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.
- Xiaotao Shen
- Hong Yan
- Michael P. Snyder