a QC-based normalization method for large-scale untargeted metabolomics.
- address: http://serrf.fiehnlab.ucdavis.edu
- functionality:
- use quality control (QC) samples to build SERRF to normalize biology samples and validate samples.
- calculate relative standard deviation (RSD) on the validate samples to access performance quantitatively.
- perform principal component analysis (PCA) to access performance visually.
more tutorial and explanation available online. The online version have only be tested in a limited number of data sets. If any error/suggestion, please feel free to contact me at slfan@ucdavis.edu. I'll try my best to answer your question within 24 hours.
Sili Fan, Tomas Cajka, Stanley L. Hazen, W.H. Wilson T ang, Dinesh K. Barupal, and Oliver Fiehn. Systematical Error Removal using Random Forest (SERRF) for large-scale untargeted metabolomics