WiNNbeta: Batch and drift correction method by white noise normalization for metabolomic studies
Abstract
We developed a method called batch and drift correction method by White Noise Normalization (WiNNbeta) to correct individual metabolites for batch effects and drifts. This method tests for white noise properties to identify metabolites in need of correction and corrects them by using fine-tuned splines. To test the method performance we applied WiNNbeta to LC-MS data from our metabolomic studies and computed CVs before and after WiNNbeta correction in quality control samples.
0
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.