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dc.contributor.authorIacovacci, J.
dc.contributor.authorLin, W.
dc.contributor.authorGriffin, J. L.
dc.contributor.authorGlen, R. C.
dc.date.accessioned2021-10-25T15:11:55Z
dc.date.available2021-10-25T15:11:55Z
dc.date.issued2021-09-25
dc.date.submitted2021-05-09
dc.identifier.issn1573-3882
dc.identifier.others11306-021-01841-z
dc.identifier.other1841
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/329853
dc.description.abstractAbstract: 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.
dc.languageen
dc.publisherSpringer US
dc.subjectOriginal Article
dc.subjectIonomics
dc.subjectNetwork biology
dc.subjectGalaxy platform
dc.titleIonFlow: a galaxy tool for the analysis of ionomics data sets
dc.typeArticle
dc.date.updated2021-10-25T15:11:54Z
prism.issueIdentifier10
prism.publicationNameMetabolomics
prism.volume17
dc.identifier.doi10.17863/CAM.77298
dcterms.dateAccepted2021-09-13
rioxxterms.versionofrecord10.1007/s11306-021-01841-z
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidIacovacci, J. [0000-0002-1430-5062]
dc.identifier.eissn1573-3890
pubs.funder-project-idWellcome Trust (202952/D/16/Z)


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