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

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 com...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954639/
https://www.ncbi.nlm.nih.gov/pubmed/31350543
http://dx.doi.org/10.1093/bioinformatics/btz566
Descripción
Sumario: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. AVAILABILITY AND IMPLEMENTATION: 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.