Tootfinder

WiNNbeta: Batch and drift correction method by white noise normalization for metabolomic studies
Olga Demler, Franco Giulianini, Yanyan Liu, Malte Londschien, Anja Sj\"ostr\"om, Tanmay Tanna, Heike Luttmann-Gibson, Antoine Jeanrenaud
https://arxiv.org/abs/2404.07906

WiNNbeta: Batch and drift correction method by white noise normalization for metabolomic studies
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.

WiNNbeta: Batch and drift correction method by white noise normalization for metabolomic studies
Olga Demler, Franco Giulianini, Yanyan Liu, Malte Londschien, Anja Sj\"ostr\"om, Tanmay Tanna, Heike Luttmann-Gibson, Antoine Jeanrenaud
https://arxiv.org/abs/2404.07906

WiNNbeta: Batch and drift correction method by white noise normalization for metabolomic studies
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.