Imputomics : web server and R package for missing values imputation in metabolomics data
Chilimoniuk, Jaroslaw (Medical University of Białystok (Polònia))
Grzesiak, Krystyna (Medical University of Białystok (Polònia))
Kała, Jakub (Medical University of Białystok (Polònia))
Nowakowski, Dominik (Medical University of Białystok (Polònia))
Krętowski, Adam (Medical University of Białystok (Polònia))
Kolenda, Rafał (Wrocław University of Environmental and Life Sciences (Polònia))
Ciborowski, Michał (Medical University of Białystok (Polònia))
Burdukiewicz, Michał (Universitat Autònoma de Barcelona)

Data:	2024
Resum:	Missing values are commonly observed in metabolomics data from mass spectrometry. Imputing them is crucial because it assures data completeness, increases the statistical power of analyses, prevents inaccurate results, and improves the quality of exploratory analysis, statistical modeling, and machine learning. Numerous Missing Value Imputation Algorithms (MVIAs) employ heuristics or statistical models to replace missing information with estimates. In the context of metabolomics data, we identified 52 MVIAs implemented across 70 R functions. Nevertheless, the usage of those 52 established methods poses challenges due to package dependency issues, lack of documentation, and their instability. Our R package, 'imputomics', provides a convenient wrapper around 41 (plus random imputation as a baseline model) out of 52 MVIAs in the form of a command-line tool and a web application. In addition, we propose a novel functionality for selecting MVIAs recommended for metabolomics data with the best performance or execution time. 'imputomics' is freely available as an R package () and a Shiny web application (). The documentation is available at .
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Publicat a:	Bioinformatics, Vol. 40 (february 2024) , ISSN 1367-4811

DOI: 10.1093/bioinformatics/btae098
PMID: 38377398

4 p, 1.9 MB

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