TidyMass an object-oriented reproducible analysis framework for LC–MS data - Xiaotao Shen; Hong Yan; Chuchu Wang; Peng Gao; Caroline H. Johnson; Michael P. Snyder (Nature Communications, 2022)
Reproducibility, traceability, and transparency have been long-standing issues in metabolomics data analysis. Here, the authors present tidyMass, an R-based computational framework that allows designing traceable, shareable, and reproducible data processing and analysis workflows for untargeted metabolomics.