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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Bibliographic Details
Published in:	Bioinformatics (Oxford, England) Vol. 35; no. 24; pp. 5359 - 5360
Main Authors:	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
Language:	English
Published:	England Oxford University Press 15.12.2019
Subjects:	Applications Notes
ISSN:	1367-4803, 1367-4811, 1367-4811
Online Access:	Get full text
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Summary:	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.
Bibliography:	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