Tools to preprocess, analyse, and visualize metabolomics data. We included a set of functions for sample and metabolite quality control, outlier detection, missing value imputation, dimensional reduction, normalization, data integration, regression, metabolite annotation, enrichment analysis, and visualization of data and results. The package is designed to be a comprehensive R package that can be easily used by researchers with basic R programming skills. The framework designed here is versatile and is extensible to other various methods.
|Bioconductor views||MassSpectrometry Metabolomics Normalization QualityControl Regression Software|
|Maintainer||Xikun Han <email@example.com>|
|Package repository||View on GitHub|
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