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IonFlow: a galaxy tool for the analysis of ionomics data sets.
Iacovacci, J; Lin, W; Griffin, J L; Glen, R C.
Afiliación
  • Iacovacci J; Department of Metabolism Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK. j.iacovacci@imperial.ac.uk.
  • Lin W; Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK. j.iacovacci@imperial.ac.uk.
  • Griffin JL; Department of Metabolism Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
  • Glen RC; Department of Metabolism Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Metabolomics ; 17(10): 91, 2021 09 25.
Article en En | MEDLINE | ID: mdl-34562172
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.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae Límite: Humans Idioma: En Revista: Metabolomics Año: 2021 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae Límite: Humans Idioma: En Revista: Metabolomics Año: 2021 Tipo del documento: Article