Imperial College London
Alternate

DrBeatrizJimenez

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

NMR Manager
 
 
 
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Contact

 

+44 (0)20 7594 2441b.jimenez Website

 
 
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Location

 

E306Burlington DanesHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Sands:2019:bioinformatics/btz566,
author = {Sands, C and Wolfer, A and DS, Correia G and Sadawi, N and Ahmed, A and Jimenez, B and Lewis, M and Glen, R and Nicholson, J and Pearce, J},
doi = {bioinformatics/btz566},
journal = {Bioinformatics},
pages = {5359--5360},
title = {The nPYc-Toolbox, a Python module for the pre-processing, quality-control, and analysis of metabolic profiling datasets},
url = {http://dx.doi.org/10.1093/bioinformatics/btz566},
volume = {35},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Summary: As large-scale metabolic phenotyping studies become increasingly common, the need forsystemic methods for pre-processing and quality control (QC) of analytical data prior to statistical analysishas 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 visualisation of metabolicphenotyping datasets, either interactively, or in automated pipelines.Availability and Implementation: The nPYc-Toolbox is implemented in Python, and is freelyavailable from the Python package index https://pypi.org/project/nPYc/, source isavailable at https://github.com/phenomecentre/nPYc-Toolbox. Full documentation canbe found at http://npyc-toolbox.readthedocs.io/ and exemplar datasets and tutorials athttps://github.com/phenomecentre/nPYc-toolbox-tutorials
AU  - Sands,C
AU  - Wolfer,A
AU  - DS,Correia G
AU  - Sadawi,N
AU  - Ahmed,A
AU  - Jimenez,B
AU  - Lewis,M
AU  - Glen,R
AU  - Nicholson,J
AU  - Pearce,J
DO  - bioinformatics/btz566
EP  - 5360
PY  - 2019///
SN  - 1367-4803
SP  - 5359
TI  - The nPYc-Toolbox, a Python module for the pre-processing, quality-control, and analysis of metabolic profiling datasets
T2  - Bioinformatics
UR  - http://dx.doi.org/10.1093/bioinformatics/btz566
UR  - http://hdl.handle.net/10044/1/71957
VL  - 35
ER  -
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