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) Jg. 35; H. 24; S. 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
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Oxford University Press 15.12.2019
Schlagworte:	Applications Notes
ISSN:	1367-4803, 1367-4811, 1367-4811
Online-Zugang:	Volltext
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Beschreibung
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.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1367-4803 1367-4811 1367-4811
DOI:	10.1093/bioinformatics/btz566