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 |
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| container_title | Bioinformatics (Oxford, England) |
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| creator | 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 |
| description | 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. |
| doi_str_mv | 10.1093/bioinformatics/btz566 |
| format | Article |
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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Oxford Journals Open Access Collection; PubMed Central; Alma/SFX Local Collection |
| subjects | Applications Notes |
| title | The nPYc-Toolbox, a Python module for the pre-processing, quality-control and analysis of metabolic profiling datasets |
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