Jake T M
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Sprache:eng
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Zusammenfassung:As large-scale metabolic phenotyping studies become increasingly common, the need for systemic methods for pre-processing and quality control (QC) of analytical data prior to statistical analysis has become increasingly important, both within a study, and to allow meaningful inter-study comparisons. The nPYc-Toolbox provides software for the import, pre-processing, QC and visualization of metabolic phenotyping datasets, either interactively, or in automated pipelines. The nPYc-Toolbox is implemented in Python, and is freely available from the Python package index https://pypi.org/project/nPYc/, source is available at https://github.com/phenomecentre/nPYc-Toolbox. Full documentation can be found at http://npyc-toolbox.readthedocs.io/ and exemplar datasets and tutorials at https://github.com/phenomecentre/nPYc-toolbox-tutorials.
ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/btz566