IonFlow: a galaxy tool for the analysis of ionomics data sets
Publication Date
2021-09-25Journal Title
Metabolomics
ISSN
1573-3882
Publisher
Springer US
Volume
17
Issue
10
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Iacovacci, J., Lin, W., Griffin, J. L., & Glen, R. C. (2021). IonFlow: a galaxy tool for the analysis of ionomics data sets. Metabolomics, 17 (10) https://doi.org/10.1007/s11306-021-01841-z
Abstract
Abstract: Introduction: Inductively coupled plasma mass spectrometry (ICP-MS) experiments generate complex multi-dimensional data sets that require specialist data analysis tools. Objective: Here we describe tools to facilitate analysis of the ionome composed of high-throughput elemental profiling data. Methods: IonFlow 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 Conclusion: The pipeline is described and tested on two benchmark data sets of the haploid S. Cerevisiae ionome and of the human HeLa cell ionome.
Keywords
Original Article, Ionomics, Network biology, Galaxy platform
Sponsorship
Wellcome Trust (202952/D/16/Z)
Identifiers
s11306-021-01841-z, 1841
External DOI: https://doi.org/10.1007/s11306-021-01841-z
This record's URL: https://www.repository.cam.ac.uk/handle/1810/329853
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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