Litcius/Paper detail

metabolomicsR: a streamlined workflow to analyze metabolomic data in R

Xikun Han, Liming Liang

2022Bioinformatics Advances15 citationsDOIOpen Access PDF

Abstract

Summary: metabolomicsR is a streamlined, flexible and user-friendly R package to preprocess, analyze and visualize metabolomic data. metabolomicsR includes comprehensive functionalities for sample and metabolite quality control, outlier detection, missing value imputation, dimensional reduction, batch effect normalization, data integration, regression, metabolite annotation and visualization of data and results. In this application note, we demonstrate the step-by-step use of the main functions from this package. Availability and implementation: The metabolomicsR package is available via CRAN and GitHub (https://github.com/XikunHan/metabolomicsR/). A step-by-step online tutorial is available at https://xikunhan.github.io/metabolomicsR/docs/articles/Introduction.html. Supplementary information: online.

Topics & Concepts

Computer scienceWorkflowData miningNormalization (sociology)VisualizationOutlierImputation (statistics)R packageMissing dataDatabase normalizationDatabaseCluster analysisArtificial intelligenceMachine learningComputational scienceAnthropologySociologyMetabolomics and Mass Spectrometry StudiesCell Image Analysis TechniquesGut microbiota and health