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BibTex format

@article{Iacovacci:2021:10.1007/s11306-021-01841-z,
author = {Iacovacci, J and Lin, W and Griffin, JL and Glen, RC},
doi = {10.1007/s11306-021-01841-z},
journal = {Metabolomics},
pages = {1--12},
title = {IonFlow: a galaxy tool for the analysis of ionomics data sets},
url = {http://dx.doi.org/10.1007/s11306-021-01841-z},
volume = {17},
year = {2021}
}
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TY  - JOUR
AB  - IntroductionInductively coupled plasma mass spectrometry (ICP-MS) experiments generate complex multi-dimensional data sets that require specialist data analysis tools.ObjectiveHere we describe tools to facilitate analysis of the ionome composed of high-throughput elemental profiling data.MethodsIonFlow is a Galaxy tool written in R for ionomics data analysis and is freely accessible at https://github.com/wanchanglin/ionflow. It is designed as a pipeline that can process raw data to enable exploration and interpretation using multivariate statistical techniques and network-based algorithms, including principal components analysis, hierarchical clustering, relevance network extraction and analysis, and gene set enrichment analysis.Results and ConclusionThe pipeline is described and tested on two benchmark data sets of the haploid S. Cerevisiae ionome and of the human HeLa cell ionome.
AU  - Iacovacci,J
AU  - Lin,W
AU  - Griffin,JL
AU  - Glen,RC
DO  - 10.1007/s11306-021-01841-z
EP  - 12
PY  - 2021///
SN  - 1573-3882
SP  - 1
TI  - IonFlow: a galaxy tool for the analysis of ionomics data sets
T2  - Metabolomics
UR  - http://dx.doi.org/10.1007/s11306-021-01841-z
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000699015800001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://link.springer.com/article/10.1007%2Fs11306-021-01841-z
VL  - 17
ER  -
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